39
CHAPTER 4
DATA ANALYSIS AND INTERPRETATION
4.1 INTRODUCTION
Mutual funds are the best vehicle for investors, looking for ways to
put their savings into stock market (Ajit Dayal , 2011). Tax Saving Mutual
Fund Schemes were established with the objective of inviting Indian Tax
assessees into the stock market-oriented investment. All Tax Saving Mutual
Fund Schemes have same the objective but each scheme differs in returns
produced and risks involved. Majority of investors may choose a scheme with
the aim of gaining capital appreciation and fair rate of return by minimum
investment. The risk associated with the investment differs from Investors’
behaviour. Tax saving mutual fund is one avenue which offers an investor the
opportunity to avail tax exemption on investment along with market-related
return with the diversified risks. As such, analyses have been made in this
chapter to know about risk adjusted return of all the growth oriented Tax
Saving Mutual Fund Schemes in India and about the investors’ behaviour
towards risk and return of Tax Saving Mutual Fund Schemes.
Indian mutual fund market has 32 growth-oriented open-ended Tax
Saving Mutual Fund Schemes and 12 growth-oriented closed-ended Tax
Saving Mutual Fund Schemes. Table 4.1 and Table 4.2 show various growth-
oriented open and closed-ended schemes. From the table, it is also noted that
the number of schemes increased after the year 2005. SBI Magnum was the
first Tax saving mutual fund scheme launched in the 1993 and UTI - Master
40
Equity Plan Unit Scheme was the first close-ended Tax saving mutual fund
scheme launched in the year 2003. The growth of close-ended schemes was
lower than the growth of open-ended schemes.
Table 4.1 Open-Ended Tax Saving Mutual Fund Schemes - Growth
S.No Open-Ended Schemes(as on March 2011) Date of Inception
1. SBI Magnum Tax gain Scheme 24-February-19932. Canara Robeco Equity Tax saver 25- February -19933. HDFC TaxSaver 18-December-19954. LICMF Tax plan 11-January-19975. Sahara Tax Gain 31- December -19976. Franklin India Tax shield 10-April-19997. ICICI Prudential Tax Plan 09-August-19998. UTI - ETSP 15-November-19999. Escorts Tax Plan 01- April -200010. HDFC Long Term Advantage Fund 26- December -200011. ING Tax Savings Fund 12- February -200412. Sundaram Tax Saver OE 04-May-200513. Reliance Tax Saver (ELSS) Fund 25-July-200514. L&T Tax Saver Fund 27-September-200515. Kotak Tax Saver-Scheme 29- September -200516. BNP Paribas Tax Advantage Plan (ELSS) 07- November -200517. Fidelity Tax Advantage Fund 05- January -200618. DWS Tax Saving Fund 24- January -200619. Birla Sun Life Tax Plan 03-October-200620. HSBC Tax Saver Equity Fund 20- November -200621. Religare Tax Plan 20- November -200622. DSP Black Rock Tax Saver Fund 27- November -200623. Taurus Tax Shield 05-March-200724. JM Tax Gain Fund 24- December -200725. Bharti AXA Tax Advantage Fund-ECO Plan 12- February -200826. Bharti AXA Tax Advantage Fund-Regular Plan 12- February -200827. Birla Sun Life Relief 96 03-June-200828. IDFC Tax Advantage (ELSS) Fund 01- December -200829. Quantum Tax Saving Fund 10- December -200830. JPMorgan India Tax Advantage Fund 18- December -200831. Edelweiss ELSS Fund 26- December -200832. Axis Tax Saver Fund 17- December -2009Source : www.AMFIIndia.com
41
Table 4.2 Close-Ended Tax Saving Mutual Fund Schemes - Growth
S.No. Close-Ended Schemes(as on March 2011) Date of Inception
1. UTI - Master Equity Plan Unit Scheme 31-March-20032. Tata Tax Advantage Fund -1 16-January-20063. IDFC Tax Saver (ELSS) Fund 20- November -20064. ING Retire Invest Fund Series I 7- December -20065. UTI Long Term Advantage Fund 21- December -20066. Religare AGILE Tax Fund 15-November-20077. SBI Tax Advantage Fund –Series I 3- December -20078. Reliance Equity Linked Saving Fund-Series I 18- December -20079. UTI-Long Term Advantage Fund Series -II 19- December -200710. Tata Infrastructure Tax Saving Fund 17- December -200811. L&T Tax Advg Fund - Series I 19- December -200812. ICICI Prudential R.I.G.H.T. Fund 9-June-2009
Source : www.AMFIIndia.com
Since, Union KBC Tax Saver Scheme was launched during
November 2011, it has not been considered for the present study.
4.2 TOOLS APPLIED TO MEASURE RISK AND RETURN
The aim of this study is to estimate risk-return profiles for Tax
Saving Mutual Fund Schemes that have been varied from time to time. For
the purpose of study, daily NAV are used for computing annual returns of Tax
Saving Mutual Fund Schemes (John Sorros, 2004). Mean returns are
calculated by averaging the monthly returns over the relevant time period.
Total risk (volatility) is measured by the standard deviation of
returns. Systematic (market) risk is estimated by Beta. GARCH and TARCH
is to estimate volatility of schemes. All the Tax Saving Mutual Fund Schemes
are analysed by using Capital Asset Pricing Models such as Sharpe to
measure Risk premium related to the total risk, Treynor to measure Fund’s
performance in relation to the market performance and Jensen’s Alpha is used
to compare the actual or realized return of the portfolio with the predicted or
42
calculated return. Other than Capital Asset Pricing Model, Fama-French three
factor model is used analysis the performance of TSMF. The relationship
between the market benchmark S&P CNX Nifty and Tax Saving Mutual Fund
Schemes have been analysed using regression. The details of the tools used in
this study are given here.
NAV is the change in the net asset value of mutual fund over a time
period. It is a better measure for comparing the relative performance of
several funds. Return can be calculated by using the formula given below,
Current value of the units – previous value of the units Simple Return = x 100 (4.1)
Previous value of the units
The standard deviation is a measure of variability which is used as
the standard measure of the total risk of individual assets and the residual risk
of portfolios of assets. This can be calculated by using the formula:
N2
ii 1
1 (x )N
(4.2)
Where,
xi = Sample data value
N = Sample Size
The Beta stock or portfolio is a number describing the
volatility of an asset in relation to the volatility of the market benchmark. An
asset has a Beta of zero if its returns change independently of changes in the
market's returns. A positive Beta indicates that the asset's returns generally
43
follow the market's returns (Punithavathy Pandian, 2006). A negative Beta
indicates that the asset's returns generally move opposite the market's returns.
p m
m
Co var iance(r , r )Variance(r )
(4.3)
Where, rp = Realised return on the portfolio
rm = Market Return
ARCH is econometric term developed in 1982 by Robert F. Engle,
an economist. This model describes an approach to estimate volatility in
financial markets. The ARCH process is often preferred by financial
modeling professionals because it provides a more real-world context than
other forms when trying to predict the prices and rates of financial
instruments. There are several forms of ARCH modeling such as GARCH,
TARCH, APARCH, GJR are used to measure volatility in financial market.
To measure the volatility of Tax Saving Mutual Fund Schemes GARCH and
TARCH models are used in this study
The Generalized Autoregressive Conditional Heteroskedasticity
(GARCH) model of Bollerslev (1986) is based on an infinite ARCH
specification and it allows reducing the number of estimated parameters by
imposing nonlinear restrictions on them.
Threshold ARCH (TARCH) model of Zakoian (1994) is to divide
the distribution of the innovations into disjoint intervals and then approximate
a piecewise linear function for the conditional standard deviation.
Sharpe measure was developed by William Sharpe are referred to
as the Sharpe ratio. In this ratio, variability of return or risk is measured by
the standard deviation of return. The index assigns the highest values to assets
44
that have best risk-adjusted average rate of return (Punithavathy Pandian,
2006). The formula for calculating Sharpe ratio is given below.
Sharpe Ratio (SR) = p f
p
r r(4.4)
Where, rp = Realised return on the portfolio
rf = Risk free rate of return
p = Standard deviation of the portfolio
Treynor Ratio, the performance measure developed by Jack
Treynor is referred as Treynor ratio or reward to volatility ratio. In this ratio,
volatility of return as measured by the portfolio Beta (Punithavathy Pandian,
2006). The formula for calculating Treynor ratio is given below.
Treynor ratio (TR) = p f
p
r r(4.5)
Where, rp = Realised return on the portfolio
rf = Risk free rate of return
p = Portfolio Beta
Jensen Ratio is another type of risk adjusted performance measure
developed by Michael Jensen and referred to as the Jensen measure or Alpha
ratio. This ratio attempts to measure the differential between the actual return
earned on a portfolio and the return expected from the portfolio given its level
of risk (Punithavathy Pandian, 2006). The formula for calculating Jensen ratio
is given below.
Jensen Ratio (JR) = rp – (rf + p (rm - rf) ) (4.6)
45
Where, rp = Realised return on the portfolio
rf = Risk free rate of return
p = Portfolio Beta
rm = Market Return
Fama–French three-factor model is designed by Eugene Fama and
Kenneth French to describe stock returns. This model uses three variables.
They are market, size and stocks with a high book-to-market ratio (BtM,
customarily called value stocks, contrasted with growth stocks).
– (4.7)
where, r = Portfolio's expected rate of return
Rf = Risk-free return rate
Km = Return of the whole stock market
SMB = Small [market capitalization] Minus Big
HML = High [book-to-market ratio] Minus Low
4.3 EMPIRICAL RESULTS OF TAX SAVING MUTUAL FUND
SCHEMES
The empirical results pertaining to Return of Tax Saving Mutual
Fund Schemes, Standard Deviation, Sharpe, Treynor, Alpha and Beta of
Thirty Two open-ended and twelve close-ended Tax Saving Mutual Fund
Schemes and fama-french three factor model of thirty one Tax Saving Mutual
Fund Schemes have been presented in this chapter. The study has used 364
day Government securities (Treasury Bills) return has been taken as the proxy
for the risk free instrument and S&P CNX Nifty index as market benchmark
for the market portfolio as it is visible, leading and widely acknowledged by
the market participants.
46
4.3.1 Results of Average Monthly Return
Table 4.3 presents the empirical results for the return of open-ended
Tax Saving Mutual Fund Schemes - Growth with S&P CNX Nifty. Franklin
India Tax shield has given the highest return of 12.25 percent as average
monthly return during the period 1998-99.
It is evident that the average monthly return of all the schemes
during the year 2009-10 is higher than the risk free market return. All the
schemes underperformed and produced negative return during the period
2008-09 and lower than the stock market index S&P CNX Nifty (-1.98
percent). Global economic crisis was the main reason for the poor
performance of the schemes during the period 2008-09. The overall
performance of SBI Magnum Tax Gain was better and ranked 1 by comparing
other Tax Saving Mutual Fund Schemes. Table 4.4 presents the monthly
average return of close-ended Tax Saving Mutual Fund Schemes. Tata Tax
advantage fund is ranked on the top 1 by evaluating its average return since
inception. Religare AGILE Tax Fund is in the last position with lower
average return of -0.29. 9 (75.5 percent) schemes were found to be
significantly positive. It can be found that open-ended mutual fund scheme of
SBI has been found to be superior and performance of close-ended scheme of
SBI was not good. The return of all the close-ended schemes was good during
the year 2009-10 except ICICI Prudential R.I.G.H.T Fund. Majority of both
open and close-ended tax saving mutual funds average return was lower than
the market benchmark S&P CNX Nifty.
Table 4.3 Monthly Average Return of Open-Ended Tax Saving Mutual Fund Schemes - Growth
S. No
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
Average Monthly Return
Rank
1. SBI Magnum Tax gain Scheme 0.40 2.33 10.37 -3.64 -1.00 1.96 5.61 3.69 4.59 1.96 1.96 -3.40 4.96 -0.29 -0.32 3.14 12. Canara Robeco Equity Tax saver 0.37 1.93 7.41 -3.73 0.98 -1.60 3.69 1.47 3.74 0.34 0.75 -2.53 5.91 0.47 -0.06 1.28 12
3. HDFC TaxSaver 9.77 -2.13 1.46 -1.15 5.97 3.84 4.63 -0.20 1.96 -2.87 5.81 0.53 -0.32 2.10 24. LICMF Tax plan -4.25 -0.20 -1.35 4.74 -0.41 5.18 -0.75 1.79 -3.40 3.68 0.25 -0.86 0.37 285. Sahara Tax Gain 4.56 1.57 -2.26 -0.40 2.93 -2.63 4.98 0.37 -0.88 0.92 176. Franklin India Tax shield 12.25 -2.76 0.71 -1.09 5.47 1.57 3.70 -0.87 2.53 -2.52 4.80 0.66 -0.20 1.87 3
7. ICICI Prudential Tax Plan -4.75 1.70 -1.55 7.09 4.86 4.40 -0.45 1.68 -3.07 6.39 0.41 -0.05 1.11 148. UTI – ETSP -0.97 0.60 -0.42 4.47 1.41 3.37 -1.06 2.52 -3.19 4.13 0.09 -0.15 0.90 189. Escorts Tax Plan -1.48 0.08 0.80 3.27 1.99 4.19 2.39 2.66 -5.57 4.12 -0.28 -0.60 0.96 1610. HDFC Long Term Advantage Fund 1.15 0.55 6.88 3.24 4.12 -0.20 1.60 -3.16 5.31 0.92 -1.24 1.74 511. ING Tax Savings Fund-Growth 0.67 0.01 0.65 -4.42 5.48 0.66 -0.34 0.39 27
12. Sundaram Tax Saver OE -1.30 2.84 -2.83 4.27 -0.10 -0.89 0.33 2913. Reliance Tax Saver (ELSS) Fund -0.33 1.08 -2.48 4.55 0.69 -0.45 0.51 2314. L&T Tax Saver Fund -0.32 0.94 -4.30 6.08 -0.03 0.00 0.40 25
15. Kotak Tax Saver-Scheme 0.72 1.85 -3.85 4.77 0.03 -1.16 0.39 2616. BNP PARIBAS Tax Advantage Plan -0.75 1.95 -3.94 4.00 -0.07 -0.54 0.11 3117. Fidelity Tax Advantage Fund 0.33 2.30 -2.40 4.89 0.91 0.31 1.06 1518. DWS Tax Saving Fund 3.10 -3.44 4.15 -0.49 -0.52 0.56 22
19. Birla Sun Life Tax Plan 1.72 -3.24 4.59 0.21 -0.95 0.47 2420. HSBC Tax Saver Equity Fund 1.83 -2.33 4.65 -0.10 -0.68 0.67 21
Table 4.3 (Continued)
S. No
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
21. Religare Tax Plan 2.12 -3.23 5.3522. DSP Black Rock Tax Saver Fund 3.20 -3.14 5.23
23. Taurus Tax Shield 4.52 -2.40 5.0324. JM Tax Gain Fund -6.38 4.0825. Bharti AXA Tax Advantage Fund-
ECO Plan5.98
26. Bharti AXA Tax Advantage Fund-Regular Plan
5.95
27. Birla Sun Life Relief 96 5.4728. IDFC Tax Advantage (ELSS) Fund 4.2829. Quantum Tax Saving Fund 4.72
30. JP Morgan India Tax Advantage Fund
3.90
31. Edelweiss ELSS Fund 3.6532. Axis Tax Saver Fund
Bench Mark - S&P CNX NIFTY 2.00 0.58 3.55 -1.31 0.51 -0.49 5.43 1.85 4.71 1.55 2.72 -1.98 5.47Source : Secondary DataNote : Cells with blanks are unavailable data
Table 4.4 Monthly Average Return of Close-Ended Tax Saving Mutual Fund Schemes
S. No.
Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08 2008x-09 2009-10 2010-11
1 UTI - Master Equity Plan Unit Scheme 0.40 2.24 -2.42 2.96 0.35
2 Tata Tax Advantage Fund -1 3.26 2.14 -2.59 4.55 0.55
3 IDFC Tax Saver (ELSS) Fund 1.04 -3.05 4.60 -0.01
4 ING Retire Invest Fund Series I 0.69 -3.65 3.73 -0.23
5 UTI Long Term Advantage Fund 1.09 -3.44 4.83 -0.13
6 Religare AGILE Tax Fund -2.91 1.88 0.29
7 SBI Tax Advantage Fund - Series I -2.95 3.57 -0.80
8 Reliance Equity Linked Saving Fund –Series I -2.32 4.55 0.48
9 UTI-Long Term Advantage Fund Series -II -1.97 4.31 0.27
10 Tata Infrastructure Tax Saving Fund 3.97 -0.96
11 L&T Tax Advg Fund - Series I 2.07 -0.18
12 ICICI Prudential R.I.G.H.T. Fund 1.00 0.50
Source : Secondary DataNote : Cells with blanks are unavailable data
50
4.3.2 Results of Standard Deviation
Table 4.5 presents empirical results of standard deviation of Tax
Saving Mutual Fund Schemes. It reveals that all the schemes had highest
volatility during the period 2008-09. The scheme with lowest standard
deviation was Escorts Tax Plan with the standard deviation of 8.09 during the
period 2008-2009.
It is found that the average market risk of a few schemes was higher
than the stock market index. Average standard deviation of 24 (75 percent)
schemes was lower than the stock market benchmark S&P CNX Nifty during
the period of study. It can be noted that newly launched schemes like Axis
Tax saver fund‘s standard deviation was lower than the stock market but it is
not advisable to invest in that by considering only standard deviation.
By considering more than 10 years old schemes, HDFC Long term
Advantage Fund, Escorts Tax Plan and UTI ETSP performed well. The
average volatility of these schemes was in the range of 5.47 to 5.51 which is
lower than the stock market benchmark during the period of study.
Table 4.6 presents the standard deviation of close-ended Tax
Saving Mutual Fund Schemes. UTI Long Term Advantage Fund has highest
volatility and ICICI Prudential R.I.G.H.T. Fund has lowest volatility during
the study period. Majority of the open and close-ended schemes performed
better than the stock market index S & P CNX Nifty.
Table 4.5 Standard Deviation of Open-Ended Tax Saving Mutual Fund Schemes - Growth
S. No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
Average Standard deviation
Rank
1. SBI Magnum Tax gain Scheme 8.00 7.82 15.24 12.16 8.36 6.82 6.37 6.37 5.22 6.24 6.52 10.81 8.74 4.69 5.13 7.90 292. Canara Robeco Equity Tax saver 4.42 5.35 10.10 10.80 8.22 7.41 6.19 6.40 6.30 6.67 9.90 11.78 9.25 1.55 0.21 6.97 193. HDFC TaxSaver 10.16 7.94 4.96 4.97 6.79 5.93 5.87 6.93 7.74 10.97 7.71 1.77 1.06 6.11 94. LICMF Tax plan 4.61 6.70 8.60 6.14 6.45 5.57 7.55 8.59 10.92 9.09 0.83 2.93 6.50 145. Sahara Tax Gain 6.82 5.69 19.64 5.72 8.19 9.90 9.12 1.21 0.68 6.82 176. Franklin India Tax shield 16.73 8.12 6.71 5.05 5.39 5.63 5.56 5.56 7.62 10.22 6.60 2.20 0.18 6.35 137. ICICI Prudential Tax Plan 9.28 6.01 6.29 8.76 7.17 5.93 7.71 7.98 12.45 7.53 1.38 0.50 6.12 108. UTI – ETSP 11.69 6.60 4.20 5.13 5.38 5.05 6.48 7.62 9.59 7.37 0.30 1.99 5.51 59. Escorts Tax Plan 5.44 6.07 5.50 8.20 4.75 4.89 5.33 8.73 8.09 8.74 0.91 4.11 5.47 310. HDFC Long Term Advantage Fund 4.56 4.31 6.78 5.11 4.74 5.45 6.55 10.30 7.50 4.74 5.38 5.48 411. ING Tax Savings Fund-Growth 5.14 7.91 8.09 13.18 9.45 4.73 4.23 7.12 2012. Sundaram Tax Saver OE 7.43 8.92 8.64 9.55 5.00 5.70 7.54 2613. Reliance Tax Saver (ELSS) Fund 7.04 8.60 8.97 7.26 5.25 6.43 7.26 2114. L&T Tax Saver Fund 6.23 7.36 13.46 9.70 5.13 5.63 7.92 3015. Kotak Tax Saver-Scheme 7.60 7.89 11.20 9.31 4.84 5.83 7.78 2816. BNP PARIBAS Tax Advantage Plan 8.52 9.83 10.33 7.02 5.26 4.27 7.54 2517. Fidelity Tax Advantage Fund 5.99 7.33 9.92 6.97 4.53 5.20 6.66 1618. DWS Tax Saving Fund 9.44 11.21 6.89 5.12 5.24 6.32 1219. Birla Sun Life Tax Plan 8.33 10.38 8.70 4.42 5.14 7.39 22
Table 4.5 (Continued)
S. No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008
20. HSBC Tax Saver Equity Fund 8.33 8.6321. Religare Tax Plan 6.36 10.4422. DSP Black Rock Tax Saver Fund 9.72 10.2223. Taurus Tax Shield 9.95 11.8824. JM Tax Gain Fund 14.2525. Bharti AXA Tax Advantage Fund-
ECO Plan26. Bharti AXA Tax Advantage Fund-
Regular Plan27. Birla Sun Life Relief 9628. IDFC Tax Advantage (ELSS) Fund29. Quantum Tax Saving Fund30. JP Morgan India Tax Advantage Fund31. Edelweiss ELSS Fund32. Axis Tax Saver Fund
Bench Mark - S&P CNX NIFTY 8.05 7.72 7.62 7.83 6.13 5.98 7.06 7.11 6.45 6.21 9.10 11.00Source: Secondary Data
Note : Cells with blanks are unavailable data
Table 4.6 Standard Deviation of Close-Ended Tax Saving Mutual Fund Schemes
S. No. Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08 2008-09 2009-10 2010-11
1 UTI - Master Equity Plan Unit Scheme 6.84 7.49 9.90 6.25 4.552 Tata Tax Advantage Fund -1 5.51 7.45 10.17 7.51 4.103 IDFC Tax Saver (ELSS) Fund 8.05 7.85 6.76 4.824 ING Retire Invest Fund Series I 9.11 9.72 6.84 4.315 UTI Long Term Advantage Fund 8.31 10.74 7.98 4.666 Religare AGILE Tax Fund 9.41 5.91 4.667 SBI Tax Advantage Fund - Series I 10.65 8.18 4.468 Reliance Equity Linked Saving Fund –Series I 9.73 7.26 5.729 UTI-Long Term Advantage Fund Series -II 6.33 6.84 4.61
10 Tata Infrastructure Tax Saving Fund 8.35 5.4311 L&T Tax Advg Fund - Series I 5.52 4.6912 ICICI Prudential R.I.G.H.T. Fund 2.69 4.34
Source : Secondary Data
Note : Cells with blanks are unavailable data
54
4.3.3 Results of Beta Ratio
Table 4.7 shows the Beta value of all the open-ended Tax Saving
Mutual Fund Schemes. The Beta value of the market is always 1. The average
Beta of all the tax saving mutual funds is positive. Zero Beta value tells that
the scheme performance is not depending on the market performance. No
schemes have the average Beta value zero, which means all the schemes
depends on the market performance. Negative Beta value tells that the scheme
performance is opposite to market performance. It has been found that LIC
MF tax plan has negative Beta for the year 2000-01 to 2004-05. The average
Beta value of all other Tax Saving Mutual Fund Schemes is positive during
the period of study.
