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transcript
The Nepalese Stock Market:
Efficient and Calendar
Anomalies
Title:
The Nepalese Stock Market:
Efficient and Calendar
Anomalies
Author:
Dr. Fatta Bahadeur K.C.
Narayan Krishna Joshi
Published in:
Economic Review, Vol 17
Date:
2005
About
Presented By:
Mr. Nitesh Khatiwada
Mr. Manish Das
Ms. Dipti Dhungel
Ms. Prabha Kafle
Ms. Anjana K. C.
Ms. Roshana Machamasi
Presented in:
Seminar in Investment
Analysis and Portfolio
Management
MBM; NCC
Date:
22 May, 2016
Review
◉ Efficient Capital Market: A review of Theory and
Empirical Work – Fama, 1970
◉ Efficient Market Hypothesis?
◉ Existence of anomalies
Anomalies: Deviation from the normal or common order or rule
Introduction
General
◉ To identify stock price anomalies in the context
of Nepal
Specific
◉ To examine the existence of all type of
seasonalities in Nepalese Stock Market
◉ To test weak form of market efficiency
Objective
“
All the information set is fully reflected in
security prices – Fama (1970)
If it is impossible to make economic profit
by trading on the basis of information set
– Jensen (1978)
◉ Weak Form
◉ Semi Strong Form
◉ Strong Form
Informational Effeciency
Calendar Anomalies
◉ Seasonal Irregularities
◉ Reflected in various financial market
◉ May be result of
Data mining
Data Snooping
Anomalies
Calendar Anomalies
◉ Month of the Year Effect
Tax Loss Selling Hypothesis
The Window Selling Hypothesis
Differential Information Hypothesis
Market Microstructure Biases
Anomalies
Calendar Anomalies
◉ Day of the Week Effect
The Calendar Time Hypothesis
The Trading Time Hypothesis
Anomalies
Calendar Anomalies
◉ Holiday Effect
High rate of return before holidays
Pre Holiday
Post Holiday
Regular days
Anomalies
Calendar Anomalies
◉ Half Month Effect
Tendency of common stock return to be low
in the second half of the calendar month than
first half of the calendar month
Anomalies
Calendar Anomalies
◉ Turn of the Month Effect
Average daily rate of return on common stock
different in turn of the month than that of
remaining days of the calendar
Anomalies
Calendar Anomalies
◉ Time of the Month Effect
Returns are highest during the first third
Drop during the second third
Lowest or negative in the last third
Anomalies
◉ Daily Logarithmetic return on NEPSE calculated
◉ Time: February 1, 1995 – December 31, 2004
◉ 2345 trading days
◉ Rt = 100*Ln(NEPSEt /NEPSEt-1)
Rt : Continuously compounded rate of change in the stock market
NEPSEt : Stock market index at time t
NEPSEt-1 : Stock market index at time t-1
Ln : Natural Logarithm
Methodology
Independent Dependent
Variables
NEPSEt
NEPSEt-1
Rt
Month of the Year Effect
◉ Mean return for each month of calendar year
are equal
◉ No difference in returns across months
◉ Consistent to the result obtained for emerging
market by Jordan (Maghayereh, 2003)
Findings
Day of the Week Effect
◉ Existence of day of the week effect
◉ Different pattern from those observed in most
other developed markets
◉ Instead of negative returns of Monday or
Tuesday – negative on Thursday
◉ Significant positive return on Sundays
Findings
Holiday Effect
◉ Positive holiday effect for 1998 and 2000 but
inverted and fading holiday effect for 2002
◉ Statistically insignificant and inconsistent with
other developed markets
◉ Fading holiday effect since 2002
Findings
Half-Month Effect
◉ No half of the month effect
◉ There is no statistical difference between stock
returns of FHM and SHM
◉ Consistent to those observed in international
market
Findings
Turn of the Month (TOM) Effect
◉ No TOM effect for the period 1995-2004
◉ Significant TOM effect for 2003 and inverted
TOM effect for 1999
◉ Inconsistent to that of other international market
Findings
Time of the Month Effect
◉ No time of the month effect for entire period and
sub period, post 1999
◉ For pre 1999, reverse time of the month effect –
inconsistent to US market
Findings
◉ NEPSE is
Not efficient in weak form if day of the week
is examined
Weakly efficient in respect of other anomalies
◉ May be due to market imperfections
◉ Research required to conform the findings and
validate it for individual shares.
Summary and Conclusions
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