Table 4.8 shows the Beta of close-ended Tax saving mutual funds.
Other than ICICI Prudential R.I.G.H.T. Fund all close-ended funds moves
along with the market performance which has positive Beta value. The return
or loss of tax saving mutual funds is mainly depends on the market
performance.
55
Table 4.7 Beta Ratio of Open-Ended Tax Saving Mutual Fund Schemes – Growth
S.No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
AverageBeta
1. SBI Magnum Tax gain Scheme 0.65 0.79 0.96 1.29 1.38 0.94 0.77 0.77 0.49 1.00 0.70 0.99 0.90 0.76 0.80 0.882. Canara Robeco Equity Tax saver 0.14 0.29 0.29 1.16 1.23 1.02 0.69 0.85 0.75 1.04 0.94 1.07 0.97 0.57 0.65 0.783. HDFC TaxSaver 1.06 1.02 0.74 0.69 0.90 0.77 0.71 1.13 0.83 0.99 0.80 0.65 0.79 0.854. LICMF Tax plan 0.88 -0.35 -1.04 -0.07 -0.43 0.21 1.19 0.90 1.00 0.95 0.78 0.93 0.415. Sahara Tax Gain 0.93 0.74 0.67 0.89 0.88 0.91 0.95 0.65 0.86 0.836. Franklin India Tax shield 0.61 0.99 1.10 0.76 0.72 0.75 1.25 0.85 0.84 0.94 0.68 0.74 0.72 0.847. ICICI Prudential Tax Plan 1.28 0.97 0.87 1.05 0.92 1.20 1.04 0.78 1.10 0.78 0.71 0.97 0.978. UTI – ETSP 1.57 1.09 0.67 0.72 0.70 1.10 1.05 0.82 0.89 0.76 0.81 0.73 0.919. Escorts Tax Plan 0.66 0.94 -0.60 0.76 -0.11 0.77 0.58 0.89 0.72 0.84 0.73 1.29 0.62
10. HDFC Long Term Advantage Fund 0.66 0.46 0.67 0.61 0.96 0.82 0.67 0.93 0.78 0.74 0.83 0.7411. ING Tax Savings Fund-Growth 1.21 1.13 0.75 1.21 0.99 0.73 0.73 0.8912. Sundaram Tax Saver OE 0.63 0.97 0.75 1.00 0.77 0.86 0.8313. Reliance Tax Saver (ELSS) Fund 1.05 0.84 0.80 0.73 0.79 0.96 0.8614. L&T Tax Saver Fund 0.91 0.77 1.24 0.99 0.82 0.86 0.9315. Kotak Tax Saver-Scheme 1.12 0.81 1.04 0.97 0.52 0.90 0.8916. BNP PARIBAS Tax Advantage Plan 1.31 1.03 0.30 0.73 0.81 0.64 0.8017. Fidelity Tax Advantage Fund 0.97 0.78 0.92 0.72 0.70 0.80 0.8218. DWS Tax Saving Fund 0.16 1.04 1.04 0.72 0.75 0.78 0.7519. Birla Sun Life Tax Plan 0.84 0.97 0.91 0.70 0.78 0.8420. HSBC Tax Saver Equity Fund 0.87 0.80 0.79 0.82 0.73 0.8021. Religare Tax Plan 0.61 0.96 0.75 0.65 0.26 0.65
Table 4.7 (Continued)
S.No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
200708
22. DSP Black Rock Tax Saver Fund 0.9523. Taurus Tax Shield 0.9724. JM Tax Gain Fund
25. Bharti AXA Tax Advantage Fund-ECO Plan
26. Bharti AXA Tax Advantage Fund-Regular Plan
27. Birla Sun Life Relief 96
28. IDFC Tax Advantage (ELSS) Fund
29. Quantum Tax Saving Fund
30. JP Morgan India Tax Advantage Fund
31. Edelweiss ELSS Fund
32. Axis Tax Saver FundSource : Secondary DataNote : Cells with blanks are unavailable data
Table 4.8 Beta Ratio of Close-Ended Tax Saving Mutual Fund Schemes
S.No Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08
2008-09
2009-10
1 UTI - Master Equity Plan Unit Scheme -0.01 1.91 3.37 2.042 Tata Tax Advantage Fund -1 -0.10 1.89 3.35 2.693 IDFC Tax Saver (ELSS) Fund 0.56 1.47 2.444 ING Retire Invest Fund Series I 1.90 3.35 2.325 UTI Long Term Advantage Fund 2.05 3.62 2.876 Religare AGILE Tax Fund 3.24 1.387 SBI Tax Advantage Fund - Series I 3.38 2.728 Reliance Equity Linked Saving Fund - Series I 3.00 2.549 UTI-Long Term Advantage Fund Series -II 1.98 2.4610 Tata Infrastructure Tax Saving Fund 2.5611 L&T Tax Advg Fund - Series I 0.5912 ICICI Prudential R.I.G.H.T. Fund -0.65
Source : Secondary DataNote : Cells with blanks are unavailable data
58
4.3.4 The Behavior of Volatility of ARCH models
Table 4.9 shows the result of GARCH and TARCH of open-ended
Tax Saving Mutual Fund Schemes. Monthly average return of open end tax
savings schemes for the period 1997-98 to 2011-12 and monthly average
return of close-ended schemes for the period 2005-06 to 2011-12 have been
taken for the study. Monthly return of Tax Saving Mutual Fund Schemes is
taken as dependent variable and return of market index S&P CNX Nifty are
taken as independent variable (Oana Madalina Predescu and Stelian Stancu,
2011). To find out the volatility in Open-ended tax saving mutual fund returns
the following hypothesis is framed and tested by using GARCH and TARCH
models.
Null hypothesis (H0): There is no volatility in Open-ended tax saving
mutual fund returns and market benchmark S&P
CNX Nifty.
The GARCH test results of variance equation for open-ended
TSMF shows that P-value of GARCH is 0.5911 which is not significant at 5%
level. Hence, the Null hypothesis is accepted and there is no volatility in
average of open-ended Tax Saving Mutual Fund Schemes return and market
benchmark S&P CNX Nifty return. P-value of TARCH for open-ended
TSMFs is 0.0009 which is significant at 1% level. Hence, the Null hypothesis
is rejected and there is volatility in average of open-ended Tax Saving Mutual
Fund Schemes return and market benchmark S&P CNX Nifty return.
It is found that Alpha and Beta parameters in the open-ended
TARCH model are significant. Thus, TARCH can be the possible
representative of the conditional volatility process for the open-ended TSMF
and market benchmark S&P CNX Nifty return. Further diagnostic checking
for model selection reveals that TARCH is a better fit than the GARCH
models available for the average of Tax Saving Mutual Fund Schemes, both
59
Akaike criterion and Schwarz criterion are smaller and the log-likelihood
function has smaller value as compared to the GARCH models for average of
Tax Saving Mutual Fund Schemes. Hence, it is concluded that the average of
all open-ended schemes, the conditional volatility of the market benchmark
follows TARCH process. The parameter estimates of the TARCH models are
statistically significant except the market benchmark S&P CNX Nifty return.
In TARCH, the estimate of Beta (1) is markedly larger than those
of Alpha (1) and the sum of Beta (1) + Alpha (1) is not close to unity. It can
be observed that Beta (1) + Alpha (1) is equal to 0. 81647 for average of Tax
Saving Mutual Fund Schemes. This is less than unity indicating no violation
of the stability condition. The sum, however, is rather close to one, which
indicates a no long persistence of shocks in volatility.
Table 4.9 Coefficient of ARCH Models (Open-Ended)
Dependent Variable: Tax Saving Mutual Fund Schemes Observation period : 1997:2011Included observations: 180
SNo CoefficientAverage of all schemes (Open-
Ended)GARCH TARCH
1 Benchmark S&PCNX Nifty return
-0.191493 (0.5911)
-0.804397 (0.0009 ***)
2 Alpha (1) 0.228580 (0.0399**)
0.263273(0.0066***)
3 Beta (1) 0.651983 (3.24e-06 ***)
0.553192 (0.0015***)
4 Alpha(1)+ Beta (1) 0.88056 0.816475 Log-likelihood -602.42369 -598.218256 Akaike criterion 1214.84738 1208.436507 Schwarz criterion 1230.81216 1227.594248 Hannan-Quinn 1221.32041 1216.20414
Note : Values in parenthesis are P-values
** significant at 1% level of significance
*** significant at 5% level of significance
60
Further, to find out the volatility in close-ended tax saving mutual
fund returns the following hypothesis is framed and tested by using GARCH
and TARCH models.
Null hypothesis (H0): There is no volatility in close-ended tax saving
mutual fund returns and market benchmark S&P
CNX Nifty.
Table 4.10 shows GARCH and TARCH test results of variance
equation for close-ended TSMF. P-value of GARCH model is 0.0008 which
is significant at 1% level. Hence, the Null hypothesis is rejected and volatility
is existed in average of Tax Saving Mutual Fund Schemes and market
benchmark S&P CNX Nifty return. P-value of TARCH is 0.0152 which is
statistically significant at 1% level. Hence, the Null hypothesis is rejected and
volatility is existed in average of Tax Saving Mutual Fund Schemes and
market benchmark S&P CNX Nifty return based.
It is found that Alpha and Beta parameters in close-ended GARCH
and TARCH models are significant. Thus, both the models can be the possible
representative of the conditional volatility process for the close-ended TSMF
and market benchmark S&P CNX Nifty return. Further diagnostic checking
for model selection reveals that GARCH is a better fit than the TARCH
models available for the average of Tax Saving Mutual Fund Schemes, both
Akaike criterion and Schwarz criterion are smaller and the log-likelihood
function has smaller value as compared to the other TARCH models for
average of Tax Saving Mutual Fund Schemes. Hence, it is concluded that the
average of all close-ended schemes, the conditional volatility of the market
benchmark follows GARCH process. The parameter estimates of the GARCH
models are statistically significant.
61
In GARCH and TARCH, the estimate of Beta (1) is markedly
larger than those of Alpha (1) and the sum of Beta (1) + Alpha (1) is close to
unity. It can be observed that Beta (1) + Alpha (1) is equal to 0.9151 and
0.9527 in GARCH and TARCH respectively for average of Tax Saving
Mutual Fund Schemes. This is close to unity indicating violation of the
stability condition. Further diagnostic checking for model selection reveals
that GARCH is a better fit than the TARCH models available for the average
of Tax Saving Mutual Fund Schemes.
Table 4.10 Coefficient of ARCH Models (Close-Ended)
Dependent Variable: Tax Saving Mutual Fund SchemesObservation period : 2005-06:2011-12Included observations: 84
SNo CoefficientAverage of all schemes (Close-
Ended)GARCH TARCH
1 Benchmark S&PCNX Nifty return
0.685108(0.0008***)
0.426642(0.0152**)
2 Alpha (1) 0.0386662(0.3330)
0.0539060(0.1287)
3 Beta (1) 0.876402(1.33e-060 ***)
0.898795(4.24e-053 ***)
4 Alpha(1)+ Beta (1) 0.915068 0.9527015 Log-likelihood -267.85103 -267.562956 Akaike criterion 545.70206 547.125907 Schwarz criterion 557.85614 561.710808 Hannan-Quinn 550.58790 552.98891
Note : Values in parenthesis are P-values.
** Significant at 1% level of significance.
*** Significant at 5% level of significance.
4.3.5 Results of Sharpe Ratio
The empirical results pertaining to Sharpe ratio of open-ended Tax
Saving Mutual Fund Schemes - Growth have been presented in Table 4.11.
Sharpe ratio measures the total risk of the funds on the basis of return per unit
62
of total risk. A high and positive Sharpe Ratio shows a superior risk-adjusted
performance of a fund, a low and negative Sharpe Ratio indicates unfavorable
performance.
A close examination of Table 4.11 indicates that out of 32 mutual
fund schemes, the average Sharpe value of 29 (90.63 percent) open-ended Tax
Saving Mutual Fund Schemes were positive. The highest average Sharpe
value 0.32 was obtained by HDFC Long term advantage fund, the lowest
average Sharpe measure of -0.09 was obtained by Kotak Tax Saver-Scheme-
Growth during the period of study. Total risks of all the schemes were very
high and produced negative Sharpe during the period 2008-09. The average
Sharpe value of 21 (65.63 percent) schemes was lower than S&P CNX Nifty
(0.16).
Table 4.12 shows the risk adjusted Sharpe measures of close-ended
Tax Saving Mutual Fund Schemes - Growth. It has been found that 75 percent
of close-ended schemes were significantly positive. Average Sharpe value of
Tata Tax Advantage Fund -1 was the high and it was very low in SBI Tax
advantage fund-Series I during the period of study.
63
Table 4.11 Sharpe Ratio of Open-Ended Tax Saving Mutual Fund Schemes - Growth
S. No.
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
AverageSharpe
Rank
1. SBI Magnum Tax gain Scheme 0.05 0.28 0.67 -0.31 -0.13 -0.30 0.87 0.57 0.87 0.30 0.29 -0.32 0.56 -0.08 -0.08 0.22 52. Canara Robeco Equity Tax saver 0.06 0.34 0.72 -0.35 0.11 -0.22 0.59 0.22 0.58 0.04 0.07 -0.22 0.63 0.25 -0.72 0.14 143. HDFC TaxSaver 0.95 -0.28 0.28 -0.24 0.87 0.63 0.77 -0.04 0.24 -0.27 0.74 0.25 -0.38 0.27 24. LICMF Tax plan -0.94 -0.04 -0.16 0.76 -0.07 0.92 -0.11 0.20 -0.32 0.40 0.20 -0.33 0.04 285. Sahara Tax Gain 0.66 0.26 -0.12 -0.08 0.35 -0.27 0.54 0.23 -0.43 0.13 166. Franklin India Tax shield 0.73 -0.35 0.09 -0.23 1.00 0.27 0.65 -0.17 0.32 -0.25 0.72 0.26 -0.77 0.17 87. ICICI Prudential Tax Plan -0.52 0.27 -0.26 0.80 0.67 0.73 -0.07 0.20 -0.25 0.84 0.24 -0.47 0.18 78. UTI – ETSP -0.09 0.08 -0.11 0.86 0.25 0.65 -0.18 0.32 -0.34 0.55 0.02 -0.34 0.14 159. Escorts Tax Plan -0.29 0.00 0.14 0.39 0.40 0.84 0.43 0.30 -0.70 0.46 -0.39 -0.32 0.10 19
10. HDFC Long Term Advantage Fund 0.24 0.11 1.01 0.62 0.85 -0.05 0.23 -0.31 0.70 0.18 -0.08 0.32 111. ING Tax Savings Fund-Growth 0.94 -0.01 0.07 -0.34 0.57 0.12 -0.23 0.16 1112. Sundaram Tax Saver OE -0.19 0.31 -0.34 0.44 0.20 -0.09 0.06 2513. Reliance Tax Saver (ELSS) Fund -0.06 0.12 -0.28 0.62 0.11 -0.01 0.08 2014. L&T Tax Saver Fund -0.06 0.12 -0.32 0.62 -0.02 -0.22 0.02 2915. Kotak Tax Saver-Scheme 0.08 0.22 -0.35 -0.35 -0.01 -0.11 -0.09 3216. BNP PARIBAS Tax Advantage Plan -0.10 0.19 -0.39 0.56 -0.03 0.05 0.05 2717. Fidelity Tax Advantage Fund 0.04 0.30 -0.25 0.69 0.18 -0.12 0.14 1318. DWS Tax Saving Fund 0.32 -0.31 0.59 -0.11 -0.20 0.06 2419. Birla Sun Life Tax Plan 0.20 -0.32 0.52 0.03 -0.15 0.06 2620. HSBC Tax Saver Equity Fund 0.21 -0.28 0.60 -0.04 -0.12 0.08 21
Table 4.11 (Continued)
S. No.
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
200809
21. Religare Tax Plan 0.32 -0.32
22. DSP Black Rock Tax Saver Fund 0.32 -0.31
23. Taurus Tax Shield 0.45 -0.21
24. JM Tax Gain Fund -0.45
25. Bharti AXA Tax Advantage Fund-ECO Plan
26. Bharti AXA Tax Advantage Fund-Regular Plan
27. Birla Sun Life Relief 96
28. IDFC Tax Advantage (ELSS) Fund
29. Quantum Tax Saving Fund
30. JP Morgan India Tax Advantage Fund
31. Edelweiss ELSS Fund
32. Axis Tax Saver Fund
Bench Mark - S&P CNX NIFTY 0.17 -0.02 0.41 -0.28 -0.01 -0.19 0.74 0.19 0.70 0.17 0.23 -0.29Source : Secondary DataNote : Cells with blanks are unavailable data
Table 4.12 Sharpe Ratio of Close-Ended Tax Saving Mutual Fund Schemes
S.No Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08 2008-09 2009-10 2010-11
1 UTI - Master Equity Plan Unit Scheme 0.05 0.29 -0.25 0.44 0.06
2 Tata Tax Advantage Fund -1 0.58 0.28 -0.26 0.57 0.11
3 IDFC Tax Saver (ELSS) Fund 0.12 -0.41 0.64 -0.02
4 ING Retire Invest Fund Series I 0.07 -0.38 0.51 -0.07
5 UTI Long Term Advantage Fund 0.12 -0.33 0.57 -0.04
6 Religare AGILE Tax Fund -0.32 0.30 0.04
7 SBI Tax Advantage Fund - Series I -0.28 0.41 -0.20
8 Reliance Equity Linked Saving Fund –Series I -0.25 0.59 0.07
9 UTI-Long Term Advantage Fund Series -II -0.34 0.59 0.04
10 Tata Infrastructure Tax Saving Fund 0.45 -0.19
11 L&T Tax Advg Fund - Series I 0.34 -0.05
12 ICICI Prudential R.I.G.H.T. Fund 0.36 0.10Source : Secondary DataNote : Cells with blanks are unavailable data
66
4.3.6 Results of Treynor Ratio
Table 4.13 presents the Treynor value of all Tax Saving Mutual
Fund Schemes. Treynor Ratio relates excess return to systematic risk. The
higher the Treynor Ratio, the better the performance under analysis. Canara
Robeco Equity tax saver performed well with the average Treynor value of
3.07 and Axis tax saver fund performed not good with the average Treynor
value of -3.81 during the period of study.
The Treynor value of Canara Robeco Equity Tax Saver Fund was
25.38 during the period 1999-00 which is the highest Treynor value among all
other tax saving funds during the study period. Canara Robeco Equity Tax
Saver ranked 1 by Treynor measure and Axis Tax Saver ranked last. The
average Treynor value for 15 (46.88 percent) open-ended Tax Saving Mutual
Fund Schemes was higher than the stock market benchmark.
Table 4.14 presents the Treynor measure of close-ended Tax
Saving Mutual Fund Schemes. The average Treynor value of 3 (25 percent)
close-ended Tax Saving Mutual Fund Schemes has been found positive. The
average Treynor value of Reliance Equity Linked Saving Fund - Series I -
Growth Plan was high and it was very low in IDFC Tax Saver (ELSS) Fund
than other schemes during the period 2006-07 to 2011-12.
67
Table 4.13 Treynor Ratio of Open-Ended Tax Saving Mutual Fund Schemes – Growth
S. No
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
Average Treynor Rank
1. SBI Magnum Tax gain Scheme 0.43 2.83 10.69 -2.91 -0.79 -2.19 7.24 4.72 9.29 1.88 2.68 -3.50 5.41 -0.49 -0.50 2.32 62. Canara Robeco Equity Tax saver 1.84 6.27 25.38 -3.31 0.72 -1.64 5.23 1.65 4.89 0.25 0.71 -2.44 6.02 0.67 -0.23 3.07 13. HDFC TaxSaver 9.12 -2.18 1.83 -1.78 6.59 4.89 6.43 -0.25 2.26 -2.97 7.14 0.70 -0.51 2.41 44. LICMF Tax plan -4.97 0.85 1.38 -6.23 1.10 24.67 -0.70 1.90 -3.48 3.80 0.22 -1.05 1.46 115. Sahara Tax Gain 4.84 2.05 -3.46 -0.53 3.23 -2.96 5.16 0.44 -0.34 0.94 196. Franklin India Tax shield 19.74 -2.89 0.56 -1.53 7.54 2.02 2.89 -1.12 2.91 -2.75 6.93 0.79 -0.19 2.68 27. ICICI Prudential Tax Plan -3.79 1.67 -1.87 6.72 5.22 3.60 -0.51 2.06 -2.86 8.07 0.47 -0.24 1.55 108. UTI – ETSP -0.69 0.47 -0.74 6.17 1.92 3.00 -1.08 2.96 -3.69 5.31 0.01 -0.94 1.06 179. Escorts Tax Plan -2.42 -0.01 -1.21 4.26 -1.23 5.35 3.96 2.90 -7.81 4.82 -0.49 -1.03 0.59 2510. HDFC Long Term Advantage Fund 1.61 1.03 10.16 5.21 4.22 -0.34 2.25 -3.48 6.70 1.14 -0.51 2.54 311. ING Tax Savings Fund-Growth 1.00 3.99 -0.06 0.76 -3.72 5.49 0.79 -1.50 0.84 2012. Sundaram Tax Saver OE -2.21 2.83 -3.87 4.21 -0.24 -1.50 -0.13 2913. Reliance Tax Saver (ELSS) Fund -0.39 1.18 -3.21 6.16 0.77 -0.62 0.65 2414. L&T Tax Saver Fund -0.44 1.12 -3.54 6.06 -0.13 -0.09 0.50 2615. Kotak Tax Saver-Scheme 0.57 2.18 -3.79 4.84 -0.10 -1.52 0.37 2816. BNP PARIBAS Tax Advantage Plan -0.63 1.81 -13.34 5.42 -0.18 -1.21 -1.36 3117. Fidelity Tax Advantage Fund 0.26 2.83 -2.68 6.71 1.18 0.28 1.43 1218. DWS Tax Saving Fund 2.90 -3.37 5.70 -0.76 -0.87 0.72 2219. Birla Sun Life Tax Plan 1.95 -3.44 4.97 0.19 -1.38 0.46 27
Table 4.13 (Continued)
S. No
Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
200809
20. HSBC Tax Saver Equity Fund - Growth 2.00 -2.99
21. Religare Tax Plan 3.32 -3.4422. DSP Black Rock Tax Saver
Fund 3.28 -3.40
23. Taurus Tax Shield 4.59 -2.3324. JM Tax Gain Fund -5.1625. Bharti AXA Tax Advantage
Fund-ECO Plan26. Bharti AXA Tax Advantage
Fund-Regular Plan27. Birla Sun Life Relief 9628. IDFC Tax Advantage (ELSS)
Fund29. Quantum Tax Saving Fund30. JP Morgan India Tax
Advantage Fund31. Edelweiss ELSS Fund32. Axis Tax Saver Fund
Bench Mark - S&P CNX NIFTY 1.35 -0.14 3.10 -2.19 -0.07 -1.12 5.22 1.35 4.50 1.08 2.11 -3.15
Source : Secondary DataNote : Cells with blanks are unavailable data
Table 4.14 Treynor Ratio of Close-Ended Tax Saving Mutual Fund Schemes
S. No. Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08 2008-09 2009-10 2010-11
1 UTI - Master Equity Plan Unit Scheme 0.28 1.12 -0.74 1.41 0.37
2 Tata Tax Advantage Fund -1 8.72 1.09 -0.80 1.66 0.71
3 IDFC Tax Saver (ELSS) Fund 1.72 -2.12 1.85 -0.13
4 ING Retire Invest Fund Series I 0.32 -1.11 1.57 -0.46
5 UTI Long Term Advantage Fund 1.81 -2.39 1.94 -0.29
6 Religare AGILE Tax Fund -0.92 1.31 0.29
7 SBI Tax Advantage Fund - Series I -0.89 1.28 -1.36
8 Reliance Equity Linked Saving Fund –Series I -0.80 1.76 0.47
9 UTI-Long Term Advantage Fund Series -II -1.03 1.72 0.25
10 Tata Infrastructure Tax Saving Fund 1.52 -1.29
11 L&T Tax Advg Fund - Series I 3.38 -0.42
12 ICICI Prudential R.I.G.H.T. Fund -1.46 0.64Source : Secondary DataNote : Cells with blanks are unavailable data
70
4.3.7 Results of Jensen’s Alpha Ratio
Table 4.15 presents the Jensen’s Alpha value of all the Tax Saving
Mutual Fund Schemes in India during the period 1997-98 to 2011-12. If the
Alpha for a stock or portfolio is positive it is said to be an ideal or quality
investment that will generate excess returns over a given period of time.
However, a negative Alpha points show poor future performance.
HDFC TaxSaver-Growth Plan ranked 1 during the period of study
and gained the average Alpha value of (1.24). BNP PARIBAS Tax Advantage
Plan (ELSS)-Growth Option gained lower Alpha and ranked last. For 15 (46.9
percent) schemes, Alpha has found to be significantly positive and all the
schemes’ average Alpha was lower than the average Alpha value of the stock
market S&P CNX Nifty (1.25).
Table 4.16 shows Alpha measures of close-ended schemes. It is
found that the average Alpha of 91.7 percent close-ended schemes were
significantly positive. Tata Infrastructure Tax Saving Fund ranked 1 and the
Jenson’s Alpha value of this scheme was positive during the period of study
except the year 2011-12. The average Alpha value of ICICI Prudential
R.I.G.H.T Fund was low and ranked last during the period of study. The
details of the Jensen’s Alpha calculations are given in the Appendix 3.
71
Table 4.15 Jensen’s Alpha Ratio of Open-Ended Tax Saving Mutual Fund Schemes - Growth
S. No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
Average Alpha Rank
1. SBI Magnum Tax gain Scheme -0.39 2.03 9.27 -2.43 -6.76 -1.15 5.48 3.98 1.68 0.88 -0.33 0.76 0.46 -0.51 -0.16 0.85 22. Canara Robeco Equity Tax saver 0.10 1.74 7.00 -2.65 -4.15 -0.69 3.57 1.79 -0.71 -0.78 -2.30 1.95 1.09 0.17 -0.05 0.41 103. HDFC TaxSaver 9.07 -2.13 -1.70 -0.57 5.84 4.13 0.42 -1.41 -0.74 1.29 1.80 0.33 -0.16 1.24 14. LIC MF Tax plan -3.46 1.12 -2.46 4.64 -0.53 3.91 -2.02 -1.13 0.78 -1.04 0.02 -0.69 -0.07 195. Sahara Tax Gain 4.49 1.52 -6.27 -1.36 0.07 1.19 0.25 0.16 -0.03 -0.01 166. Franklin India Tax shield 11.50 -1.85 -3.90 -0.44 5.48 1.56 -3.71 -1.80 -0.20 1.43 1.39 0.45 0.08 0.77 57. ICICI Prudential Tax Plan -3.55 -2.35 -0.79 7.09 4.85 -2.70 -1.57 -0.85 1.54 2.48 0.20 0.06 0.16 128. UTI – ETSP 0.53 -3.96 0.14 4.48 1.39 -3.13 -2.19 -0.16 0.51 0.31 -0.14 -0.46 -0.22 249. Escorts Tax Plan -0.92 -3.89 0.12 3.27 1.89 -0.38 1.73 -0.23 -2.56 -0.07 -0.49 -0.93 -0.21 2210. HDFC Long Term Advantage Fund -1.65 0.91 6.88 3.21 -1.56 -1.10 -0.61 0.73 1.41 0.70 -0.17 0.80 411. ING Tax Savings Fund-Growth -2.25 -1.20 -1.78 0.66 0.58 0.44 -0.77 -0.62 3012. Sundaram Tax Saver OE -2.01 -0.31 0.30 -0.69 0.88 -0.27 -0.35 2713. Reliance Tax Saver (ELSS) Fund -1.45 -1.65 0.85 0.92 0.46 0.20 -0.11 2014. L&T Tax Saver Fund -1.31 -1.56 0.90 1.15 -0.26 -0.98 -0.34 2615. Kotak Tax Saver-Scheme -0.47 -0.78 0.50 -0.06 -0.14 -0.35 -0.22 2316. BNP PARIBAS Tax Advantage Plan -2.14 -1.39 -2.73 0.37 -0.30 0.42 -0.96 3217. Fidelity Tax Advantage Fund -0.25 1.46 1.30 0.69 -0.36 0.57 818. DWS Tax Saving Fund -0.26 0.94 0.57 -0.71 -0.80 -0.05 18
Table 4.15 (Continued)
S. No Open-Ended Tax Saving Mutual Fund Schemes
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
200809
19. Birla Sun Life Tax Plan Growth Option -1.00 0.8020. HSBC Tax Saver Equity Fund - Growth -1.01 1.0221. Religare Tax Plan 0.11 0.8022. DSP Black Rock Tax Saver Fund 0.12 0.8223. Taurus Tax Shield 1.39 2.0624. JM Tax Gain Fund -1.1125. Bharti AXA Tax Advantage Fund-ECO
Plan26. Bharti AXA Tax Advantage Fund-
Regular Plan27. Birla Sun Life Relief 9628. IDFC Tax Advantage (ELSS) Fund29. Quantum Tax Saving Fund30. JP Morgan India Tax Advantage Fund31. Edelweiss ELSS Fund32. Axis Tax Saver Fund
Bench Mark - S&P CNX NIFTY 1.49 -0.02 3.21 -2.07 0.04 -1.03 5.29 1.41 4.56 1.16 2.18 -3.07Source : Secondary DataNote : Cells with blanks are unavailable data
Table 4.16 Jensen’s Alpha Ratio of Close-Ended Tax Saving Mutual Fund Schemes
S.No Close-Ended Tax Saving Mutual Fund Schemes 2006-07 2007-08 2008-09 2009-10 2010-11
1 UTI - Master Equity Plan Unit Scheme 0.30 7.19 -4.35 6.22 1.26
2 Tata Tax Advantage Fund -1 3.03 7.03 -4.49 8.70 1.32
3 IDFC Tax Saver (ELSS) Fund 2.43 -3.78 8.24 0.84
4 ING Retire Invest Fund Series I 5.62 -5.47 7.36 0.59
5 UTI Long Term Advantage Fund 6.40 -5.43 9.27 0.77
6 Religare AGILE Tax Fund -4.73 4.09 1.17
7 SBI Tax Advantage Fund - Series I -4.85 8.05 -0.02
8 Reliance Equity Linked Saving Fund - Series I -4.03 8.41 1.52
9 UTI-Long Term Advantage Fund Series -II -3.09 8.07 1.15
10 Tata Infrastructure Tax Saving Fund 8.01 0.04
11 L&T Tax Advg Fund - Series I 2.82 0.59
12 ICICI Prudential R.I.G.H.T. Fund -5.39 -0.45Source : Secondary DataNote : Cells with blanks are unavailable data
74
4.3.8 Regression Analysis
Regression is used to estimate the relationship between market
benchmark return and Tax Saving Mutual Fund Schemes return. Figure 4.1
shows the relationship between market benchmark S&P CNX Nifty and Tax
Saving Mutual Fund Schemes. This relationship has been obtained by
regressing the monthly average return of the tax saving mutual funds with
S&P CNX Nifty. The regression equation shows that co-efficient of the
market is 0.0054. This indicates that every additional unit in S&P CNX Nifty,
it can be expected Tax Saving Mutual Fund Schemes increase by an average
of 0.0054 units. R2 is equal to 0.6858, which shows this model is fit to
explain the dependent variable TSMF. 68% variation of the TSMF is
explained by the independent variable S&P CNX Nifty.
Source :Secondary Data
y = 0.799x + 0.0054R² = 0.6858
-30
-20
-10
0
10
20
30
40
-30.00 -20.00 -10.00 0.00 10.00 20.00 30.00 40.00
Ret
urn
of T
SMF
Benchmark S&P CNX NiftyFigure 4.1 Relationship between TSMF and Benchmark
75
Close-ended schemes have a fixed maturity. It does not highly
influenced by the market buying and selling is fixed with particular period.
The market price may not be the same as the net asset value. (Punithvathy
Pandian, 2008). Hence, regression between close-ended schemes and market
benchmark is not done.
4.3.9 Fama-French Three factor model
The traditional asset pricing model Capital Asset Pricing Model
(CAPM) uses only Beta to describe the returns of a portfolio with market
returns. Whereas, the Fama–French model uses three variables such as
market, size of the portfolio and value of the portfolio. This model used SMB
for “small (market capitalization) minus big” and HML for “high (book-to-
market ratio) minus low”. It measures the excess returns of small caps over
big caps and value stocks over growth stocks. The assets of all the 31 schemes
as on March 2012 have been considered for the study.
SMB is the difference between the average return of smallest 30%
of Tax Saving Mutual Fund Schemes and the average return of the largest
30% of the schemes assets (Kent Womack and Ying Zhang, 2003). A positive
SMB indicates that small cap stocks outperformed large cap and a negative
SMB indicates the large caps outperformed in a particular period. The five
schemes with least assets are Bharti AXA Tax Advantage Fund-ECO Plan,
Escorts Tax Plan, JPMorgan India Tax Advantage Fund, Quantum Tax
Saving Fund and Edelweiss ELSS Fund which is having less than 10 crore
assets. The schemes with greatest assets are ICICI Prudential Tax Plan,
Sundaram Tax saver OE- App, Reliance Tax Saver (ELSS) Fund, HDFC
TaxSaver and SBI Magnum Tax gain Scheme 1993 which is having more
than 1000 crores. Table 4.17 shows the assets of the schemes.
76
Table 4.17 Assets of the Tax Saving Mutual Fund Schemes
S.No Tax Saving Mutual Fund Schemes Asset (cr)1. Bharti AXA Tax Advantage Fund-ECO Plan 3.12. Escorts Tax Plan 3.83. JPMorgan India Tax Advantage Fund 4.24. Quantum Tax Saving Fund 5.55. EDELWEISS ELSS FUND 5.96. SaharaTax Gain 11.17. L&T Tax Saver Fund 27.88. ING Tax Savings Fund 29.59. Bharti AXA Tax Advantage Fund 32.510. LIC MF Tax plan 34.211. JM Tax Gain Fund 40.812. Birla Sun Life Tax Plan 45.213. DWS Tax Saving Fund 58.714. Taurus Tax Shield 72.815. Religare Tax Plan 111.516. BNP Paribas Tax Advantage Plan 118.617. IDFC Tax Advantage (ELSS) Fund 134.918. HSBC Tax Saver Equity Fund 196.219. Canara Robeco Equity Tax saver 362.420. Kotak Tax Saver-Scheme 433.121. UTI – ETSP 461.622. DSP Black Rock Tax Saver Fund 724.423. Birla Sun Life Relief 96 765.924. Franklin India Tax shield 812.425. HDFC Long Term Advantage Fund 840.526. Fidelity Tax Advantage Fund 1,167.1027. ICICI Prudential Tax Plan 1,278.4028. Sundaram Tax saver OE- App 1,391.3029. Reliance Tax Saver (ELSS) Fund 1,972.8030. HDFC TaxSaver 3,114.1031. SBI Magnum Tax gain Scheme 1993 4,778.50
Source : Secondary Data
77
HML has been constructed to measure value premium with high book
to market values. HML is the difference between the average return of the
50% of the schemes with the highest book to equity and the 50% of the
schemes with the lowest book to equity of the schemes (Kent Womack,
2003). A positive HML indicated value scheme outperformed in a particular
period and a negative HML indicates growth schemes outperformed in a
month. Table 4.18 shows the book to market ratio of the Tax Saving Mutual
Fund Schemes. The five schemes with least Book to Market Ratio are SBI
Magnum Tax gain Scheme 1993, HDFC Long Term Advantage Fund, ICICI
Prudential Tax Plan, Franklin India Tax shield and HDFC TaxSaver. The
schemes with high book to market ratio are JM Tax Gain Fund, Birla Sun Life
Relief 96 , DWS Tax Saving Fund, Birla Sun Life Tax Plan and HSBC Tax
Saver Equity Fund.
Table 4.18 Book to Market of Tax Saving Mutual Fund Schemes
Tax saving mutual fund schemes Book to MarketJM Tax Gain Fund 1.5916Birla Sun Life Relief 96 0.9930DWS Tax Saving Fund 0.8390Birla Sun Life Tax Plan 0.7669HSBC Tax Saver Equity Fund 0.7170L&T Tax Saver Fund 0.7072BNP Paribas Tax Advantage 0.6926DSP Black Rock Tax Saver Fund 0.6324Religare Tax Plan 0.5794Kotak Tax Saver-Scheme 0.5775JPMorgan India Tax Advantage fund 0.5724IDFC Tax Advantage (ELSS) Fund 0.5353Edelweiss ELSS Fund 0.5227Bharti AXA Tax Advantage Fund 0.4812Bharti AXA Tax Advantage Fund-ECO Plan 0.4778
78
Table 4.18 (Continued)
Tax saving mutual fund schemes Book to MarketFidelity Tax Advantage Fund 0.4747Reliance Tax Saver (ELSS) Fund 0.4695Quantum Tax Saving Fund 0.4538Canara Robeco Equity Tax saver 0.3852LIC MF Tax plan 0.3702ING Tax Savings Fund 0.3627Taurus Tax Shield 0.3058Sahara Tax Gain 0.2743UTI – ETSP 0.2661Escorts Tax Plan 0.2642Sundaram Tax saver OE- App 0.2384SBI Magnum Tax gain Scheme 1993 0.1714HDFC Long Term Advantage Fund 0.0747ICICI Prudential Tax Plan 0.0736Franklin India Tax shield 0.0468HDFC TaxSaver 0.0448
Source: Secondary Data
Table 4.19 summarizes the results of Fama French three factor
analysis. The tables shows the coefficients of Rm-Rf, SMB and HML that is
obtained by regressing Ri-Rf with Rm-Rf, SMB and HML. These
coefficients are substituted in Fama French three factor model to obtain the
Expected Rate of Return. Additionally, Actual Rate of Return of these
schemes have been calculated by using the historical values of past three
years from 2009-10 to 2011-12. Table 4.19 results showed that Reliance Tax
Saver (ELSS) Fund, Canara Robeco Equity Tax saver, Religare Invesco Tax
Plan, SaharaTax Gain and Bharti AXA Tax Advantage Fund-ECO Plan
performed well with high difference in expectation and actual return.
Sundaram Tax saver OE- App, Kotak Tax Saver-Scheme, DWS Tax Saving
Fund, Franklin India Tax shield and L&T Tax Saver Fund-Cumulative were
not performed well. The actual return of these schemes was lower than the
expected return.
79
There are only minimum number of close-ended schemes are available.
Hence, Fama French model is not applied with close-ended Tax Saving
Mutual Fund Schemes.
Table 4.19 Coefficients, Expected Return and Actual Rate of Return of the Tax Saving Mutual Fund Schemes
S.No Tax Saving Mutual Fund SchemesCoefficient Expected
ReturnActualReturn
DifferenceRM-RF SMB HML
1 Reliance Tax Saver (ELSS) Fund 0.7517 -0.4336 1.2158 0.1342 1.9581 1.82402 Canara Robeco Equity Tax saver 0.8306 -0.2054 0.3408 0.3615 1.3303 0.96883 Religare Tax Plan 0.6067 -0.3036 0.8697 0.1476 1.1113 0.96374 Sahara Tax Gain-Growth 0.8473 -0.0524 0.9628 0.1849 1.1274 0.94255 Bharti AXA Tax Advantage Fund-
ECO Plan 0.9886 0.2817 1.4450 0.0695 0.9150 0.8456
6 Bharti AXA Tax Advantage Fund 0.9914 0.2838 1.4270 0.0749 0.9028 0.82797 Quantum Tax Saving Fund 0.7430 0.4863 -0.0847 0.3398 1.1484 0.80868 Birla Sun Life Relief 96 0.9323 -0.3519 0.8731 0.2845 1.0911 0.80669 ING Tax Savings Fund 0.8720 0.1051 0.4753 0.2996 1.0819 0.7823
10 HDFC TaxSaver 0.8094 -0.2273 -0.1059 0.4722 1.2322 0.760011 Fidelity Tax Advantage Fund 0.7594 0.0826 0.1812 0.3339 1.0646 0.730712 SBI Magnum Tax gain Scheme 1993 0.8256 -1.0357 0.8475 0.3442 1.0743 0.730113 BNP Paribas Tax Advantage Plan 0.6877 -0.3951 0.9244 0.1788 0.8860 0.707214 Taurus Tax Shield 0.9297 0.5048 0.8527 0.1685 0.8719 0.703415 HDFC Long Term Advantage Fund 0.8248 0.0310 -0.3155 0.4966 1.1849 0.688316 IDFC Tax Advantage (ELSS) Fund 0.7319 -0.1575 1.2269 0.0845 0.7571 0.672617 Edelweiss ELSS Fund 0.6976 -0.4201 1.3587 0.0733 0.7367 0.663418 Birla Sun Life Tax Plan 0.7991 -0.4789 1.2689 0.1458 0.7698 0.624019 HSBC Tax Saver Equity Fund 0.7725 -0.1209 0.7870 0.2102 0.8338 0.623620 DSP Black Rock Tax Saver Fund 0.8269 -0.0431 0.2150 0.3699 0.9531 0.583121 JM Tax Gain Fund 0.8106 -0.1832 1.6051 0.0214 0.5077 0.486322 JPMorgan India Tax Advantage Fund 0.7487 1.1519 0.0204 0.2213 0.7066 0.485423 UTI – ETSP 0.7642 0.0118 0.4400 0.2784 0.7116 0.433124 LIC MF Tax plan 0.8821 -0.1357 0.6201 0.2997 0.5659 0.266125 Escorts Tax Plan 0.9388 1.3115 0.4344 0.1677 0.4120 0.244326 ICICI Prudential Tax Plan 0.8569 0.0149 0.1210 0.3983 0.4720 0.073827 Sundaram Tax saver OE- App 0.8731 -0.5069 1.0954 0.2246 0.2360 0.011328 Kotak Tax Saver-Scheme 0.8961 0.1592 0.7727 0.2243 0.0463 -0.178029 DWS Tax Saving Fund 0.7232 -0.2497 1.1125 0.1237 -0.1377 -0.261530 Franklin India Tax shield 0.7210 -0.1676 0.0995 0.3748 0.1093 -0.265531 L&T Tax Saver Fund 0.9494 -0.2921 0.5659 0.3629 -0.0883 -0.4512
Source: Secondary Data
Note : Fama French model has applied for three years (2009-11 to 2001-12) with 31 open ended schemes as the required data is available only for that period.
80
4.4 PRIMARY DATA ANALYSIS
An analysis on primary data always produces the exact information
about any study. As such, Investors behviour has been studied with respect to
risk and return of Tax Saving Mutual Fund Schemes. The details of analysis
have been given in this section.
4.4.1 Investors’ Preference on Investment
Investors’ preferences are not identical. Everyone has practical
advantage over others. Table 4.20 exhibits the investment preference of
sample respondents on different types of tax shielded avenues such as Term
Deposit, Insurance, Postal Savings Scheme, Monthly Income Plan and House
Construction. Respondents have chosen multiple options on their preference.
Invariably every Investor preferred Insurance plans and Tax Saving Mutual
Fund Schemes. In this chapter, a respondent of the questionnaire is also
referred as investors. Figure 4.2 shows the investment preference of the
sample respondents.
Table 4.20 Investors’ Preference on Tax Shielded Investments
(Multiple Response)
Investment Avenue Number of Respondents
Percentage of Respondents
Various Tax Saving Mutual Fund Schemes 400 100
Insurance 400 100Postal Savings 205 51Term Deposit 195 49Monthly Income Plan 121 30House Construction 108 27Other Areas 6 2Source : Primary Data
81
(Multiple Response)(Values in Percentage)
Figure 4.2 Investors’ Preference on Tax Shielded Investments
Source : Primary Data
100 percent sample respondents preferred both Insurance and Tax
Saving Mutual Fund Schemes. 51 percent respondents have preferred postal
savings, 49 percent respondents have chosen Term deposits, 30 percent
respondents have chosen Monthly Income Plan and 27 percent respondents
have chosen house construction to avail tax exemption on their income
according to the Sections 80C, 80CCA, 80CCB, 80CCC, 80CCD and 80CCF.
Insurance is one of the oldest and trusted investment instruments
used by the Indian Investors. Every investor preferred insurance plans and
they like to get benefit out of the investment in a secured way. Investors
preferred mutual fund schemes because it provides market related return,
diversified risk and tax protection on investment.
100
100
51
49
30
27 2Tax Saving Mutual Fund Schemes
Insurance
Postal Savings
Term Deposit
Monthly Income Plan
House Construction
Other Areas
82
Table 4.21 presents the investors’ choice towards Tax Saving
Mutual Fund Schemes. There are 44 growth oriented Tax Saving Mutual
Fund Schemes available in India, whereas, the respondents have chosen only
15 schemes. Any individual investor may invest in more than one area.
Hence, an investor may choose more than one option. Mean rank has been
adopted to know the choice of investors. 36 percent respondents have chosen
SBI Magnum Tax Gain Mutual Fund Schemes, 23.8 percent investors have
chosen ICICI prudential tax plan and 21 percent investors have chosen HDFC
tax saver fund.
It is also noted that the schemes chosen by the respondents are
existed in the market for more than seven years. Majority of the respondents
have chosen SBI Magnum Tax gain. The average monthly return and Alpha
value of SBI magnum tax gain was found to be good but the volatility of this
scheme was not lower than other schemes. The reason for choosing this
scheme may be that SBI magnum tax gain was the first tax saving mutual
fund Scheme in India since SBI has its own brand name for its service to their
customers in banking sector. So SBI comes first in every investor’s mind
when they want to invest in Tax Saving Mutual Fund Schemes.
It is also noted that only 14 percent of respondents have chosen
close-ended tax saving mutual fund scheme such as Reliance Equity Linked
Saving Fund-Series I and Tata Tax Advantage Fund -1. The performances of
these two schemes were found to be good according to their rate of return,
Sharpe, Treynor and Jensen’s Alpha.
83
Table 4.21 Investors’ Choice on Tax Saving Mutual Fund Schemes
(Multiple Response)
Investors’ Choice Number of respondents
Percentage ofrespondents
SBI Magnum Tax Gain 144 36.0ICICI Prudential Tax Plan 95 23.8HDFC TaxSaver 84 21.0Reliance Tax Saver (ELSS) Fund 81 20.3Sundaram Tax Saver 72 18.0Tata Tax Advantage Fund -1 48 12.0Kotak Tax Saver 39 9.8Birla Sun Life Tax Plan 30 7.5Canara Robeco Equity Tax saver 11 2.8DSP Black Rock Tax Saver 11 2.8Principal Personal Tax plan 10 2.5HDFC Long Term Advantage Fund 9 2.3Franklin India Tax shield 8 2.0Reliance Equity Linked Saving Fund –Series I 8 2.0UTI ETSP 6 1.5
Source: Primary Data
4.4.2 Investment in Tax Saving Mutual Fund Schemes
Investment varies from person to person based on respondents age,
annual income, past experience with the scheme and family size. To study the
association between these factors and investment, various hypotheses have been
framed and tested here.
Age is one of the factors for doing a certain activity. Age factor
compels people to do certain activities and prevents them from doing some
other activities. In this research, age is added as one of the factors that
influences the amount invested in Tax Saving Mutual Fund Schemes which is
84
shown in Table 4.22. 48 percent investors were in the age group of 26-35
years, 19.8 percent investors were in the age group of 36-45 years, 14.5
percent investors were below 25 years, 12.3 percent investors were in the age
group of 46-55 years and 5.5 percent investors were in the age group of 55
years and the above have invested in Tax Saving Mutual Fund Schemes.
It can also be noted from Table 4.22 that the maximum number of
investors are in the age group of 26-35 years. Individuals in the age group of
26-35 years will be more sincere to save their income for their future
commitment and their family. They are not ready to lose their money by
paying tax. Instead they would think of investing in tax shielded investment
area. Out of 192, 93 investors have invested less than Rs. 50,000, 58 percent
have invested from Rs. 50,000 to Rs. 1 lakh, 22 percent have invested from
Rs. 1 lakh to 1.5 lakhs, 17 percent have invested from Rs. 1.5 lakhs to Rs. 2
lakhs and only 2 percent have invested more than Rs. 3 lakhs in the age group
of 26-35 years. Further, hypothesis has been framed to test the association
between age and investment in Tax Saving Mutual Fund Schemes. To test this
hypothesis, chi-square test was employed.
Null hypothesis (H0): There is no association between different age
group of respondents and investment amount in
Tax Saving Mutual Fund Schemes.
The test result shows that the chi square value is significant at 1%
level. Hence, the null hypothesis is rejected and alternate hypothesis is
accepted. From the analysis, it is concluded that there is a significant
association exists between investors’ age and investment amount in the Tax
Saving Mutual Fund Schemes.
85
Table 4.22 Association between Age Groups on the Options about
Investment in Tax Saving Mutual Fund Schemes
Age groups(in years)
Amount of Investment in TSMFUp to 0.5
Lakhs0.5 to 1.0
Lakhs1.0 to 1.5
Lakhs1.5 to 2.0
Lakhs2.0 to 2.5
LakhsAbove 3.0
Lakhs Total
No. % No. % No. % No. % No. % No. % No. %Up to 25 29 16.9 16 14.2 13 22.8 0 0.0 0 0.0 0 0.0 58 14.526-35 93 54.1 58 51.3 22 38.6 17 53.1 0 0.0 2 10.0 192 48.036-45 25 14.5 22 19.5 15 26.3 5 15.6 1 16.7 11 55.0 79 19.846-55 22 12.8 8 7.1 6 10.5 6 18.8 1 16.7 6 30.0 49 12.355 and Above 3 1.7 9 8.0 1 1.8 4 12.5 4 66.7 1 5.0 22 5.5Total 172 100 113 100 57 100 32 100 6 100 20 100 400 100
Variable Chi-square Value df asymp. Sig.(2-sided)
Age and Investment in TSMF 99.777 20 .000Source : Primary Data
Individual income and expenses are the deciding factors of savings
and investment. Income has also been considered as one of the important
parameters that determine the objective of investment. Table 4.23 shows
investors’ investment amount in Tax Saving Mutual Fund Schemes according
to their Annual Income. For the sake of convenient understanding, total
investors are divided into three income groups such as up to Rs. 2 lakhs, Rs. 2
lakhs to Rs. 4 lakhs and above Rs. 4 lakhs.
The data collected through a questionnaire is given in Table 4.23,
has revealed that 33.5 percent of investors’ income level was less than Rs. 2
lakhs, 39.5 percent investors were in the income level of Rs. 2 to Rs. 4 lakhs
and 27 percent investors’ income was more than Rs. 4 lakhs. Among the
group of investors whose Annual Income is Rs. 2 lakhs to 4 lakhs, 66
respondents have invested less than Rs. 50,000, 49 respondents have invested
Rs. 50,000 to Rs. 1 lakh, 26 respondents have invested Rs. 1 lakh to Rs. 1.5
lakhs, 11 respondents have invested Rs. 1.5 lakhs to Rs. 2 lakhs, 1 respondent
86
has invested Rs. 2 lakhs to Rs. 2.5 lakhs and 5 respondents have invested
above 3 lakhs. Further, hypothesis has been framed to test the association
between Investors’ annual income and investment in Tax Saving Mutual Fund
Schemes. To test this hypothesis, chi-square test was employed.
Null Hypothesis (H0): There is no association between respondents’
annual income and investment in the Tax Saving
Mutual Fund Schemes.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between Investors’ annual income and the amount invested in Tax Saving
Mutual Fund Schemes.
Table 4.23 Association between Annual Income and the Options about
Investment in Tax Saving Mutual Fund Schemes
Annual Income
Investment in TSMFup to 0.5
Lakhs0.5 to 1.0
Lakhs1.0 to 1.5
Lakhs1.5 to 2.0
Lakhs2.0 to 2.5
LakhsAbove 3.0
Lakhs Total
No. % No. % No. % No. % No. % No. % No. %up to 2 Lakhs 72 41.9 41 36.3 19 33.3 2 6.3 0 0.0 0 0.0 134 33.52-4 Lakhs 66 38.4 49 43.4 26 45.6 11 34.4 1 16.7 5 25.0 158 39.5Above 4 Lakhs 34 19.8 23 20.4 12 21.1 19 59.4 5 83.3 15 75.0 108 27.0Total 172 100 113 100 57 100 32 100 6 100 20 100 400 100
Variable Chi-square Value df asymp. Sig. (2-sided)Annual Income and Investment in TSMF 65.213 10 .000
Source : Primary Data
Age and experience strongly influence all the activities and they
have the ability to change the decision to be taken. Investors’ past experience
in their investment activities teaches them about the risk and return from
relevant area of investment. Table 4.24 shows that among the group of
investors 158 respondents have 1 to 4 years of experience in investing in
87
TSMF, in which 37 percent of respondents invested up to Rs.50,000, 30
percent have invested between Rs. 0.5 lakhs and Rs. 1 lakhs, 17 percent have
invested Rs. 1 lakhs to Rs. 1.5 lakhs, 7 percent have invested Rs. 1.5 laks to
Rs. 2 lakhs, 4 percent have invested Rs. 2 lakhs to Rs. 2.5 lakhs and 4 percent
have invested more than Rs. 3 laks. Further, hypothesis has been framed to
test the association between the past experience with TSMF and the
investment in Tax Saving Mutual Fund Schemes. To test this hypothesis, chi-
square test was employed.
Null Hypothesis (H0) : There is no association between respondents’ past
experience with TSMF and investment in TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between the past experience and the investment in tax saving mutual funds.
Table 4.24 Association between Experience with TSMF and the Options
about the Investment in TSMF
Experience in TSMF
Number of respondents invested in TSMF Percentage of respondents invested in TSMFUp to
0.5 Lakhs
0.5 to 1.0
Lakhs
1.0 to 1.5
Lakhs
1.5 to 2.0
Lakhs
2.0 to 2.5
Lakhs
Above 3.0
LakhsTotal
Up to 0.5
Lakhs
0.5 to 1.0
Lakhs
1.0 to 1.5
Lakhs
1.5 to 2.0
Lakhs
2.0 to 2.5
Lakhs
Above 3.0
LakhsTotal
Less than 1 year 87 34 14 4 0 4 143 61 24 10 3 0 3 100
1 to 4 years 58 48 27 11 6 8 158 37 30 17 7 4 5 100
4 to 7 years 14 23 8 4 0 2 51 28 5 16 8 0 4 100
More 13 8 8 13 0 6 48 27 17 17 27 0 13 100
Variable Chi-square Value df asymp. Sig. (2-sided)Past Experience and Investment in TSMF 72.565 15 .000
Source: Primary Data
Family size is the deciding factor of family expenses. It decides the
proportion of investors’ savings habits. It can be understood from Table 4.25,
40 percent of respondents invested up to Rs. 50,000, 33 percent invested
88
between Rs. 50,000 to Rs. 1 lakhs, 11 percent invested between Rs.1 lakhs to
Rs. 1.5 lakhs, 9 percent invested between Rs.1.5 lakhs to Rs. 2 lakhs, 3
percent invested between Rs.2 lakhs to Rs. 2.5 lakhs and 4 percent invested
above Rs.2.5 lakhs whose family size is four. Further, hypothesis has been
framed to test the association between family size and investment. To test this
hypothesis, chi-square test was employed.
Null hypothesis (H0) : There is no association between respondents
family size and investment in TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between family size and investment.
Table 4.25 Association between Family Size and the Options of the
Investment in TSMF
Family Size
Number of respondents Percentage of respondentsup to 0.5
Lakhs
0.5 to 1.0
Lakhs
1.0 to 1.5
Lakhs
1.5 to 2.0
Lakhs
2.0 to 2.5
Lakhs
Above 2.5
LakhsTotal
up to 0.5
Lakhs
0.5 to 1.0
Lakhs
1.0 to 1.5
Lakhs
1.5 to 2.0
Lakhs
2.0 to 2.5
Lakhs
Above 2.5
LakhsTotal
Two 13 6 10 1 0 3 33 39 18 30 3 0 9 100Three 77 35 16 15 1 9 153 50 23 11 10 1 6 100Four 64 53 18 14 5 7 161 40 33 11 9 3 4 100
Above Four 18 19 13 2 0 1 53 34 36 25 4 0 2 100
Variable Chi-square Value df asymp. Sig. (2-sided)Family Size and Investment in TSMF 31.209 15 .008
Source : Primary Data
4.4.3 Factors considered by Investors before Investment
There are a number of factors considered by the investors while
selecting their investment avenue. Not all the factors were equally considered
by every investor. The investors’ opinion on the factors like Transparency,
Diversification, Low Cost, Convenience, Reputation, Portfolio Management,
89
Capital Appreciation, Return Potential and Security or Safety of the Tax
Saving Mutual Funds varying based on respondents demographic features.
The significant difference between these factors with respect to respondents
demographic features like Gender, Marital status, Age, Educational
qualification and Annual income have been analysed in this study.
Table 4.26 shows the factors considered by the investors. Every
investor has given importance to Security and Safety of their investment. 80.8
percent of the investors required security for their amount by AMCs. It has
mean value of 1.26. Lower mean has assigned higher value. 69.8 percent of
the investors have highly considered return potential on their investment. It
can be said that the investors of TSMF in Tamil Nadu have highly considered
Security or Safety and Return out of their investment.
Table 4.26 Mean Rank test of Factors Considered by Respondents
Factors ConsideredMeanRank
Percentage of RespondentsHighly
Considered Considered Neutral Not Considered
Highly not Considered
Security/Safety 1.26 80.8 13.8 4.8 0.5 .3Return Potential 1.44 69.8 21.8 4.5 3.0 1.0Reputation 1.47 59.0 34.8 6.3 - -Capital Appreciation 1.49 65.5 25.5 5.0 3.8 .3Convenience 1.93 35.6 43.4 14.0 6.3 .8Portfolio Mgt. 1.96 26.3 57.0 12.0 4.5 .3Low Cost 2.11 34.0 31.5 24.3 10.0 .3Transparency 2.13 30.8 37.3 22.5 7.5 2.0Diversification 2.34 30.8 26.5 25.0 14.8 3.0Source : Primary Data
Table 4.27 shows different factors considered by the respondents
and their gender. Independent sample t-test has been applied for the purpose
of analysis. The factors like Low cost, Security or Safety, Capital appreciation
and Return potential of the investment have been considered equally by both
male and female respondents. 2-tailed significant value of these variables is
90
greater than 0.05. Hence, there is no significant difference between the means
of male and female investors about these factors.
Factors like Company Reputation, Portfolio Management,
Convenience, Transparency and Diversification have been seen differently by
male and female investors. 2-tailed significant value of these factors is lesser
than 0.05. So these factors have significant difference from each other. Both
Male and Female investors considered these factors differently.
From this analysis, it can be said that the AMCs have no need to
change their strategies to market TSMFs based on cost, security or safety,
capital appreciation and return potential because both male and female
investors have considered all those factors equally. Most of the company
related variables like company reputation, portfolio management,
transparency and diversification have been seen differently by male and
female respondents. Moreover only male respondents have highly considered
these factors. It seems that female respondents do not bother about the
company policies and they only considered about the return which they will
get from their investment.
Table 4.27 Significant Difference between Mean Ranks of Factors
Considered by Respondents and Gender
Factors ConsideredMale Female
Mean Std. Deviation
Std. Error Mean Mean Std.
DeviationStd. Error
MeanCompany Reputation 1.39 .591 .035 1.69 .615 .058Portfolio Mgt. 1.90 .773 .045 2.10 .726 .069Convenience 1.84 .795 .047 2.16 1.105 .105Low Cost 2.06 .982 .058 2.24 1.029 .098Transparency 2.06 .974 .057 2.32 1.044 .099Security/Safety 1.27 .587 .035 1.23 .642 .061Capital Appreciation 1.52 .821 .048 1.42 .781 .074Diversification 2.26 1.101 .065 2.57 1.240 .118Return Potential 1.48 .854 .050 1.32 .620 .059
91
Independent Sample Test for Table 4.27 Factors Considered by Respondents and Gender
Factors
Levene’s Test for Equality of Variance
t - test for Equality of Means
F Sig. T df Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the
DifferenceLower Upper
Company Reputation 0.384 .536 -4.587 398 .000 -0.306 0.067 -0.437 -0.175Portfolio Management 0.968 .326 -2.350 398 .019 -0.199 0.085 -0.366 -0.033Convenience 18.17 .000 -3.200 397 .001 -0.319 0.100 -0.516 -0.123Low Cost 2.107 .147 -1.659 398 .098 -0.184 0.111 -0.403 0.034Transparency 4.343 .038 -2.342 398 .020 -0.260 0.111 -0.478 -0.042Security/Safety 1.431 .232 0.715 398 .475 0.048 0.067 -0.084 0.181Capital Appreciation 0.496 .482 1.018 398 .309 0.092 0.090 -0.086 0.270Diversification 4.625 .032 -2.445 398 .015 -0.312 0.127 -0.562 -0.061Return Potential 9.683 .002 1.761 398 .079 0.157 0.089 -0.018 0.331Source: Primary Data
Marriage is the process by which two people who love each other
make their relationship public, official and permanent. It gives many new
responsibilities to both male and female. It makes changes in individual
behaviour, attitude and life style. Table 4.28 represents the significant
difference between the factors considered by married and unmarried
respondents. The significant difference between the factors considered by the
respondents and their marital status has been tested with independent sample
t-test.
The factors like Portfolio management, Transparency and Security
or Safety have been considered differently by the married and unmarried
respondents. The 2-tailed Significant value of all these factors are lesser than
0.05. It is evident that there is significant difference between the means of
these factors and the marital status of respondents at 1% level of significance.
The factors like Company Reputation, Convenience, Low cost,
Capital Appreciation, Diversification and Return Potential have been equally
considered by both married and unmarried respondents. 2-tailed Significant
92
values of all these factors is greater than 0.05 which shows that both married
and unmarried respondents have not seen these factors differently (Shyan-
Rong Chou, 2010). If any new plan is introduced by AMCs, it depends on
the target group for which they shall make a different strategy. Companies
may use different strategies to attract married and unmarried respondents with
respect to the factors like portfolio management, transparency, security or
safety of TSMF which have been seen differently by married and unmarried
respondents.
Table 4.28 Significant Difference between Mean Ranks of Factors Considered by Respondents and their Marital status
Marriage
Marital StatusMarried Unmarried
Mean Std. Deviation
Std. Error Mean Mean Std.
DeviationStd. Error
MeanCompany Reputation 1.43 .629 .037 1.56 .563 .052Portfolio Mgt. 1.89 .743 .044 2.11 .796 .074Convenience 1.91 .967 .058 1.98 .719 .066Low Cost 2.07 .967 .057 2.20 1.069 .099Transparency 2.01 1.019 .061 2.41 .892 .082Security/Safety 1.17 .456 .027 1.47 .826 .076Capital Appreciation 1.47 .773 .046 1.55 .895 .083Diversification 2.36 1.157 .069 2.30 1.132 .105Return Potential 1.39 .775 .046 1.55 .846 .078
Independent Sample Test for Table 4.28 Factors Considered by Respondents and their Marital status
Factors
Levene’s Test for Equality of
Variancet - test for Equality of Means
F Sig. T df Sig. (2-tailed)
Mean Differ ence
Std. Error Diffe rence
95% Confidence Interval of the
DifferenceLower Upper
Company Reputation .773 .380 -1.930 398 .054 -.129 .067 -.261 .002Portfolio Management .059 .808 -2.646 398 .008 -.221 .083 -.385 -.057Convenience 19.278 .000 -.722 398 .471 -.072 .099 -.266 .123Low Cost 6.398 .012 -1.116 398 .265 -.122 .110 -.338 .093Transparency .070 .791 -3.696 398 .000 -.400 .108 -.612 -.187Security/Safety 65.528 .000 -4.594 398 .000 -.297 .065 -.424 -.170Capital Appreciation 4.185 .041 - .905 398 .366 -.081 .089 -.256 .095Diversification .782 .377 .485 398 .628 .061 .126 -.187 .310Return Potential 3.882 .050 -1.768 398 .078 -.155 .088 -.327 .017Source: Primary Data
93
Age is one of the main factors which decide the investment
potential of individuals. The factors considered by investors vary according to
their age group. From Table 4.29, it has been noted that there is significant
difference between the respondents’ age and their consideration on various
factors of Tax Saving Mutual Fund Schemes.
Table 4.29 shows the results of ANOVA, which has been used to
test the association between the different age group of respondents and their
consideration on various factors of Tax Saving Mutual Fund Schemes.
Through ANOVA test, it has been proved that there is no significant
difference between the means of Company Reputation, Portfolio
Management, Low Cost, Security or Safety, Diversification and different age
group of the respondents. The Significant value of all these factors are greater
than 0.05. So, respondents in all the age groups have considered these factors
similarly.
Through ANOVA test, it has been proved that the factors like
Convenience, Transparency, Capital Appreciation and Return Potential have
been considered differently by different age group of respondents. The
Significant values of all these factors are lesser than 0.05. So, there is a
significant difference between the respondents’ age and their consideration on
these factors. Convenience on investment and Transparency in procedure has
been highly considered by respondents in the age group of 46-55 years.
Capital appreciation and Return potential have been highly considered by the
respondents whose age was 50 and above.
94
Table 4.29 Mean Rank for Factors Considered by Respondents and Age
Factors Age Mean Std. Deviation
Std. Error
95% confidence interval for Mean
Lower Bound
Upper Bound
Company Reputation
Up to 25 1.50 .538 .071 1.36 1.6426-35 1.51 .622 .045 1.42 1.6036-45 1.42 .653 .073 1.27 1.5646-55 1.33 .591 .084 1.16 1.5050 and Above 1.59 .590 .126 1.33 1.85
Portfolio Management
Up to 25 1.83 .701 .902 1.64 2.0126-35 1.99 .701 .051 1.89 2.0936-45 2.04 .898 .101 1.84 2.2446-55 1.86 .816 .117 1.62 2.0950 and Above 1.91 .811 .173 1.55 2.27
Convenience
Up to 25 2.00 .725 .095 1.81 2.1926-35 1.95 .922 .067 1.82 2.0836-45 2.06 .066 .120 1.82 2.3046-55 1.57 .612 .087 1.40 1.7550 and Above 1.95 .899 .192 1.56 2.35
Low Cost
Up to 25 2.05 1.033 1.36 1.78 2.3226-35 2.18 1.040 .075 2.03 2.3336-45 2.05 .959 .108 1.84 2.2746-55 1.96 .889 .127 1.70 2.2150 and Above 2.18 .907 .193 1.78 2.58
Transparency
Up to 25 2.31 .959 .126 2.06 2.5626-35 2.19 1.007 .073 2.05 2.3436-45 2.06 .965 .109 1.85 2.2846-55 1.71 .935 .134 1.45 1.9850 and Above 2.23 1.110 .237 1.74 2.72
Security/Safety
Up to 25 1.24 .802 .105 1.03 1.4526-35 1.31 .634 .046 1.22 1.436-45 1.25 .493 .055 1.14 1.3646-55 1.18 .441 .063 1.06 1.3150 and Above 1.09 .294 .063 0.96 1.22
Capital appreciation
Up to 25 1.60 .954 .125 1.35 1.8526-35 1.47 .792 .057 1.36 1.5836-45 1.65 .892 .100 1.45 1.8546-55 1.35 .597 .085 1.18 1.5250 and Above 1.14 .468 .100 0.93 1.34
Diversification
Up to 25 2.12 1.109 .146 1.83 2.4126-35 2.38 1.173 .085 2.21 5.5436-45 2.48 1.073 .121 2.24 2.7246-55 2.29 1.118 .160 1.96 2.6150 and Above 2.27 1.352 .288 1.67 2.87
Return Potential
Up to 25 1.78 .974 .128 1.52 2.0326-35 1.38 .735 .053 1.28 1.4836-45 1.38 .789 .089 1.20 1.5646-55 1.53 .868 .124 1.28 1.7850 and Above 1.05 .213 .045 .95 1.14
95
ANOVA for Table 4.29 Factors Considered by Respondents and Age
Factors Sum of squares df Mean square F Sig.
Company Reputation
Between Groups 1.909 4 .477 1.276 .279Within Groups 147.788 395 .374Total 149.698 399
Portfolio Management
Between Groups 2.231 4 .558 9.540 .433Within Groups 230.959 395 .585Total 233.190 399
Convenience Between Groups 8.058 4 2.015 2.519 .041Within Groups 315.115 394 .800Total 323.173 398
Low Cost Between Groups 2.707 4 .677 .678 .608Within Groups 394.453 395 .999Total 397.160 399
Transparency Between Groups 11.667 4 2.917 2.978 .019Within Groups 386.831 395 .979Total 398.498 399
Security/Safety Between Groups 1.368 4 .342 .941 .440Within Groups 143.592 395 .364Total 144.960 399
Capital Appreciation
Between Groups 6.499 4 1.625 2.512 .041Within Groups 255.461 395 .647Total 261.960 399
Diversification Between Groups 4.837 4 1.209 .916 .454Within Groups 521.240 395 1.320Total 526.078 399
Return Potential Between Groups 11.340 4 2.385 4.607 .001Within Groups 243.097 395 .615Total 254.438 399
Source : Primary Data
Education is the formal process by which society deliberately
transmits its accumulated knowledge, skills, customs and values from one to
another. From the data collection, an analysis has been made to check whether
education changes the perception of respondents on the factors considered
towards the investment in Tax Saving Mutual Fund Schemes.
Table 4.30 explains the factors considered by different qualified
respondents. Through ANOVA test, it has been proved that there is a
significant difference between the factors like Convenience, Return Potential
96
and Educational Qualification of the respondents at 1% significant level and
the factors like Transparency, Capital Appreciations are significantly different
at 5% level. There is no significant difference between the factors like
Company Reputation, Portfolio Management, Low Cost, Security or Safety,
Diversification and the Educational qualification of the respondents at 5%
significant level. Convenience on investment has been highly considered by
Diploma/Under Graduate holders. Secondary School Leaving Certificate
(SSLC) holders have highly considered Transparency and Return potential of
the company. Post Graduate Degree holders have highly considered Capital
appreciation on their investment. Among all these factors invariably Security
and Return Potential have been highly considered by all the respondents.
97
Table 4.30 Mean Rank Test for Factors Considered by Respondents and
Educational qualification
Factors Educational Qualification Mean Std.
DeviationStd.
Error
95% confidence interval for Mean
Lower Bound
Upper Bound
Company Reputation
SSLC 1.25 .444 .099 1.04 1.46HSC 1.46 .779 .159 1.13 1.79Diploma/UG 1.48 .638 .054 1.37 1.58PG Degree 1.49 .587 .040 1.41 1.57
Portfolio Management
SSLC 1.55 .605 .135 1.27 1.83HSC 2.04 .690 .141 1.75 2.33Diploma/UG 1.97 .780 .065 1.84 2.10PG Degree 1.97 .769 .053 1.87 2.08
Convenience
SSLC 1.90 .788 .176 1.53 2.27HSC 2.13 .992 .202 1.71 2.54Diploma/UG 1.72 .728 .061 1.60 1.84PG Degree 2.06 .979 .067 1.92 2.19
Low Cost
SSLC 2.00 .795 .178 1.63 2.37HSC 2.42 1.018 .208 1.99 2.85Diploma/UG 1.99 .871 .073 1.85 2.14PG Degree 2.16 1.082 .074 2.02 2.31
Transparency
SSLC 1.55 .605 .135 1.27 1.83HSC 2.00 .978 .200 1.59 2.41Diploma/UG 2.07 9.270 .078 1.92 2.22PG Degree 2.23 1.058 .072 2.09 2.38
Security/Safety
SSLC 1.50 .607 .136 1.22 1.78HSC 1.25 .442 .090 1.06 1.44Diploma/UG 1.24 .595 .050 1.14 1.34PG Degree 1.25 .622 .043 1.17 1.34
Capital Appreciation
SSLC 1.85 1.040 .233 1.36 2.34HSC 1.79 .977 .199 1.38 2.20Diploma/UG 1.52 .831 .070 1.38 1.66PG Degree 1.40 .736 .050 1.30 1.50
Diversification
SSLC 2.40 1.095 .245 1.89 2.91HSC 2.75 1.073 .219 2.30 3.20Diploma/UG 2.32 1.145 .096 2.13 2.51PG Degree 2.31 1.162 .079 2.15 2.46
Return Potential
SSLC 1.20 0.696 .156 0.87 1.53HSC 1.96 1.268 .229 1.42 2.49Diploma/UG 1.43 .709 .059 1.31 1.55PG Degree 1.41 .780 .053 1.30 1.51
98
ANOVA result for Table 4.30 Factors Considered by Respondents and
Educational qualification
Factors Sum of squares df Mean
square F Sig.
Company Reputation
Between Groups 1.071 3 0.357 0.951 0.416Within Groups 148.626 396 0.375Total 149.698 399
Portfolio Management
Between Groups 3.563 3 1.188 2.048 0.107Within Groups 229.627 396 0.580Total 233.190 399
ConvenienceBetween Groups 10.692 3 3.546 4.505 0.004Within Groups 312.481 395 .791Total 323.173 398
Low CostBetween Groups 5.058 3 1.686 1.703 0.166Within Groups 392.102 396 0.990Total 392.160 399
TransparencyBetween Groups 9.934 3 3.311 3.375 0.018Within Groups 388.564 396 0.981Total 398.498 399
Security/SafetyBetween Groups 1.227 3 0.409 1.127 0.338Within Groups 143.733 396 0.363Total 144.960 399
Capital Appreciation
Between Groups 6.579 3 2.192 3.399 0.018Within Groups 255.384 396 0.645Total 261.960 399
DiversificationBetween Groups 4.393 3 1.464 1.112 0.344Within Groups 521.684 396 1.317Total 526.078 399
Return PotentialBetween Groups 7.853 3 2.618 4.204 0.006Within Groups 246.585 396 0.623Total 254.438 399
Source : Primary Data
Income of a person makes changes in his or her life, gives
confidence, motivates for further growth and it induces to save for future. Any
person whose income falls into tax slab, needs to invest money into the tax
shield area to avoid paying tax. In this research, an analysis has been made
with the respondents’ income and their consideration on various factors of
Tax Saving Mutual Fund Schemes. Table 4.31 shows the results of ANOVA
test which tells that the significant P Value of factors like Portfolio
Management, Low Cost and Transparency are lesser than 0.05. So, there is a
99
significant difference between the income level of respondents’ and their
consideration on these factors. Moreover, it can also be noted that among the
group of respondents whose salary was more than four lakhs have highly
considered all these factors. The significant value of the factors like Company
Reputation, Convenience, Security or Safety, Capital Appreciation,
Diversification and Return Potential is greater than 0.05. Hence, all income
groups of respondents equally considered these factors.
Table 4.31 Mean Ranks of Factors Considered by Respondents and
Annual income
Factors Salary Mean Std. Deviation
Std. Error
95% confidence interval for Mean
LowerBound
Upper Bound
Company Reputation
Up to 2 Lakhs 1.46 .583 .050 1.36 1.552-4 Lahks 1.49 .626 .050 1.40 1.59Above 4 Lakhs 1.46 .633 .061 1.34 1.58
Portfolio Management
Up to 2 Lakhs 1.96 .547 .047 1.86 2.052-4 Lahks 2.01 .714 .057 1.90 2.12Above 4 Lakhs 1.87 1.024 .099 1.68 2.07
ConvenienceUp to 2 Lakhs 1.77 .681 .059 1.66 1.892-4 Lahks 2.14 1.050 .083 1.97 2.30Above 4 Lakhs 1.82 .852 .082 1.66 1.99
Low CostUp to 2 Lakhs 2.04 .799 .069 1.90 2.172-4 Lahks 2.29 1.067 .085 2.12 2.46Above 4 Lakhs 1.94 1.079 .104 1.73 2.14
TransparencyUp to 2 Lakhs 2.11 .801 .069 1.98 2.252-4 Lahks 2.16 1.052 .084 2.00 2.33Above 4 Lakhs 2.09 1.140 .110 1.88 2.31
Security/SafetyUp to 2 Lakhs 1.40 .705 .061 1.28 1.522-4 Lahks 1.16 .430 .034 1.09 1.23Above 4 Lakhs 1.24 .654 .063 1.12 1.37
Capital Appreciation
Up to 2 Lakhs 1.60 .851 .073 1.45 1.742-4 Lahks 1.51 .880 .070 1.37 1.65Above 4 Lakhs 1.32 .609 .059 1.21 1.44
DiversificationUp to 2 Lakhs 2.03 .892 .077 1.88 2.182-4 Lahks 2.57 1.255 .100 2.37 2.77Above 4 Lakhs 2.40 1.191 .115 2.17 2.63
Return PotentialUp to 2 Lakhs 1.46 .701 .061 1.34 1.582-4 Lahks 1.58 .883 .070 1.44 1.72Above 4 Lakhs 1.19 .729 .070 1.06 1.33
100
ANOVA results for Table 4.31 Factors Considered by Respondents and
Annual income
Factors Sum of squares df Mean square F Sig.
Company ReputationBetween Groups 0.515 2 .258 .686 .504Within Groups 149.182 397 .376Total 149.968 399
Portfolio Management
Between Groups 4.120 2 2.06 3.570 .029Within Groups 229.070 397 .557Total 233.190 399
ConvenienceBetween Groups 3.419 2 1.709 2.117 .122Within Groups 319.754 396 .807Total 323.173 398
Low CostBetween Groups 17.350 2 8.675 9.067 .000Within Groups 379.810 397 .957Total 397.160 399
TransparencyBetween Groups 10.737 2 5.368 5.496 .004Within Groups 387.761 397 .977Total 398.498 399
Security/SafetyBetween Groups 1.607 2 .804 2.225 .109Within Groups 143.353 397 .361Total 144.96 399
Capital AppreciationBetween Groups 3.380 2 1.690 2.594 .076Within Groups 258.580 397 .651Total 261.960 399
DiversificationBetween Groups 6.546 2 3.273 2.501 .083Within Groups 519.531 397 1.309Total 526.078 399
Return PotentialBetween Groups 0.527 2 .263 .412 .663Within Groups 253.911 397 .640Total 254.438 399
Source : Primary Data
4.4.4 Factor Analysis
Factor analysis is adopted to study the dimensionality of a set of
factors considered by respondents. The results of factor analysis carried out
on ten variables that had been considered by respondents before investing in
TSMF are presented in Tables 4.32. The results of Kaiser-Meyer-Olkin
(KMO) and Bartlett’s Test indicate that a factor analysis can be applied to the
data as the value of KMO statistics is greater than 0.7 and the Bartlett’s Test
of Sphericity is significant.
101
Table 4.32 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .746
Bartlett's Test of Sphericity
Approx. Chi-Square 798.383df 36Sig. .000
Table 4.33 gives the descriptive statistics of the variables used in
the factor analysis. It can be seen from the table that the variable
Security/Safety has the highest mean (1.26) followed by Return Potential
(1.47) and Reputation (1.47). The variable Diversification has the lowest
mean (2.13). This means that the respondents are primarily concerned about
return of their investment amount and reputation / capital appreciation but
least concerned with respect to the factor diversification.
Table 4.33 Variables in the Factor Analysis
The following table presents the correlation among the variables taken
for study. It can be seen from the table that most of the variables are
positively correlated. A close look on the table may reveal the fact that the
variables security/safety, capital appreciation and return potential have low
correlations with other variables rather than the rest of the variables.
Factors Mean Std. Deviation Analysis N
Reputation 1.47 .613 400Portfolio Mgt. 1.96 .764 400Convenience 1.94 .902 400Low Cost 2.11 .998 400Transparency 2.13 .999 400Security/Safety 1.26 .603 400Capital Appreciation 1.49 .810 400Diversification 2.34 1.148 400Return Potential 1.44 .799 400
102
Correlation Matrix for Table 4.33 Factor Analysis
Reputation Portfolio Mgt. Convenience Low
Cost Transparency Security/Safety Capital Appreciation Diversification Return
Potential
Correlation
Reputation 1.000Portfolio Mgt. .393 1.000Convenience .319 .385 1.000Low Cost .296 .329 .493 1.000Transparency .462 .395 .474 .504 1.000Security/Safety -.021 -.007 .137 .002 .065 1.000Capital Appreciation
.002 .202 .129 .076 .050 .170 1.000
Diversification .304 .323 .385 .402 .578 -.042 .212 1.000Return Potential .017 .102 .127 .134 .100 .076 .319 -.033 1.000
Sig.
Reputation .000 .000 .000 .000 .335 .484 .000 .368Portfolio Mgt. .000 .000 .000 .443 .000 .000 .021Convenience .000 .000 .003 .005 .000 .006Low Cost .000 .481 .065 .000 .004Transparency .096 .161 .000 .023Security/Safety .000 .201 .066Capital Appreciation
.000 .000
Diversification .258Return Potential
103
The following table shows the number of components extracted with
eigenvalues and cumulative variance explained by them. There are only two
factors resulting from the analysis explaining a total of 50 per cent of the
variations in the entire data set. The percentage of variation is explained by
the two factors are 33.672 and 15.989 respectively after varimax rotation is
performed. Figure 4.3 shows the graph of eigenvalues of the extracted factors,
which clearly indicate that two factors have eigenvalues more than 1.
Total Variance Explained for Table 4.33 Factor Analysis
ComponentInitial Eigenvalues Extraction Sums of Squared
LoadingsRotation Sums of Squared
Loadings
Total % of Variance
Cumulative% Total % of
VarianceCumulative
% Total % of Variance
Cumulative%
1 3.096 34.395 34.395 3.096 34.395 34.395 3.031 33.672 33.6722 1.374 15.266 49.661 1.374 15.266 49.661 1.439 15.989 49.6613 .967 10.745 60.4074 .825 9.171 69.5785 .799 8.874 78.4526 .643 7.146 85.5987 .500 5.556 91.1558 .478 5.311 96.4659 .318 3.535 100.000Extraction Method: Principal Component Analysis.
Figure 4.3– Graph of eigenvalues of the extracted factors
The following table presents the rotated component matrix using 0.5 as
a cut-off point for factor loading for naming the factors. In this way five
factors are obtained. Factor 1 will comprise variables Transparency,
Diversification, Low Cost, Convenience, Reputation and Portfolio
104
Management. This factor is named as CORPORATE IMAGE. Factor 2
comprises of the variables Capital Appreciation, Return Potential and
Security/Safety. This factor is named as SAFETY ON INVESTMENT.
Rotated Component Matrix for Table 4.33 Factor Analysis
Component Communalities1 2Transparency .820 .447Diversification .716 .429Low Cost .709 .530Convenience .701 .509Reputation .654 .672Portfolio Mgt. .637 .251Capital Appreciation .770 .606Return Potential .713 .513Security/Safety .501 .512
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Figure 4.4 shows the component plot in a rotated space. It is also very
much visible from the figure that the variables were grouping as per the
rotated component matrix.
Figure 4.4 – Component Plot in rotated space
105
Two factors were extracted from the factor analysis, namely,
1. Corporate Image Transparency, Diversification, Low Cost,
Convenience, Reputation and Portfolio
Management
2. Safety on investment Capital Appreciation, Return Potential and
Security/Safety
4.4.5 Methods used by Investors for TSMF Analysis
Presence of risk in any investment is a normal feature. Investors’
behaviour in terms of making preliminary analysis on their investment
prevents them from huge loss. Data collected through survey revealed that
301 (75.25 percent) respondents made an analysis before making an
investment and 99 (24.75 percent) respondents have not made any analysis.
The secondary data analyses made in this study show that all the schemes
chosen by the respondents are performed well during the study period.
Moreover, the schemes chosen by respondents are existed in the market for
more than five years. The association between the methods used by the
respondents with respect to their Gender and Educational qualification have
been analysed here.
It is advisable to choose any investment scheme after proper
analysis. Table 4.34 shows that 49 percent of respondents have made own
analysis and 49 percent of respondents had consultation with an expert and 2
percent of respondents found other methods of analysis. The percent of
respondents are rounded to nearest digit. More over 53 percent of male
respondents and 40 percent of female respondents made own analysis, 47
percent male respondents and 56 female respondents consulted experts.
Further, hypothesis has been framed to test the association between the gender
106
and methods used to analyse the schemes and it has been tested by chi-square
test.
Null hypothesis (H0): There is no association between gender and
method used to analyse the schemes.
The test result shows that the chi square value is not significant at
5% level. Hence, Null hypothesis is accepted and alternate hypothesis is
rejected. From this analysis, it is concluded that there is no significant
association between gender and method used by the respondents to analyse
the schemes.
Table 4.34 Association between Gender on the Opinions about the
Methods used for TSMF Analysis
Method of AnalysisNumber of Respondents Percentage of respondentsMale Female Total Male Female Total
Own Analysis 116 32 148 53 40 49Consult with Expert 103 45 148 47 56 49Any other 1 4 5 0 5 2Total 220 81 301 100 100 100
Variable Chi-square Value df asymp. Sig. (2-sided)
Method of Analysis and Gender 6.771a 3 .080
Source: Primary Data
Table 4.35 shows that, among the group of PG qualified
respondents 48 percent made own analysis, 51 percent consulted an expert
and 2 percent adopted other methods for analysis. Among the group of UG /
Diploma qualified respondents 55 percent made own analysis, 43 percent
consulted an expert and 2 percent adopted other methods of analysis
107
Table 4.35 Methods Used by Respondents for TSMF Analysis and
Educational qualification
Kind of AnalysisNumber of Respondents Percentage of Respondents
SSLC HSC Diploma / UG
PGDegree
Total SSLC HSC Diploma/ UG
PGDegree
Total
Own Analysis 8 2 59 79 148 57 14 55 48 49Consulted Expert 6 12 46 84 148 43 86 43 51 49Any other 0 0 2 3 5 0 0 2 2 2Total 14 14 107 166 301 100 100 100 100 100Source : Primary Data
An analysis has been made to know the methods of analysis used
by the respondents in the selected sample cities. Table 4.36 presents the
methods used by the respondents in the selected sample cities. It is found that
69 percent of respondents were from Erode district made own analysis.
Respondents in Chennai region have not made an analysis before investment.
Table 4.36 Territory wise Methods Used by Respondents for
TSMF Analysis
DistrictNumber of Respondents Percentage of Respondents
Own Analysis
Consulted Expert
Any other Total Own
AnalysisConsulted
ExpertAny
other Total
Chennai 13 15 2 30 43 50 7 100Coimbatore 11 24 0 35 31 69 0 100Erode 24 10 1 35 69 29 3 100Madurai 21 22 0 43 49 51 0 100Salem 16 20 1 37 43 54 3 100Tirunelveli 21 17 1 39 54 44 3 100Tirupur 21 15 0 36 58 42 0 100Trichy 21 25 0 46 46 54 0 100Source : Primary Data
There are various documents used by investors for analyzing risk
and return of a particular scheme. Annual reports and brochure are popularly
and frequently used by most of the respondents. Table 4.37 shows the various
documents used by the respondents. Among the group of respondents, 17
108
percent have analysed Annual and Half yearly reports, 16 percent have used
Scheme offer document and Statement of accounts, 11.3 percent have used
Key Information Memorandum and 7.3 percent have used Portfolio
disclosures before investing into Tax Saving Mutual Fund scheme.
Table 4.37 Documents Used by Respondents for Own Analysis
(Multiple Response)Documents used in Own
analysisNumber of
RespondentsPercentage of Respondents
Scheme offer documents 64 16.0Key Information Memorandum 45 11.3Statement of Accounts 64 16.0Annual and half yearly reports 68 17.0Portfolio disclosures 29 7.3
Source : Primary Data
There are various techniques and methods available to analyse a
particular investment scheme. There are many other technical documents that
provide investors more information about the scheme. Scheme Information
Document (SID) is one of the technical documents which contain scheme
related information. Statement of Additional Information (SAI) contains legal
information about mutual fund schemes. Application for mutual fund scheme
is accompanied by Key Information Memorandum (KIM). From the data
collected through survey, it can be noted that 75.25 percent of respondents
made analysis before investment. Table 4.38 shows that among the group of
respondents, 49.3 percent have read and understood, 32 percent have read and
partially understood and 18.8 percent have not read and understood the
information given in the brochure.
Among the group of respondents, 39.5 percent have read and
understood, 38.3 percent have read and partially understood and 22.3 percent
have not read and understood the information given in the SID. Among the
109
group of respondents, 24 percent have read and understood, 47.8 percent have
read and partially understood and 28.3 percent have not read and understood
the information given in SAI.
Among the group of respondents, 26.3 percent have read and
understood, 40.3 percent have read and partially understood and 33.5 percent
have not read and understood about KIM. The understanding potential of
respondents has been graphically shown in Figure 4.5.
Table 4.38 Respondents’ Understanding Potential on Various Documents
(Multiple Choices)
Understanding of Documents
Number of Respondents Percentage of RespondentsRead and
UnderStood
Read and Partially
understood
Not Read and under
stood
Read and
Under stood
Read and Partially
understood
Not Read and under
stood
SID 158 153 89 39.5 38.3 22.3SAI 96 191 113 24 47.8 28.3KIM 105 161 134 26.3 40.3 33.5Brochure 197 128 75 49.3 32 18.8Source : Primary Data
(Multiple Choices)
Figure 4.5 Respondents’ Understanding Potential on Various Documents
Source : Primary Data
0
50
100
150
200
250
SID SAI KIM Brochure
Num
ber
of R
epon
dent
s
Varous documents of Mutual funds
Read and Under Stood
Read and Partially understood
Not Read and understood
110
4.4.6 Investors’ Perception on factors influencing Tax Saving Mutual
Fund Schemes
There are various factors such as Nature and Natural Disaster,
Management Affairs, Nature of Business, Financial Position of AMC,
Management Strategies, Security Market and Economy, Inflation, Political
Factors, Government Policies, Terrorism, Global Economy and Markets,
National and International events are identified as risk factors of mutual
funds. Every factor may influence the mutual fund market in varying degrees.
Perception on these factors may change the investment attitude of an
individual. Hence, an analysis has been made with respondents’ perception
towards these factors. Table 4.39 shows the perception of respondents on
TSMF risk factors by their gender.
The results of Independent sample test shows that there is no
significant difference between the means of risk factors such as Natural
Disaster, Management Affairs, Financial Position of AMC, Management
Strategies, Security Market and Economy, Inflation, Government Policies,
Terrorism, Global Economy and Markets, National and International events
and respondents’ gender at 5% level of significance. The perception on
Nature of Business and Political factors are significantly different for male
and female respondents. There is a relationship between respondents’
perception on nature of the business and political factor and their gender at
1% significant level. Female respondents were highly considering these risk
factors. The reverse mean value of these two factors is very low in female
respondents than male respondents.
111
Table 4.39 Mean Ranks of Respondents’ Perception on Risk Factors and Gender
Risk Factors Gender Mean Std. Deviation Std. Error
Nature and Natural Disaster Male 1.78 0.942 0.064Female 1.79 0.630 0.067
Management Affairs Male 1.84 0.886 0.060Female 1.73 0.579 0.061
Nature of Business Male 1.94 1.102 0.075Female 1.61 0.748 0.079
Financial Position of AMC Male 1.92 1.075 0.073Female 1.98 0.825 0.087
Management Strategies Male 2.10 1.014 0.069Female 2.12 1.136 0.120
Security Market and Economy Male 1.84 1.184 0.081Female 1.62 0.983 0.104
Inflation Male 1.75 1.013 0.069Female 1.62 0.715 0.076
Political Factor Male 2.13 1.053 0.072Female 1.67 0.735 0.078
Government Policies Male 1.96 1.219 0.083Female 1.73 0.836 0.089
Terrorism Male 2.40 1.216 0.083Female 2.37 1.171 0.124
Global Economy and Markets Male 1.94 1.230 0.084Female 2.12 1.232 0.131
National and International events Male 2.08 1.145 0.078Female 2.17 1.199 0.127
Independent samples test results for Table 4.39 Respondents’ Perception on Risk Factors and Gender
Risk Factors
Levene’s Test for Equality of
Variancet - test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. ErrorDifference
95% Confidence Interval of the
DifferenceLower Upper
Nature and Natural Disaster 7.218 .008 -.308 303 .970 -.004 .109 -.218 0.210Management Affairs 6.826 .009 1.102 303 .271 .112 .102 -.088 0.313Nature of Business 9.580 .002 2.648 303 .009 .338 .128 .087 0.589Financial Position of AMC 4.149 .043 -.479 303 .632 -.061 .127 -.311 0.189Management Strategies 2.935 .088 -.192 301 .848 -.025 .133 -.286 0.235Security Market and Economy 0.774 .380 1.547 303 .123 .220 .142 -.060 0.500
Inflation 1.888 .170 1.120 303 .264 .132 .118 -.100 0.364Political Factor 9.942 .002 3.722 303 .000 .455 .122 .215 0.696Government Policies 9.564 .002 1.646 303 .101 .233 .141 -.045 0.511Terrorism 0.008 .927 .181 303 .857 .027 .152 -.271 0.326Global Economy and Markets 1.046 .307 -1.156 303 .249 -.179 .155 -.484 0.126
National and International events 1.209 .272 -.615 303 .539 -.090 1.460 -.378 0.198
Source : Primary Data
112
Table 4.40 shows that there is significant difference between the
opinion of respondents on Nature and Natural Disaster, Management Affairs,
Nature of Business, Financial Position of AMC, Inflation and Marital Status.
The result of Independent sample test shows that the significant P value of
these factors are lesser than 0.05. The reverse mean values of all these factors
are low for married respondents. So, Married respondents have highly
considered these risk factors. The perception on Management Strategies,
Security Market and Economy, Political Factor, Government Policies,
Terrorism, Global Economy and Markets, National and International events
have been considered equally by both married and unmarried respondents.
Independent sample test result shows that the significant P value of all these
variables are greater than 0.05, which shows that there is no significant
difference between the mean value of these factors and marital status of the
respondents at 5% level. It can also be noted that the factors like security
market and economy, National and International events have been highly
considered by unmarried respondents. Other than these two factors, all other
factors have been highly considered by the married respondents. All the
married respondents have very much considered the factors associated with
their investment on TSMF.
113
Table 4.40 Mean Ranks of Respondents’ Perception on Risk Factors and
Marital Status
Risk FactorsMean Std. Deviation Std. Error
Married Unmarried Married Unmarried Married UnmarriedNature and Natural Disaster 1.67 2.16 0.783 0.985 0.052 0.112Management Affairs 1.73 2.05 0.796 0.804 0.053 0.091Nature of Business 1.75 2.13 0.966 1.132 0.064 0.128Financial Position of AMC 1.84 2.21 0.893 1.252 0.059 0.142Management Strategies 2.09 2.14 1.083 0.948 0.072 0.109Security Market and Economy 1.70 0.99 1.108 1.179 0.074 0.133Inflation 1.63 1.94 0.827 1.177 0.055 0.133Political Factor 1.94 2.17 0.989 0.986 0.066 0.112Government Policies 1.84 2.05 1.077 1.247 0.072 0.141Terrorism 2.32 2.06 1.211 1.155 0.080 0.131Global Economy and Markets 1.94 2.17 1.229 1.232 0.082 0.139National and International events 2.16 1.95 1.202 1.018 0.080 0.115
Independent sample test result for Table 4.40 Respondents’Perception
on Risk Factors and Marital Status
Risk Factors
Levene’s Test for Equality of Variance
t - test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Diffe-rence
Std. ErrorDiffe-rence
95% Confidence Interval of the
DifferenceLower Upper
Nature and Natural Disaster .585 .445 -4.205 303 .000 -.463 .110 -.680 -.246
Management Affairs 2.528 .113 -3.098 303 .002 -.324 .105 -.530 -.118Nature of Business 1.081 .299 -2.860 303 .005 -.379 .133 -.640 -.118Financial Position of AMC 10.652 .001 -2.780 303 .006 -.364 .131 -.621 -.106
Management Strategies 1.684 .195 -0.375 301 .708 -.052 .139 -.326 .222Security Market and Economy .297 .586 -1.939 303 .053 -.287 .148 -.578 .004
Inflation 9.668 .002 -2.474 303 .014 -.302 .122 -.541 -.062Political Factor 0.288 .592 -1.760 303 .079 -.228 .130 -.484 .027Government Policies 2.293 .131 -1.424 303 .155 -.21 .147 -.500 .080Terrorism .231 .631 -1.817 303 .070 -.285 .157 -.594 .024Global Economy and Markets .000 .986 -1.415 303 .158 -.228 .161 -.546 .089
National and International events 3.824 .051 1.381 303 .168 .21 .152 -.089 .509
Source : Primary Data
114
Table 4.41 presents the respondents’ perception on various factors
influencing the performance of TSMF and educational qualification. There is
a difference on consideration of Security Market and Economy, Political
factor and Terrorism among the group of respondents. 2-tailed significant P
value of all these factors is lesser than 0.05. So it is evident that there is a
significant difference between the considerations of all these factors among
the group of respondents with respect to their qualification. The respondents
who had their educational qualification up to SSLC have highly considered
these three factors. The factors like Nature and Natural Disaster, Management
Affairs, Nature of Business, Financial Position of AMC, Management
Strategies, Inflation and Government Policies have been considered equally
by all the respondents irrespective of their educational qualification.
115
Table 4.41 Mean Ranks of Respondents’ Perception on Risk factors and
Educational Qualification
Risk Factors Educational Qualification Mean Std.
DeviationStd.
Error
95% Confidence Interval for Mean
Lower Bound
Upper Bound
Nature and Natural Disaster
SSLC 1.580 1.240 0.358 0.80 2.37HSC 2.140 0.535 0.143 1.83 2.45Diploma/UG 1.740 0.705 0.066 1.61 1.87PG Degree 1.800 0.945 0.074 1.65 1.95
Management AffairsSSLC 1.830 1.193 0.345 1.08 2.59HSC 1.710 0.914 0.244 1.19 2.24Diploma/UG 1.710 0.648 0.061 1.59 1.83PG Degree 1.880 0.865 0.067 1.75 2.02
Nature of BusinessSSLC 2.080 1.240 0.358 1.30 2.87HSC 2.140 1.406 0.376 1.33 2.95Diploma/UG 1.860 0.840 0.079 1.70 2.02PG Degree 1.790 1.085 0.084 1.63 1.96
Financial Position of AMCSSLC 1.580 0.996 0.288 0.95 2.22HSC 1.930 1.269 0.339 1.20 2.66Diploma/UG 1.820 0.779 0.073 1.68 1.97PG Degree 2.040 1.115 0.087 1.87 2.21
Management StrategiesSSLC 1.670 1.231 0.355 0.88 2.45HSC 2.430 1.222 0.327 1.72 3.13Diploma/UG 2.040 0.943 0.089 1.87 2.22PG Degree 2.150 1.085 0.084 1.98 2.32
Security Market and Economy
SSLC 1.330 0.651 0.188 0.92 1.75HSC 2.210 1.578 0.422 1.30 3.13Diploma/UG 1.340 0.607 0.057 1.23 1.45PG Degree 2.070 1.284 0.100 1.87 2.26
Inflation
SSLC 1.920 1.311 0.379 1.08 2.75HSC 2.210 1.578 0.422 1.30 3.13Diploma/UG 1.580 0.650 0.061 1.46 1.70PG Degree 1.750 0.992 0.077 1.59 1.90
Political Factor
SSLC 1.330 0.651 0.188 0.92 1.75HSC 2.000 0.784 0.210 1.55 2.45Diploma/UG 1.860 1.012 0.095 1.67 2.05PG Degree 2.140 0.987 0.077 1.99 2.29
Government Policies
SSLC 1.420 0.669 0.193 0.99 1.84HSC 2.210 1.578 0.422 1.30 3.13Diploma/UG 1.730 0.962 0.090 1.55 1.91PG Degree 2.020 1.192 0.093 1.83 2.20
Terrorism
SSLC 1.250 0.622 0.179 0.86 1.64HSC 3.000 1.301 0.348 2.25 3.75Diploma/UG 2.190 1.021 0.096 2.00 2.38PG Degree 2.560 1.270 0.099 2.36 2.75
116
ANOVA for Table 4.41 Respondents’ Perception on Risk Factors and
Educational Qualification
Risk Factors df Mean Square F Sig.
Nature and Natural DisasterBetween Groups 3 .861 1.161 .325Within Groups 301 .741Total 304
Management AffairsBetween Groups 3 .729 1.115 .343Within Groups 301 .654Total 304
Nature of BusinessBetween Groups 3 .793 0.757 .519Within Groups 301 1.048Total 304
Financial Position of AMCBetween Groups 3 1.523 1.508 .213Within Groups 301 1.010Total 304
Management StrategiesBetween Groups 3 1.512 1.378 .250Within Groups 301 1.097Total 304
Security Market and Economy
Between Groups 3 13.481 11.628 .000Within Groups 301 1.159Total 304
InflationBetween Groups 3 2.079 2.404 .068Within Groups 301 .865Total 304
Political FactorBetween Groups 3 3.594 3.753 .011Within Groups 301 .958Total 304
Government PoliciesBetween Groups 3 3.284 2.638 .050Within Groups 301 1.245Total 304
TerrorismBetween Groups 3 9.954 7.331 .000Within Groups 301 1.358Total 304
Source : Primary Data
Table 4.42 presents the respondents’ perception on various factors
influencing the performance of TSMF and Annual income. The result of
ANOVA shows that the significant P value of the factors like Inflation,
Political factor and Terrorism is lesser than 0.05. So, there is a significant
difference between the considerations of all these factors with respect to the
respondents’ Annual Income. The respondents with the annual income of
above Rs. 4 lakhs have highly considered Inflation and Terrorism.
Respondents with the annual income of less than Rs. 2 lakhs have highly
117
considered Nature and Natural disaster. The factors like Nature and Natural
Disaster, Management Affairs, Nature of Business, Financial Position of
AMC, Management Strategies, Security Market and Economy and
Government Policies have been considered equally by all the respondents
irrespective of their annual income.
Table 4.42 Mean Ranks of Respondents’ Perception on Risk Factors and
Annual IncomeRisk Factors Annual Income Mean Std. Deviation Std. Error
Nature and Natural Disaster
up to 2 Lakhs 1.28 0.687 0.0812-4 Lakhs 1.89 0.979 0.083Above 4 Lakhs 1.78 0.774 0.079
Management Affairs
up to 2 Lakhs 1.67 0.65 0.0772-4 Lakhs 1.86 0.83 0.071Above 4 Lakhs 1.84 0.879 0.09
Nature of Businessup to 2 Lakhs 1.93 1.191 0.142-4 Lakhs 1.83 1.043 0.089Above 4 Lakhs 1.8 0.846 0.087
Financial Position of AMC
up to 2 Lakhs 2 1.126 0.1332-4 Lakhs 2.03 1.08 0.092Above 4 Lakhs 1.75 0.757 0.078
Management Strategies
up to 2 Lakhs 2.1 0.919 0.112-4 Lakhs 2.2 1.122 0.095Above 4 Lakhs 1.97 1.026 0.105
Security Market and Economy
up to 2 Lakhs 1.87 1.016 0.122-4 Lakhs 1.58 1.35 0.115Above 4 Lakhs 1.77 0.807 0.083
Inflationup to 2 Lakhs 1.56 0.785 0.0932-4 Lakhs 1.94 1.093 0.093Above 4 Lakhs 1.49 0.698 0.072
Political Factorup to 2 Lakhs 1.74 0.822 0.0972-4 Lakhs 2.15 1.087 0.093Above 4 Lakhs 1.97 0.928 0.095
Government Policies
up to 2 Lakhs 1.81 1.002 0.1182-4 Lakhs 2.02 1.287 0.11Above 4 Lakhs 1.78 0.936 0.096
Terrorismup to 2 Lakhs 2.31 1.194 0.1412-4 Lakhs 2.65 1.206 0.103Above 4 Lakhs 2.07 1.123 0.115
118
ANOVA for Table 4.42 Respondents’ Perception on Risk Factors and
Annual IncomeRisk Factors df Mean Square F Sig.
Nature and Natural Disaster
Between Groups 2 2.245 3.065 .048Within Groups 302 0.733Total 304
Management Affairs
Between Groups 2 0.977 1.498 .225Within Groups 302 0.651Total 304
Nature of Business
Between Groups 3 0.369 0.351 .704Within Groups 302 1.05Total 304
Financial Position of AMC
Between Groups 2 2.434 2.419 .091Within Groups 302 1.006Total 304
Management Strategies
Between Groups 2 1.548 1.409 .246Within Groups 300 1.098Total 302
Security Market and Economy
Between Groups 2 2.63 2.068 .128Within Groups 302 1.272Total 302
InflationBetween Groups 2 6.774 8.084 .000Within Groups 302 0.838Total 304
Political FactorBetween Groups 2 4.15 4.312 .014Within Groups 302 0.963Total 304
Government Policies
Between Groups 2 2.036 1.616 .200Within Groups 302 1.26Total 304
TerrorismBetween Groups 2 9.752 7.028 .001Within Groups 302 1.388Total 304
Source : Primary Data
4.4.7 Investors’ Awareness on SEBI
Awareness is the state or ability to perceive, to feel or to be
conscious of events, objects or sensory patterns. It makes people to
understand and involve in relative action. SEBI is the authorized apex
institution to regulate and protect the investors involved in mutual funds,
securities and security related markets. The measures taken by SEBI, protects
the investors from various kinds of risks such as fraudulent and
misrepresentation of investment related information, unauthorized dealers,
over cost, unethical and unprofessional management and scams. Every
119
investor must know about SEBI and its rules and regulations which saves
them from a loss. Thus, the awareness of respondents have been analysed in
the present study. From the collected data, the awareness of respondents’ on
SEBI has been analysed. 76 percent of sample respondents were aware of
SEBI and 24 percent of sample respondents were not aware of SEBI.
Table 4.43 shows that among the group of respondents, 77 percent
were in the age group of 26-35 years and 86 percent were in the group of
above 50 years were aware of SEBI. Further, hypothesis has been framed to
test the association between age and awareness on SEBI and it has been tested
by chi-square test.
Null hypothesis (H0): There is no association between age and
awareness on SEBI.
The test result shows that the chi square value is not significant at
5% level. Hence, null hypothesis is accepted and alternate hypothesis is
rejected. From this analysis, it is concluded that there is no significant
association between age and awareness on SEBI.
Table 4.43 Association between Age Groups on the Opinions about the
Awareness on SEBI
Age group of respondents
Number of Respondents Percentage of RespondentsYes No Total Yes No Total
Up to 25 37 21 58 64 36 10026-35 148 44 192 77 23 10036-45 60 19 79 76 24 10046-55 40 9 49 82 18 10050 and Above 19 3 22 86 14 100
Variable Chi-square Value df asymp. Sig. (2-sided)
Age and Awareness on SEBI 14.779 8 .064Source : Primary Data
120
Table 4.44 present, 75 percent of male, 77 percent of female
respondents were aware of SEBI. Among the group of respondents, 25
percent male and 23 percent female were not aware of SEBI. Further,
hypothesis has been framed to test the association between gender and
awareness on SEBI and it has been tested by chi-square test.
Null hypothesis (H0): There is no association between gender and
awareness on SEBI.
The test result shows that the chi square value is not significant at
5%. Hence, null hypothesis is accepted and alternate hypothesis is rejected.
From the analysis, it is concluded that there is no significant association
between gender and awareness on SEBI.
Table 4.44 Association between Gender on the Opinions about the
Awareness on SEBI
Gender Number of Respondents Percentage of respondentsYes No Total Yes No Total
Male 218 71 289 75 25 100Female 86 25 111 77 23 100Total 305 95 400 76 24 100
Variable Chi-square Value df asymp. Sig. (2-sided)
Gender and Awareness on SEBI 2.941 2 .230
Source : Primary Data
Table 4.45 shows that 74 percent of salaried respondents, 78
percent of respondents doing business and 89 percent of respondents engaged
in some other job were aware of SEBI. 26 percent of salaried respondents, 22
percent of respondents doing business and 11 percent of respondents engaged
in some other jobs were not aware of SEBI. Further, hypothesis has been
121
framed to test the association between profession and awareness on SEBI and
it has been tested by chi-square test.
Null hypothesis (H0): There is no association between profession and
awareness on SEBI.
The test result shows that the chi square value is not significant at
5%. Hence, null hypothesis is accepted and alternate hypothesis is rejected.
From the analysis, it is concluded that there is no significant association
between profession and awareness on SEBI.
Table 4.45 Association between Profession on the Opinions about the
Awareness on SEBI
ProfessionAwareness on SEBI
Number of Respondents Percentage of respondentsYes No Total Yes No Total
Salaried 210 74 284 74 26 100Business 62 17 79 78 22 100Others 33 4 37 89 11 100Total 305 95 400 76 24 100
Variable Chi-Square Value df asymp. Sig. (2-sided)
Profession and Awareness on SEBI 5.012 6 .542
Source: Primary Data
Table 4.46 shows that 79 percent of married and 69 percent of
unmarried respondents were aware of SEBI. 21 percent of married and 31
percent of unmarried respondents were not aware of SEBI. Further,
hypothesis has been framed to test the association between the marital status
of the respondents and awareness on SEBI and it has been tested by chi-
square test.
122
Null hypothesis (H0): There is no association between marital status
and awareness on SEBI.
The test result shows that the chi square value is not significant at
5%. Hence, null hypothesis is accepted and alternate hypothesis is rejected.
From the analysis, it is concluded that there is no significant association
between marital status and awareness on SEBI.
Table 4.46 Association between Marital Status on the Opinions about the
Awareness on SEBI
MaritalStatus
Number of Respondents Percentage of respondentsYes No Total Yes No Total
Married 224 59 283 79 21 100Unmarried 81 36 117 69 31 100Total 305 95 400 76 24 100
Variable Chi-Square Value df asymp. Sig. (2-sided)
Marital Status and Awareness on SEBI 4.841 2 .089
Source : Primary Data
Table 4.47 shows that those who have knowledge on risk factors
that affect the performance of Tax Saving Mutual Funds were aware of SEBI.
86 percent of respondents who have knowledge on risk factors were aware of
SEBI and 14 percent of respondents who have knowledge on risk factors were
unaware of SEBI. 48 percent of respondents who do not have knowledge on
risk factors were aware of SEBI and 52 percent of respondents who do not
have knowledge on risk factors were unaware of SEBI. Further, hypothesis
has been framed to test the association between knowledge on risk factors and
awareness on SEBI and it has been tested by chi-square test.
123
Null hypothesis (H0): There is no association between knowledge on
risk factors and awareness on SEBI.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From this analysis, it can be concluded that that there is a significant
association between knowledge on risk factors and awareness on SEBI.
Table 4.47 Association between Knowledge on Risk Factors and
Awareness on SEBI
Knowledge on Risk factors
Number of Respondents
Percentage of respondents
Yes No Total Yes No TotalKnow Risk factors 256 42 298 86 14 100Does not know risk factors 49 53 102 48 52 100Total 305 95 400 76 24 100
Variable Chi-Square Value df asymp. Sig.
(2-sided)Knowledge on Risk factors and Awareness on SEBI 60.305 2 .000
Source : Primary Data
Table 4.48 shows that 80.8 percent of the respondents were
interested to participate in the awareness campaign and 19.2 percent of
respondents did not show interest to participate in awareness campaign. By
attending awareness program respondents will know about the controlling
authority like SEBI and AMFI and also they can understand about various
risk factors, documents to be analysed and guidelines to be followed while
making an investment.
124
Table 4.48 Respondents’ Interest in Attending Awareness Program
Interested in Awareness Programs
Number of Respondents
Percentage of Respondents
Yes 323 80.8No 77 19.3Total 400 100.0Source : Primary Data
Table 4.49 exhibits that among the group of respondents, 59
percent have not attended any awareness program, 19.3 percent have attended
the awareness program one time, 14.5 percent have attended 2 to 3 times and
7.3 percent have attended more than 3 times. Even though SEBI and AMFI
have been organizing many awareness programs along with the AMCs, it has
not reached the entire investor population.
Table 4.49 Number of Awareness Programs Attended by Respondents
Number of Programs Attended
Number of Respondents
Percentage of Respondents
No program attended 236 59.0One time 77 19.32-3 times 58 14.5More than 3 29 7.3Total 400 100
Source : Primary Data
Table 4.50 shows that 56.3 percent of interested respondents have
not attended any program. Even though the respondents were interested they
have not attended any program organized by SEBI, AMFI and AMC. The
reason for not attending the program may be that there was no frequent
awareness program or the program would not have been organized in their
accessible place. Further, hypothesis has been framed to test the association
between respondents’ interest and number of programs attended by them and
it has been tested by chi-square test.
125
Null hypothesis (H0): There is no association between respondents’
interest and number programs attended by them.
The test result shows that the chi square value is not significant at
5%. Hence, null hypothesis is accepted and alternate hypothesis is rejected.
From this analysis, it can be concluded that there is no significant association
between respondents’ interest and participation in awareness programs.
Table 4.50 Association between Respondents’ Interest on the opinions
about the Participation in Awareness Program
Interest in participating
awareness program
Number of Respondents Percentage of RespondentsNot
attended any
Program
1 2-3 >3 Total
Notattended
any Program
1 2-3 >3 Total
Yes 182 64 51 26 323 56.3 19.8 15.8 8.0 80.8No 54 13 7 3 77 70.1 16.9 9.1 3.9 19.3
Total 236 77 58 29 400 59.0 19.3 14.5 7.3 100.0
Variable Chi-Square Value df asymp. Sig.
(2-sided)Interest in awareness program and Number of programs attended 5.683 3 .128
Source : Primary Data
SEBI has been increasing the number of awareness programs to
make all the investors to know details about their investment, to understand
the guidelines and protection measures taken by SEBI. Every investor must
make use of the opportunities provided by SEBI and must be aware of all
their investment related information.
4.4.8 Investors’ Monitoring Method
Information Technology makes communication faster and has
shrunk the globe so small. Information can be shared, communication can be
126
passed within a very short span of time from one part of the world to other.
Technological development makes easier and speedy communication.
Irrespective of speed, people consider other factors to believe or accept the
message. They accept the information which is given by authorized media.
From the collected data, the popularly used communication mode used by the
TSMF investors has been analysed. Respondents may prefer or refer more
than one media, so multiple choices were given by the respondents.
Table 4.51 exhibits that among the group of respondents, 57
percent were using Television channels, 44.3 percent were getting
information from newspapers, 31.8 percent were using mutual fund company
websites, 16 percent were using financial magazines, 4.8 percent were using
publications from the respective investment company and 8 percent were using
other communication medium to update the market and to know the
performance of their investment avenue. Figure 4.6 also shows the various
communication media used by the respondents.
Table 4.51 Respondents’ Monitoring Method
(Multiple Response)
Monitoring Method Number of Respondents
Percentage of Respondents
Newspapers 177 44.3Television channels 228 57.0Mutual Fund company website 127 31.8Financial Magazines 64 16.0Publications of mutual fund companies 19 4.8Other modes 32 8.0Source : Primary Data
127
(Multiple Response)
Figure 4.6 Respondents’ Monitoring Method
Source : Primary Data
Table 4.52 exhibits that among the group of Post Graduate
respondents, 20 percent were using Newspapers, 32.25 percent were using
Television channels, 16.5 percent were using Mutual Fund company websites,
9 percent were using Financial magazines, 4 percent were using Publications
of mutual fund companies and 3.75 percent of respondents were using other
mode of communication to update the mutual fund market. SSLC and HSC
qualified respondents were not using company publications and other mode of
communications and they preferred Newspapers, Television channels, Mutual
Fund company websites and Financial magazines.
Table 4.53 exhibits that among the group of salaried respondents,
28.25 percent were using Newspapers, 39.25 percent were using Television
channels, 20 percent were using Mutual Fund company websites, 9 percent
were using Financial magazines, 4 percent were using Publications of mutual
fund companies and 5.5 percent were using other modes of communication to
update the mutual fund market.
177
228
127
64
19 32 Newspapers
Television channels
Mutual Fund company website
Financial Magazines
Publications of Mutual fund companies
Other modes
128
Table 4.54 exhibits that among the group of respondents whose
Annual income is up to 2 lakhs, 12.25 percent were using Newspapers, 17.25
percent were using Television channels, 6.5 percent were using Mutual Fund
company websites, 4.25 percent were using Financial magazines, 1.25 percent
were using Publications of mutual fund companies and 2 percent were using
other modes of communication to update the mutual fund market.
Table 4.52 Respondents’ Monitoring Method by Educational Qualification(Multiple Response)
Educational Qualification
Number of Respondents Percentage of Respondents
Newspapers
Television channels
Mutual fund company website
Financial Magazines
Publications of mutual
fund companies
Other modes
Newspapers
Television channels
Mutual fund company website
Financial Magazines
Publications of mutual
fund companies
Other modes
SSLC 12 13 8 6 - - 3 3.25 2 1.5 0 0HSC 6 5 14 2 - - 1.5 1.25 3.5 0.5 0 0Diploma/UG 79 81 39 20 3 17 19.75 20.25 9.75 5 0.75 4.25PG Degree 80 129 66 36 16 15 20 32.25 16.5 9 4 3.75Total 177 228 127 64 19 32 44.25 57 31.75 16 4.75 8Source : Primary Data
Table 4.53 Respondents’ Monitoring Method by Profession(Multiple Response)
Profession
Number of Respondents Percentage of Respondents
NewsPapers
Television channels
Mutual fund company website
Financial Magazines
Publications of mutual
fund companies
Other modes
NewsPapers
Television channels
Mutual fund
company website
Financial Magazines
Publications of mutual
fund companies
Other modes
Salaried 113 158 80 36 16 22 28.25 39.5 20 9 4 5.5Business 40 53 34 20 2 1 10 13.25 8.5 5 0.5 0.25Others 24 17 13 8 1 9 6 4.25 3.25 2 0.25 2.25Total 177 228 127 64 19 32 44.25 57 31.75 16 4.75 8Source : Primary Data
Table 4.54 Respondents’ Monitoring Method by Annual income(Multiple Response)
Annual Income
Number of Respondents Percentage of Respondents
Newspapers Television channels
Mutual fund
company website
Financial Magazines
Publications of mutual
fund companies
Other modes
Newspapers
Television channels
Mutual fund company website
Financial Magazines
Publications of mutual
fund companies
Other modes
up to 2 Lakhs 49 69 26 17 5 8 12.25 17.25 6.5 4.25 1.25 22-4 Lakhs 49 82 60 13 5 20 12.25 20.5 15 3.25 1.25 5Above 4 Lakhs 79 77 41 34 9 4 19.75 19.25 10.25 8.5 2.25 1Total 177 228 127 64 19 32 44.25 57 31.75 16 4.75 8Source : Primary Data
130
4.4.9 Investors’ opinion on Risk and Return of Tax Saving Mutual
Fund Schemes
Risk and return on market related investments is not constant and it
will be varying time to time. As such, an analysis has been made in this study
to know the respondents’ opinion on their risk and return on TSMF
investment. Table 4.55 shows that 44.8 percent of respondents have gained
moderate return, 31.5 percent have gained substantial return, 20.3 percent
have gained nothing and only 3.5 percent of respondents lost their capital by
investing into TSMF. Respondents’ opinion on their return on Tax Saving
Mutual Fund Schemes has been depicted in Figure 4.7.
Table 4.55 Respondents’ Opinion on Tax Saving Mutual Fund Scheme
Return
Opinion on Return Number of Respondents
Percentage of Respondents
Gained substantial return 126 31.5Gained moderate return 179 44.8Not gained anything 81 20.3Lost the capital 14 3.5Total 400 100.0
Source : Primary Data
Figure 4.7 Respondents’ Opinion on Tax Saving Mutual Fund Schemes
Return
Source : Primary Data
31.5
44.8
20.3
3.5 Gained substantial return
Gained moderate return
Not gained anything
Lost the capital
131
Table 4.56 shows that, among the group of respondents who gained
substantial return, 25 percent have invested for less than one year, 48 percent
have invested for the past 1 to 4 years, 10 percent have invested for the past 4
to 7 years and 17 percent have invested for more than 7 years. Among the
group of respondents who lost their capital, 14 percent have invested for less
than one year, 71 percent have invested for the past 1 to 4 years and 14
percent have invested for more than 7 years. Further, hypothesis has been
framed to test the association between the number of years invested in TSMF
and their opinion on TSMF and it has been tested by chi-square test.
Null hypothesis (H0) : There is no association between the number of
years investing in TSMF and their opinion on
TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is accepted and alternate hypothesis is rejected.
From the analysis, it is concluded that there is a significant association
between the number of years investing in Tax Saving Mutual Fund Schemes
and their opinion on TSMF.
132
Table 4.56 Association between Number of Years Investing in TSMF on the opinions on TSMF
Number of years investing in TSMF
Number of respondents Percentage of respondentsGained
substantial return
Gained moderate
return
Not gained
anything
Lost the
capitalTotal
Gained substantial
return
Gained moderate
return
Not gained
anything
Lost the
capitalTotal
Less than 1 year 32 84 25 2 143 25 47 31 14 361 to 4 years 60 63 25 10 158 48 35 31 71 404 to 7 years 13 22 16 0 51 10 12 20 0 13More than 7 years 21 10 15 2 48 17 6 19 14 12
Total 126 179 81 14 400 100 100 100 100 100
Variable Chi-Square Value df asymp. Sig. (2-sided)
Opinion on TSMF Return and Number of years investing in TSMF 37.330 9 .000
Source : Primary Data
133
Table 4.57 shows that 80 percent of the respondents know that
mutual fund NAV depends on market condition and 70 percent respondents
know that the past performance does not guarantee future return.
Table 4.57 Knowledge on Information about Mutual Fund Risk
Knowledge on information about mutual fund risk
Number of Respondents
Percentage of Respondents
Know Don't know Total Know Don't
know Total
NAV depends on market condition 320 80 400 80 20 100Past performance does not guarantee future 279 121 400 70 30 100
Source : Primary Data
Table 4.58 shows that among the group of respondents who know
that mutual funds are risky, 32 percent have gained substantial return, 44
percent have gained moderate return, 21 percent have not gained anything and
4 percent have lost their capital by investing into Tax Saving Mutual Fund
Schemes.
Further, hypothesis has been framed to test the association between
knowledge on Mutual Fund risk factors and their opinion on return of TSMF
and it has been tested by chi square test.
Null hypothesis (H0): There is no association between knowledge on
Mutual Fund risks and opinion on return of
TSMF.
The test result shows that the chi square value is not significant 5%.
Hence, null hypothesis is accepted and alternate hypothesis is rejected. From
the analysis, it is concluded that there is no significant association between
knowledge on mutual funds risks and their opinion on return of Tax Saving
Mutual Fund Schemes.
134
Table 4.58 Association between Knowledge on Mutual Fund Risks on the
opinions about the Return on TSMF
Risk in Mutual Fund
Number of Respondents Percentage of RespondentsGained
substantial return
Gained moderate
return
Not gained
anything
Lost the
capitalTotal
Gained substantial
return
Gained moderate
return
Not gained
anything
Lost the
capitalTotal
Know 115 157 74 13 359 32 44 21 4 100Don't know 11 22 7 1 41 27 54 17 2 100Total 126 179 81 14 400 32 45 20 4 100
Variable Chi-Square Value df asymp. Sig. (2-
sided)Knowledge on Mutual Fund risks and
opinion on TSMF return 1.501a 3 .682
Source : Primary Data
Table 4.59 shows the risk managing mechanism known by the
respondents. 78 percent stated that they know about Systematic Investment
Plan, 64.8 percent knew about the switch over facility, 49.5 percent knew
about partial withdrawal, 29.3 percent knew about systematic withdrawal and
18.5 percent knew about systematic transfer facilities available in the mutual
funds to balance risk and return of TSMF. Respondents’ risk managing
mechanism is depicted in Figure 4.8.
Table 4.59 Respondents’ Risk Managing Mechanism
(Multiple Response)
Risk managing mechanism Number of Investor Percentage of Investor
Switchover 259 64.8Systematic Investment 312 78.0Partial Withdrawal 198 49.5Systematic Withdrawal 117 29.3Systematic Transfer 74 18.5
Source : Primary Data
135
(Values in Percentage)
Figure 4.8 Respondents’ Risk Managing Mechanism
Source : Primary Data
4.4.10 Investors’ Grievances on Tax Saving Mutual Fund Schemes
Investors may have various grievances with the AMCs and
intermediaries. SEBI and AMFI have separate teams to redress the investors’
grievances. Every AMC is involved in solving the investors’ grievances.
Thus, an analysis has been made to study the grievances of mutual fund
investors. From the sample population, it is noted that 21.3 percent of
respondents have no grievances on their investment in TSMF.
From Table 4.60, it can be noted that 44.3 percent of respondents
have grievances like Delay in refund, Lower Dividend, Delay in switchover,
Delay or Nonpayment of Dividend, Non-receipt of Certificates but they have
not approached any authorities. Among the group of respondents who have
grievances on their investment on TSMF, 29.8 percent were approaching the
authorities for the past one year, 11.5 percent were approaching the
authorities for the past 2-3 years and 7.8 percent were approaching for more
than 3 years.
64.8
78
49.5
29.3
18.5
Switchover
Systematic Investment
Partial Withdrawal
Systematic Withdrawal
Systematic Transfer
136
Table 4.60 Respondents’ Grievances on TSMF
(Multiple responses)
Types of grievancesNo. of times approached
Percentage of respondents approached
0 1 2-3 >3 0 1 2-3 >3Delay in refund 54 24 12 17 13.5 6.0 3.0 4.3Lower Dividend 73 45 17 - 18.3 11.3 4.3 0.0Delay in switchover 18 15 11 11 4.5 3.8 2.8 2.8Delay/Nonpayment of Dividend 14 11 2 - 3.5 2.8 0.5 0.0
Non-receipt of Certificates 18 24 4 3 4.5 6.0 1.0 0.8Total 177 119 46 31 44.3 29.8 11.5 7.8
Source: Primary Data
4.4.11 Factors affecting TSMF Investment
Investment in any source depends on many factors such as annual
income, expenses, number of family members, personal commitment, interest
in investment planning, execution and satisfaction with the existing services
on investment. From the collected data, Regression was carried out to see the
impact of variables like annual income, number of years with TSMF and
satisfaction level on investment in TSMF. From Table 4.61, it can be noted
that the model very much fits in, to explain the relationship between these
variables.
From the regression relationship analysis amount of investment is
varying according to the number of years with TSMF, Annual income and
satisfaction. The model suggested that the amount of investment =1.32 + 0.28
(Number of years with TSMF) + 0.24 (Annual Income) – 0.23 (Satisfaction).
All these variables have an association with the investment of TSMF at 1%
significant level. The model explains about 17% of total variation in
137
investment of TSMF and the variation is accounted by the variables such as
Income, duration with TSMF and satisfaction.
The relationship between these variables is shown in Figure 4.9.
Each of the determinant variables is significant and number of years investing
in TSMF has high impact on investment followed by income and satisfaction.
The model suggests that 1 unit increase in number years of association with
TSMF causes an increase of 0.280 units in investment, keeping other
variables constant. 1 unit increase in income causes an increase of 0.240 units
in investment, keeping other variables constant and 1 unit increase in
satisfaction causes an increase of 0.232 units in investment, keeping other
variables constant.
Table 4.61 Regression Analysis on Relationship between Investment and
Personal Factors
Model Variables Entered VariablesRemoved Method
1 Number of years investing in TSMF .
Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
2 Annual Income .Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
3 Satisfaction with TSMF .
Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).
a Dependent Variable: Amount of Investment in TSMF
138
Model Summary for Table 4.61 Regression Analysis on Relationship
Between Investment and Personal Factors
Model R RSquare
Adjusted R
Square
Std. Error of the
Estimate
Change StatisticsR
Square Change
FChange df1 df2 Sig. F
Change
1 .306(a) .094 .092 .923 .094 38.569 1 372 .0002 .377(b) .142 .138 .900 .048 20.895 1 371 .0003 .415(c) .173 .166 .885 .030 13.545 1 370 .000
a Predictors: (Constant), Number of years investing in TSMF
b Predictors: (Constant), Number of years investing in TSMF, Annual
Income
c Predictors: (Constant), Number of years investing in TSMF, Annual
Income, Satisfaction with overall benefits
ANOVA for Table 4.61 Regression Analysis on Relationship between
Investment and Personal Factors
Model Sum of Squares df Mean Square F Sig.
1Regression 32.883 1 32.883 38.569 .000(a)Residual 317.162 372 .853Total 350.045 373
2Regression 49.793 2 24.897 30.763 .000(b)Residual 300.252 371 .809Total 350.045 373
3Regression 60.397 3 20.132 25.717 .000(c)Residual 289.649 370 .783Total 350.045 373
a Predictors: (Constant), Number of years investing in TSMF
b Predictors: (Constant), Number of years investing in TSMF, Annual
Income
c Predictors: (Constant), Number of years investing in TSMF, Annual
Income, Satisfaction with overall benefits
d Dependent Variable: Amount of Investment in TSMF
139
Coefficients for Table 4.61 Regression Analysis on Relationship between
Investment and Personal Factors
ModelUnstandardized
CoefficientsStandardized Coefficients t Sig.
B Std.Error Beta1 (Constant)
Number of years investing inTSMF
1.261.304
.108
.049 .306 11.6506.210
.000
.000
(Constant) .727 .157 4.619 .000Number of years investing in TSMF .308 .048 .311 6.467 .000
Annual Income .280 .061 .220 4.571 .000
3(Constant)
Number of years investing inTSMFAnnual IncomeSatisfaction
1.320 .224 5.907 .000.280 .048 .282 5.885 .000
.240 .061 .189 3.930 .000-.232 .063 -.179 -3.680 .000
a Dependent Variable: Amount of Investment in TSMF
Figure 4.9 Relationship between Respondents’ Investment and Number
of Years Investing in TSMF, Annual Income and
Satisfaction
Number of yearsinvesting in TSMF
0.280
Investment Amount
1.32
Annual Income
0.240
Satisfaction
-0.232
140
4.4.12 Investors’ Satisfaction on Tax Saving Mutual Fund Schemes
Satisfying all investors in all aspects is very difficult because the
expectations of investors vary from one to another. Table 4.62 presents
respondents’ satisfaction on overall benefits received on TSMF. Among the
group of respondents, 29 percent were highly satisfied, 48.3 percent were
satisfied, 21 percent were neither satisfied nor dissatisfied, 1.5 percent was
dissatisfied and 0.3 percent was highly dissatisfied by benefits on their TSMF
investment. Figure 4.10 graphically represents the respondents’ satisfaction
on their investment.
Table 4.62 Respondents’ Satisfaction on TSMF
Satisfaction Number of Respondents
Percentage of Respondents
Highly Satisfied 116 29.0Satisfied 193 48.3Neutral 84 21,0Dissatisfied 6 1.5Highly Dissatisfied 1 0.3Total 400 100
Source : Primary Data
(Values are in Number)
Figure 4.10 Respondents’ Satisfaction on TSMF
Source: Primary Data
116
193
84
61
Highly Satisfied
Satisfied
Neutral
Dissatisfied
Highly Dissatisfied
141
Table 4.63 shows that among group of respondents, falling in the
age group of less than 25 years, 40 percent were highly satisfied, 40 percent
were satisfied, 21 percent were neither satisfied nor dissatisfied and no one is
dissatisfied with the overall benefits of Tax Saving Mutual Fund Schemes.
The respondents falling in the age group of 46-55 years, 35 percent were
highly satisfied, 45 percent were satisfied, 20 percent were neither satisfied
nor dissatisfied and no one is dissatisfied and highly dissatisfied by the overall
benefits of Tax Saving Mutual Fund Schemes. The percentage values in the
table are rounded to the nearest digit. Further, hypothesis has been framed to
test the association between respondents’ interest and number of programs
attended by them and it has been tested by chi-square test.
Null hypothesis (H0): There is no association between different age
group of respondents and satisfaction on TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between respondents’ age and satisfaction on TSMF.
Table 4.64 shows that out of 289 male respondents, 96 were highly
satisfied, 143 were satisfied, 48 were neither satisfied nor dissatisfied, 2 were
dissatisfied and no one were highly dissatisfied with the overall benefits from
the investments of Tax Saving Mutual Fund Schemes. The percentage values
in table are rounded to the nearest digit. Further, hypothesis has been framed
to test the association between gender and satisfaction on TSMF and it has
been tested with chi square test.
142
Null hypothesis (H0): There is no association between gender and
satisfaction on TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between gender and satisfaction on TSMF.
Table 4.63 Association between Age Groups on the opinions about the Satisfaction on TSMF
Number of Respondents Percentage of RespondentsAge group of respondents
Highly Satisfied Satisfied Neutral Dissatisfied Highly
Dissatisfied Total Highly Satisfied Satisfied Neutral Dissatisfied Highly
Dissatisfied Total
Up to 25 23 23 12 0 0 58 40 40 21 0 0 10026-35 38 107 44 3 0 192 20 56 23 2 0 10036-45 27 31 18 3 0 79 34 39 23 4 0 10046-55 17 22 10 0 0 49 35 45 20 0 0 10050 and Above 11 10 0 0 1 22 50 46 0 0 5 100Total 116 193 84 6 1 400 29 48 21 2 0 100
Variable Chi-Square Value df asymp. Sig. (2-sided)Respondents’ satisfaction and Age 44.089 16 .000
Source: Primary Data
Table 4.64 Association between Gender on the opinions about the Satisfaction on TSMF
GenderNumber of Respondents Number of Respondents
Highly Satisfied Satisfied Neutral Dissatisfied Highly
Dissatisfied Total Highly Satisfied Satisfied Neutral Dissatisfied Highly
Dissatisfied Total
Male 96 143 48 2 0 289 33 50 17 1 0 100Female 20 50 36 4 1 111 18 45 32 4 1 100Total 116 193 84 6 1 400 29 48 21 2 0 100
Variable Chi-Square Value df asymp. Sig. (2-sided)Respondents satisfaction and Gender 23.414 4 .000
Source: Primary Data
144
Table 4.65 exhibits that among the group of respondents who
invested in TSMF for less than one year, 22 percent were highly satisfied, 46
percent were satisfied, 30 percent were neither satisfied nor dissatisfied, 2
percent were dissatisfied and no one is highly dissatisfied by the overall
benefits of Tax Saving Mutual Fund Schemes. Further, hypothesis has been
framed to test the association between the number of years investing in TSMF
and their satisfaction on TSMF and it has been tested by chi-square test.
Null hypothesis (H0): There is no association between number of years
investing in TSMF and satisfaction on TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between number of years investing in TSMF and their satisfaction on TSMF.
Table 4.66 shows that among the group of respondents who have
invested less than Rs. 50,000, 20 percent were highly satisfied, 47 percent
were satisfied, 31 percent were neither satisfied nor dissatisfied, 2 percent
were dissatisfied and no one is highly dissatisfied by overall benefits of Tax
Saving Mutual Fund Schemes. Among the group of respondents who invested
from Rs. 2 lakhs to Rs. 2.5 lakhs, 100 percent were highly satisfied. Further,
hypothesis has been framed to test the association between respondents’
investment in TSMF and their satisfaction on TSMF and it has been tested by
chi-square test.
Null hypothesis (H0) : There is no association between the amount invested in
TSMF and satisfaction on TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From the analysis, it is concluded that there is a significant association
between respondents’ investment amount in TSMF and their satisfaction.
Table 4.65 Association between Number of Years investing in TSMF on the opinions about the Satisfaction on TSMFNumber of years associated with
TSMF
Number of respondents Percentage of respondentsHighly
Satisfied Satisfied Neutral Dissatisfied Highly Dissatisfied Total Highly
Satisfied Satisfied Neutral Dissatisfied Highly Dissatisfied Total
Less than 1 year 31 66 43 3 0 143 22 46 30 2 0 1002 to 4 years 60 72 25 0 1 158 38 46 16 0 1 1005 to 7 years 6 30 12 3 0 51 12 59 24 6 0 100More than 7 years 19 25 4 0 0 48 40 52 8 0 0 100Total 116 193 84 6 1 400 29 48 21 2 0 100
Variable Chi-Square Value df asymp. Sig. (2-sided)Respondents satisfaction and number of years number of years investing in TSMF 38.736 12 .000
Source : Primary Data
Table4.66 Association between Amount Invested in TSMF on the opinions about the Satisfaction on TSMF
Investment in TSMFNumber of Respondents
TotalPercentage of Respondents
TotalHighly Satisfied Satisfied Neutral Dissatisfied Highly
DissatisfiedHighly
Satisfied Satisfied Neutral Dissatisfied Highly Dissatisfied
Up to 0.5 Lakhs 34 80 54 4 0 172 20 47 31 2 0 1000.5 to 1.0 Lakhs 24 63 24 2 0 113 21 56 21 2 0 1001.0 to 1.5 Lakhs 26 30 1 0 0 57 46 53 2 0 0 1001.5 to 2.0 Lakhs 12 18 1 0 1 32 38 56 3 0 3 1002.0 to 2.5 Lakhs 6 0 0 0 0 6 100 0 0 0 0 100Above 2.5 Lakhs 14 2 4 0 0 20 70 10 20 0 0 100Total 116 193 84 6 1 400 29 48 21 2 0 100
Variable Chi-Square Value df asymp. Sig. (2-sided)Respondents satisfaction and amount Invested in TSMF 85.792 20 .000
Source : Primary Data
146
Table 4.67 shows that among the group of respondents, who have
qualified with SSLC, 40 percent were highly satisfied, 50 percent were
satisfied, 10 percent were neither satisfied nor dissatisfied and no one is
dissatisfied by overall benefits of tax saving mutual funds. Further, hypothesis
has been framed to test the association between respondents’ educational
qualification and their satisfaction on TSMF and it has been tested by chi-
square test.
Null hypothesis (H0): There is no association between educational
qualification and satisfaction on TSMF.
The test result shows that the chi square value is not significant at
5% level. Hence, null hypothesis is accepted and alternate hypothesis is
rejected. From this analysis, it can be concluded that there is no significant
association between respondents’ educational qualification and their
satisfaction on TSMF.
147
Table 4.67 Association between Educational Qualifications on the opinions about the Satisfaction on TSMF
Educational Qualification
Number of Respondents Percentage of Respondents
Highly Satisfied Satisfied Neutral
Dissatisfied
Highly Dissatisfied Total Highly
Satisfied Satisfied NeutralDis
SatisfiedHighly
Dissatisfied Total
SSLC 8 10 2 0 0 20 40.0 50.0 10.0 0.0 0.0 100HSC 5 9 10 0 0 24 20.8 37.5 41.7 0.0 0.0 100Diploma/UG 36 74 30 2 0 142 25.4 52.1 21.1 1.4 0.0 100PG Degree 67 100 42 4 1 214 31.3 46.7 19.6 1.9 0.5 100Total 116 193 84 6 1 400 29.0 48.3 21.0 1.5 0.3 100
Variable Chi-Square Value df asymp. Sig. (2-sided)
Respondents’ satisfaction and Educational qualification 11.519 12 .485Source : Primary Data
148
4.4.13 Investors’ Analysis on Tax Saving Mutual Fund Schemes and
Return
It is advisable to make an analysis before investment. The
relationship between respondents’ analysis on tax saving mutual funds and
return has been shown in Table 4.68. Among the group of respondents who
made analysis, 35 percent have gained substantial return, 47 percent have
gained moderate return, 16 percent have gained nothing and only 3 percent
have lost their capital by investing into Tax Saving Mutual Fund Schemes.
From the data collected, it is found that only 19 percent of
respondents made an analysis but they have not chosen right scheme to get
dividend on their investment. Even though, 49 percent of the respondents
have not made any analysis but they got dividend return on their investment.
Among the group of respondents, who did not make any analysis
before investment, 22 percent have gained substantial return, 39 percent have
gained moderate return, 33 percent have not gained anything and 7 percent
have lost their capital. The percentage values in the table are rounded to the
nearest digit. Further, hypothesis has been framed to test the association
between respondents’ analysis on TSMF and return on Tax Saving Mutual
Fund Schemes and it has been tested with chi square test.
Null hypothesis (H0): There is no association between analysis on
TSMF and on return on TSMF.
The test result shows that the chi square value is significant at 1%
level. Hence, null hypothesis is rejected and alternate hypothesis is accepted.
From this analysis, it can be concluded that there is a significant association
between respondents’ analysis and opinion on return of Tax Saving Mutual
Fund Schemes.
149
Table 4.68 Association between Analysis of TSMF on the opinions about the Return
Analysis Before
Investment
Number of Respondents Percentage of RespondentsGained
substantial return
Gained moderate return
Notgained
anything
Lost the capital Total
Gained substantial
return
Gained moderate
return
Notgained
anything
Lost the capital Total
Yes 106 143 50 8 307 35 47 16 3 100
No 20 36 31 6 93 22 39 33 7 100
Total 126 179 81 14 400 32 45 20 4 100
Variable Chi-Square Value df asymp. Sig. (2-sided)
Analysis before Investment and opinion on TSMF return 14.517a 3 .002Source : Primary Data
150
4.4.14 Discriminant Analysis
Discriminant Analysis is used to predict group membership. This
technique is used to classify individuals/objects into one of the alternative
groups on the basis of a set of predictor variables. As such in this study
discriminant analysis has been adopted to determine main predictors in
discriminating gain or loss and satisfaction level of investors.
4.4.14.1 Discriminant Analysis to determine Main Predictors in
Discriminating Gain or Loss
Discriminant analysis was done with the following objectives:
To find a linear combination of variables (age, gender, income, marital
status and factors considered before investment) that discriminate
between categories of dependent variable (gain or loss) in the best
possible manner.
To find out which independent variables (age, gender, income, marital
status and factors considered before investment) are relatively better in
discriminating between the groups (gain or loss).
To determine the statistical significance of the discriminant function
and whether any statistical difference exists among the groups in terms
of predictor variables.
To evaluate the accuracy of classification (the percentage of cases that
able to classify correctly).
Discriminant analysis was used to classify the objects into two
categories. The gain on investment in TSMF or loss on investment in TSMF
and to determine which factors are the main predictors in discriminating
between gain and loss. The individuals are actually classified as ‘gain’ if they
151
do not lose their capital (categories – ‘gained substantial / moderate return and
capital intact, and lost the capital).
Table 5.69 shows the group statistics which gives the means and
standard deviations for both the groups (gain and loss). From this table, a few
preliminary observations about the groups can be made, and it clearly shows
that the two groups are widely separated with respect to the factors Corporate
Image and Safety on investment. The mean of Corporate Image and Safety for
individuals incurred loss is 0.546 and 1.317 respectively, whereas for
individuals who have gained, the mean of Corporate Image and Safety are -
0.020 and -0.048 respectively.
Table 4.69 Discriminant Analysis Group Statistics on Investors’ Return
on TSMF
Level of efficiency Mean Std. DeviationValid N (list wise)
Unweighted WeightedLoss Marital Status 1.429 0.514 14 14
Annual Income 1.643 0.745 14 14Gender 1.143 0.363 14 14Corporate Image 0.546 0.849 14 14Safety on investment 1.317 1.669 14 14
Age 2.429 1.399 14 14
Gain Marital Status 1.288 0.453 386 386Annual Income 1.946 0.776 386 386Gender 1.282 0.451 386 386Corporate Image -0.020 1.000 386 386Safety on investment -0.048 0.936 386 386Age 2.464 1.044 386 386
Total Marital Status 1.293 0.455 400 400Annual Income 1.935 0.776 400 400Gender 1.278 0.448 400 400Corporate Image 0.000 1.000 400 400Safety on investment 0.000 1.000 400 400Age 2.463 1.057 400 400
152
Table 4.70 shows test of equality of group means. F statistic
determines the variable that should be included in the model and describes
that when predictors (independent variables) are considered individually, only
two factors significantly differ between two groups. The last column of the
following table is the p-value corresponding to the F value and confirms that
these variables differ significantly between the two groups at 5% level of
significance.
Table 4.70 Tests of Equality for Discriminant Analysis on Investors’
Return on TSMF
Wilks' Lambda F df1 df2 Sig.
Marital Status .997 1.296 1 398 .256Annual Income .995 2.061 1 398 .152Gender .997 1.310 1 398 .253Corporate Image .989 4.359 1 398 .037**Safety on investment .937 26.776 1 398 .000*Age 1.000 .015 1 398 .903* significant at 1% level of significance
** significant at 5% level of significance
Table 4.71 shows pooled within-group matrices and indicates the
degree of correlation between the predictors. It can be seen from the table,
that variables have significant correlations among them, and hence
discriminant analysis by stepwise method is carried out to take care of the
multicollinearity problem.
153
Table 4.71 Pooled Within-Groups Matrices for Discriminant Analysis on
Investors’ Return on TSMF
Factors Marital Status
Annual Income Gender Corporate
ImageSafety on
Investment Age
Marital Status 1.000 -.170 .022 .095 .126 -.454Annual Income -.170 1.000 -.017 .044 -.164 .196Gender .022 -.017 1.000 .206 -.099 -.129Corporate Image .095 .044 .206 1.000 -.027 -.049Safety on investment .126 -.164 -.099 -.027 1.000 -.133Age -.454 .196 -.129 -.049 -.133 1.000
Table 4.72 shows Eigen values, a large eigen value is an indication
of a strong function. Two functions were developed by the stepwise method
and from the table it can be seen that the function 2 with two variables has a
eigen value of .926.
Table 4.72 Wilks' Lambda for Discriminant Analysis on Investors’
Return on TSMF
Step Number of Variables Lambda df1 df2 df3
Exact FStatistic df1 df2 Sig.
1 1 .937 1 1 398 26.776 1 398.000 .0002 2 .926 2 1 398 15.833 2 397.000 .000
Table 4.73 and Table 4.74 show Eigen values and Wilks’ Lambda
to verify the significant level of discriminant function. From the table, the
chi-square value is found to be 30.466 with the corresponding p-value of .000.
This value is significant at 99% confidence level. It indicates that the
discriminant function is statistically significant and the overall discriminating
power of the discriminant function is good. The eigen value of .080
explaining 100% variance with a canonical correlation of .272, thus
explaining about 8% variation in the dependent variable (gain or loss) by all
the independent variables. But still, the discriminant function is significant in
explaining the variation even at 1% level of significance.
154
Table 4.73 Eigenvalues for Discriminant Analysis on Investors’
Return on TSMF
Function Eigenvalue
% of Variance
Cumulative %
Canonical Correlation
1 .080a 100.0 100.0 .272a. First 1 canonical discriminant functions were used in the analysis.
Table 4.74 Wilks' Lambda for Discriminant Analysis on
Investors’ Return on TSMF
Test of Function(s)
Wilks'Lambda
Chi-square df Sig.
1 .926 30.466 2 .000
Table 4.75 shows standardized canonical discriminant function
coefficients. From the table, it can be noted that Safety is the most important
predictor in discriminating between the groups followed by Corporate Image.
Table 4.75 Standardized Canonical Discriminant Function Coefficients
for Discriminant Analysis on Investors’ Return on TSMF
Factor Function 1Corporate ImageSafety oninvestment
.396
.929
Table 4.76 shows structure matrix table. These structured
correlations indicate that the variables Corporate Image and Safety are the
important predictors in discriminating groups. The table also gives the order
of importance of the predictors in discriminating efficiency level.
155
Table 4.76 Structure Matrix for Discriminant Analysis on Investors’
Return on TSMF
Factors Function 1Safety on investment .918Corporate Image .371Marital Statusa .155Agea -.143Annual Incomea -.135Gendera -.011
Pooled within-groups correlations between discriminating variables and
standardized canonical discriminant functions
Variables ordered by absolute size of correlation within function.
a. This variable is not used in the analysis.
Table 4.77 shows canonical discriminant function coefficients
table, which gives an unstandardized coefficient and a constant value for the
discriminant equation.
Table 4.77 Canonical Discriminant Function Coefficients for
Discriminant analysis on Investors’ Return on TSMF
Function 1
Safety on investment .959
Corporate Image .397
(Constant) .000Unstandardized coefficientsThe discriminant equation can be written as: D=0.959 (Safety on
investment) + 0.397 (Corporate Image)
Table 4.78 shows function at group centroids table. These are
unstandardized canonical discriminant functions evaluated at group means
and are obtained by placing the variable means for each group in the
156
discriminant equation rather than placing the individual variable values. For
the first group, the group centroid is a positive value and for the second group
it is a negative value. This shows that higher the level of consideration of
factors before investment by individuals are likely to have gain and lower
level of consideration are likely to result in loss.
Table 4.78 Functions at Group Centroids for Discriminant Analysis on
Investors’ Return on TSMF
Group Function 1Loss 1.479Gain -.054
Unstandardized canonical discriminant functions evaluated at group means
Table 4.79 shows the classification processing summary, which is a
simple table of the number and percentage of subjects classified correctly and
incorrectly. In leave-one-out-classification, the discriminant model is re-
estimated as many times as the number of subjects in the sample. Each model
leaves one subject and is used to predict the respondent. In other words, each
subject in the analysis is classified from the function derived from all cases
except itself. The diagonal elements of the table represent correct
classification. The hit ratio, which is the percentage of cases correctly
classified, and for this analysis it is 97.0%, and the discriminant function is
judged as efficient.
157
Table 4.79 Classification Results for Discriminant Analysis on Investors’
Return on TSMF
Groups (Loss / Gain)Predicted Group
Membership TotalLoss Gain
Original Count Loss 4 10 14Gain 1 385 386
% Loss 28.6 71.4 100.0Gain .3 99.7 100.0
Cross-validateda
Count Loss 4 10 14Gain 2 384 386
% Loss 28.6 71.4 100.0Gain .5 99.5 100.0
a. Cross validation is done only for those cases in the analysis. In cross
validation, each case is classified by the functions derived from all cases
other than that case.
b. 97.3% of original grouped cases correctly classified.
c. 97.0% of cross-validated grouped cases correctly classified.
4.4.14.1 Discriminant Analysis to determine Main Predictors in
Discriminating Satisfaction of Investors on TSMF
Discriminant analysis was conducted to classify the individuals into
two categories such as satisfied and not-satisfied and to determine which
factors are the main predictors in discriminating between these categories.
The individuals are actually classified as ‘satisfied' if they opted for ‘highly
satisfied’ and ‘satisfied’; not-satisfied if they opted for ‘neither satisfied not
dissatisfied’, ‘dissatisfied’, ‘highly dissatisfied’ for the question on overall
satisfaction on mutual fund investment.
158
Table 4.80 shows the group statistics which gives the means and
standard deviations for both the groups (satisfied and not satisfied). From this
table, few preliminary observations about the groups can be made, and it
clearly shows that the two groups are widely separated with respect to the
factors Corporate image and Safety on investment. The mean of Corporate
image for Satisfied and Not-satisfied individuals are -0.103 and 0.349
respectively, whereas for individuals who are Not-satisfied, the mean of
Corporate Image and Safety on investment are 0.349 and 0.118 respectively.
Table 4.80 Discriminant Analysis Group Statistics for Investors’
Satisfaction on TSMF
Satisfaction Mean Std. Deviation
Valid N (list wise)Unweighted Weighted
Satisfied
District 4.502 2.277 309 309Age 2.495 1.101 309 309Gender 1.227 0.419 309 309Marital Status 1.272 0.446 309 309Annual Income 1.987 0.798 309 309Corporate Image -0.103 1.003 309 309Safety on investment -0.035 1.005 309 309
Notsatisfied
District 4.495 2.363 91 91Age 2.352 0.887 91 91Gender 1.451 0.500 91 91Marital Status 1.363 0.483 91 91Annual Income 1.758 0.672 91 91Corporate Image 0.349 0.911 91 91Safety on investment 0.118 0.979 91 91
Total
District 4.500 2.294 400 400Age 2.463 1.057 400 400Gender 1.278 0.448 400 400Marital Status 1.293 0.455 400 400Annual Income 1.935 0.776 400 400Corporate Image 0.000 1.000 400 400Safety on investment 0.000 1.000 400 400
159
Table 4.81 shows test of equality of group means. F statistic
determines the variable that should be included in the model and describes
that when predictors (independent variables) are considered individually, only
two factors significantly differ between two groups. The last column of the
following table is the p-value corresponding to the F value and confirms that
these variables differ significantly between the two groups at 5% level of
significance.
Table 4.81 Tests of Equality for Discriminant Analysis on Investors’
Satisfaction on TSMF
Variables Wilks' Lambda F df1 df2 Sig.
District 1.000 .001 1 398 .979Age .997 1.298 1 398 .255Gender .956 18.312 1 398 .000*Marital Status .993 2.806 1 398 .095Annual Income .985 6.190 1 398 .013**Corporate Image .964 14.817 1 398 .000*Safety on investment .996 1.651 1 398 .200
* significant at 1% level of significance
** significant at 5% level of significance
Table 4.82 shows pooled within-group matrices and indicates the
degree of correlation between the predictors. It can be seen from the table
from some variables have significant correlations among them, and hence
discriminant analysis by stepwise method is carried out to take care of the
multicollinearity problem.
160
Table 4.82 Pooled Within-Groups Matrices for Discriminant Analysis on Investors’ Satisfaction on TSMF
Factors District Age Gender Marital Status
Annual Income
Corporate Image
Safety on investment
District 1.000 -.045 -.041 -.018 -.063 -.126 .031Age -.045 1.000 -.120 -.451 .190 -.039 -.127Gender -.041 -.120 1.000 .001 .013 .166 -.127Marital Status -.018 -.451 .001 1.000 -.164 .086 .132
Annual Income -.063 .190 .013 -.164 1.000 .061 -.170
Corporate Image -.126 -.039 .166 .086 .061 1.000 -.012
Safety oninvestment .031 -.127 -.127 .132 -.170 -.012 1.000
Table 4.83 shows Wilks’ Lambda values, a large eigen value is an
indication of a strong function. Three functions were developed by the
stepwise method and from the table, it can be seen that the function 3 with
three variables has a eigen value of .917.
Table 4.83 Wilks' Lambda for Discriminant Analysis on Investors’
Satisfaction on TSMF
Step Number of Variables Lambda df1 df2 df3
Exact FStatistic df1 df2 Sig.
1 1 .956 1 1 398 18.312 1 398 .0002 2 .933 2 1 398 14.190 2 397 .0003 3 .917 3 1 398 11.929 3 396 .000
Table 4.84 and Table 4.85 show eigen value and wilks’ lambda to
verify the significant level of discriminant function. From the table the chi-
square value is found to be 34.305 with the corresponding p-value of .000.
This value is significant at 99% confidence level. It indicates that the
discriminant function is statistically significant and the overall discriminating
power of the discriminant function is good. The eigen value of .090
explaining 100% variance with a canonical correlation of .288, thus
161
explaining about 9% variation in the dependent variable (satisfied or not
satisfied) by all the independent variables. But still, the discriminant function
is significant in explaining the variation even at 1% level of significance.
Table 4.84 Eigenvalues for Discriminant Analysis on Investors’
Satisfaction on TSMF
Function Eigenvalue
% of Variance
Cumulative%
Canonical Correlation
1 .090a 100.0 100.0 .288a. First 1 canonical discriminant functions were used in the analysis.
Table 4.85 Wilks’ Lambda for Discriminant Analysis on
Investors’ Satisfaction on TSMF
Test of Function(s) Wilks’Lambda
Chi-square df Sig.
1 .917 34.305 3 .000
Table 4.86 shows standardized canonical discriminant function
coefficients. From the table, it can be noted that Corporate image is the most
important predictor in discriminating between the groups followed by Annual
income and Gender of the respondents.
Table 4.86 Standardized Canonical Discriminant Function Coefficients
for Discriminant Analysis on Investors’ Satisfaction on TSMF
Factor Function 1Gender .626Annual Income -.458Corporate image .566
Table 4.87 shows structure matrix table. These structured correlations
indicate that the variables Corporate image and Annual income are the
important predictors in discriminating groups. The table also gives the order
of importance of the predictors in discriminating efficiency level.
162
Table 4.87 Structure Matrix for Discriminant Analysis on Investors
Satisfaction on TSMF
Factors Function 1Gender .714Corporate image .642Annual Income -.415Agea -.184Marital Statusa .125Districta -.068Safety on investmenta -.009
Pooled within-groups correlations between discriminating variables and
standardized canonical discriminant functions
Variables ordered by absolute size of correlation within function.
a. This variable is not used in the analysis.
Table 4.88 shows canonical discriminant function coefficients table,
which gives an unstandardized coefficient and a constant value for the
discriminant equation.
Table 4.88 Canonical Discriminant Function Coefficients for
Discriminant Analysis on Investors’ Satisfaction on TSMF
Variables Function 1Gender 1.426Annual income -0.594Corporate Image 0.576(Constant) -0.672Unstandardized coefficients
The discriminant equation can be written as: D = -0.672 + 1.426 (Gender) –
0.594 (Annual income) + 0.576 (Corporate image)
Table 4.89 shows function at group centroids table. These are
unstandardized canonical discriminant functions evaluated at group means
163
and are obtained by placing the variable means for each group in the
discriminant equation rather than placing the individual variable values. For
the first group, the group centroid is a negative value and for the second group
it is a positive value. The discriminant equation reveals the fact that female
investors have low level of satisfaction and as the increase in annual income
of individuals increases their level of satisfaction. Similarly, when the factor
corporate image is considered more, it leads to low level of satisfaction.
Table 4.89 Functions at Group Centroids for Discriminant analysis on
Investors’ Satisfaction on TSMF
Group Function 1Satisfied -0.163Not satisfied 0.553
Unstandardized canonical discriminant functions evaluated at group means
Table 4.90 shows the classification processing summary, which is a
simple table of the number and percentage of subjects classified correctly and
incorrectly. In leave-one-out-classification, the discriminant model is
re-estimated as many times as the number of subjects in the sample. Each
model leaves one subject and is used to predict the respondent. In other
words, each subject in the analysis is classified from the function derived
from all cases except itself. The diagonal elements of the table represent
correct classification. The hit ratio, which is the percentage of cases correctly
classified, and for this analysis is 77.8%, and the discriminant function is
judged as satisfactory. The discriminant function is efficient in discriminating
the satisfied investors.
164
Table 4.90 Classification Results for Discriminant Analysis on Investors’
Satisfaction on TSMF
Groups (Loss / Gain)Predicted Group
Membership TotalSatisfied Not satisfied
Original Count Satisfied 300 9 309Notsatisfied 79 12 91
% Satisfied 97.1 2.9 100.0Notsatisfied 86.8 13.2 100.0
Cross-validatedc Count Satisfied 300 9 309Notsatisfied 80 11 91
% Satisfied 97.1 2.9 100.0Notsatisfied 87.9 12.1 100.0
a. Cross validation is done only for those cases in the analysis. In cross
validation, each case is classified by the functions derived from all cases
other than that case.
b. 78.0% of original grouped cases correctly classified.
c. 77.8% of cross-validated grouped cases correctly classified.
4.5 CONCLUDING REMARKS
Risk-adjusted performance of Tax Saving Mutual Fund Schemes
were analysed by using rate of return, standard deviation, Beta, GARCH and
TARCH models, Sharpe, Treynor, Jensen’s Alpha and Fama French. The
performance of the TSMF has been compared with the market benchmark
S&P CNX Nifty. Examining the fund volatility, it is found that the highest
volatility occurred during the period of 2008-09. It is found that there are
certain schemes which have been underperformed than the market
benchmark. There are certain funds that outperform the market benchmark.
Fama French model shows that Reliance Tax Saver (ELSS) Fund is the best
165
performing schemes. Regression analysis shows that there is a relationship
between tax saving schemes and the market.
Other than scheme analysis, individual investors behaviour on risk
and return analysis, methods used for analysis, their return over a period of
time, knowledge on risk factors, monitoring system, grievances and their
satisfaction on Tax Saving Mutual Fund Schemes were also examined in this
chapter. Further the analyses were made on the differences of the
respondents’ demographic characters like Age, Gender, Profession,
Educational Qualification and Annual Income. For the purpose of analysis
Chi-square test, Percentage Analysis, ANOVA, t-test, Regression, Factor
analysis was adopted to identify the important factors considered by the
respondents before making investment and the factors are mainly grouped
into Corporate image and Safety on investment. Discriminant analysis was
conducted to identify the main predictors discriminating the gain or loss and
satisfaction or non-satisfaction of the respondents. Two factors namely
Corporate image and Safety on investment are significant contributor in
determining the opinion on gain or loss of individuals. Other demographic
factors are not significantly contributing the opinion on gain or loss of
respondents. The important predictor for higher level of satisfaction on
TSMF is Gender, Annual income and Corporate image.