Date post: | 10-Apr-2018 |
Category: |
Documents |
Upload: | aarti-j-kaushal |
View: | 212 times |
Download: | 0 times |
of 53
8/8/2019 Lecture 14 Week 13
1/53
Lecture 14 Week 13
Alternative investment classes and
Performance Evaluation
8/8/2019 Lecture 14 Week 13
2/53
2
1 Introduction
Alternative investments tend to:
Require large initial capital
Possess barriers to entry
Illiquid
Be restricted to professional investors
Examples:
Venture capital funds
Hedge funds
8/8/2019 Lecture 14 Week 13
3/53
3
1 Introduction
Principles of investments should still apply:
Diversification
Risk-return trade-off
Do alternative investments offer superior
risk-return trade-offs?
Do alternative investments enhance the risk-
return of a portfolio?
8/8/2019 Lecture 14 Week 13
4/53
4
2 Private equity
What is private equity?
Business concepts need capital
Private equity generally funds businessconcepts
Small group of investors
Not available to the public
Common in early stages of a business
8/8/2019 Lecture 14 Week 13
5/53
5
2 Private equity
Includes family businesses
Worth USD $8 trillion in USA
Compared with $9 trillion for stock market
Typical industries:
Services
Retail & wholesale Light manufacturing
8/8/2019 Lecture 14 Week 13
6/53
6
2 Private equity
8/8/2019 Lecture 14 Week 13
7/53
7
2 Private equity
Private equity returns might be higher
because:
Illiquidity Poor diversification
Low survival rates
Difficult to estimate private equity returnsbecause:
No public trading by definition
Lack of disclosure
8/8/2019 Lecture 14 Week 13
8/53
8
2 Private equity
Performance of private equity
All private equity in USA, 1963-99
Includes small businesses 5 million units worth
$6 trillion
Compound return: 13.2%pa
S&P500 return: 15.6%
8/8/2019 Lecture 14 Week 13
9/53
9
2 Private equity
8/8/2019 Lecture 14 Week 13
10/53
10
2 Private equity
Returns from private equity appear no better
than public equity returns.
Why?
Entrepreneurs over-estimate success ability
Entrepreneurs are more risk tolerant
Entrepreneurs enjoy non-pecuniary benefits
Entrepreneurs have preference for skewness
8/8/2019 Lecture 14 Week 13
11/53
11
2 Private equity
Private equity life cycle: Business concept
Angel investor Business angel
Business structure
Venture capital
IPO
As the business grows, so capital requirementsincrease
Not all good business ideas succeed Dilution of ownership
Creates conflict for the entrepreneur
Average IPO in Aust raised $13.7 million
8/8/2019 Lecture 14 Week 13
12/53
12
2 Private equity
Private equity funds bundle up investments
and offer them to broader range of investors
Control of $9 billion in Australia Capital is typically locked-up for several years
Opportunity to increase exposure through
additional capital contributions Exit strategy is typically through an IPO
8/8/2019 Lecture 14 Week 13
13/53
13
3 Venture capital
Venture capital is a sub-set of private equity
VC funds specialise in private equity
investments
VC funds provide enhanced access to
investors to private equity
VC works with the business to get it to exit
Exit strategy is typically through an IPO
8/8/2019 Lecture 14 Week 13
14/53
Venture capital
Australian market
Around $9 billion
Small by world standards (US: $18
0
billion) Low relative share of0.12% of GDP
OECD average is 0.26%
Dominated by superannuation funds
Some specialisation in biotech
8/8/2019 Lecture 14 Week 13
15/53
15
3 Venture capital
8/8/2019 Lecture 14 Week 13
16/53
16
3 Venture capital
Funding Stages:
Stage 1: Start-up $1-3 million
Stage
2: Development
$2-5 million
Stage 3: Expansion $5-10 million
Possible mezzanine financing
VC takes large fees
VC takes large ownership stakes
Costly compared to traditional investments
8/8/2019 Lecture 14 Week 13
17/53
17
3 Venture capital
Returns to VC funds
Early research supported high returns
Gompers & Lerner (1997): 30% pa Chen et al (2002): 45% pa
Cochrane (2005): 698% to financing rounds
(not pa)
But VC returns are non-normal and
traditional averages are not appropriate
8/8/2019 Lecture 14 Week 13
18/53
18
3 Venture capital
-100% 0% 500%
A few big winners
Several losers
Distribution of VC winners
Source: Cochrane (2001)
Lots of small winners
8/8/2019 Lecture 14 Week 13
19/53
19
3 Venture capital
Appearance of winners, but many
funding rounds are hidden
Focus on those that make it to market IPOs and Acquisitions
Returns:
Mean winners: 108% compound
Several in excess of500%
8/8/2019 Lecture 14 Week 13
20/53
20
3 Venture capital
Many VC rounds end with no furtheraction
Not all rounds/ investors make it tomarket
No exit strategy (no liquidity)
Returns:
Mean: 15% compound
More than 50% of rounds earn negative IRR
8/8/2019 Lecture 14 Week 13
21/53
21
3 Venture capital
-100% 0% 400%
Almost no big winners
Lots of losers
Distribution of all VC rounds
VC projects all rounds: n=16,800 (USA); Source: Cochrane (2001)
A few small winners
8/8/2019 Lecture 14 Week 13
22/53
22
3 Venture capital
VC have high risk
Gompers & Lerner: Beta = 1.4
Cochrane: Beta = 1.
7
Risk adjust (against NASDAQ): mean
return is -7.1%
Evidence does not support superior risk-adjusted returns
8/8/2019 Lecture 14 Week 13
23/53
23
4 Hedge funds
Hedge strictly means to establish a
position to offset downturns
General view is hedge funds avoid losses
Global industry:
8,000 funds with $1,000 billion
Popularity rose through 1990s
8/8/2019 Lecture 14 Week 13
24/53
24
4 Hedge funds
Characteristics:
Minimum large investment
Not regarded as public funds
Light regulation
Smaller than superannuation and mutual
funds
Investment strategies are unorthodox Investment assets can be unorthodox
High fees
8/8/2019 Lecture 14 Week 13
25/53
8/8/2019 Lecture 14 Week 13
26/53
26
4 Hedge funds
Strategies and Types:
Long-short equity
Arbitrage
Event driven
Global macro
Emerging markets
Distressed
8/8/2019 Lecture 14 Week 13
27/53
27
4 Hedge funds
Fee structures
Management fee
Around 1.5% Performance fee
High water mark
Overall, fees are higher than traditionalfunds
8/8/2019 Lecture 14 Week 13
28/53
28
4 Hedge funds
Fund-of-funds
Fund invests in other hedge funds
Creates diversification Provides small investor access
But additional fees
Fund-of-fund fees plus individual fund fees
8/8/2019 Lecture 14 Week 13
29/53
29
4 Hedge funds
Performance measurement problems
Lack of required disclosure
Reporting lags in the system
Establishing net of fees return measures Appropriate return measure given non-normal
distributions caused by derivatives
Early research Positive alphas
Superior Sharpe ratios exceed mutual funds by 20%
Low betas (ave: 0.23)
Ackermann et al (1999)
8/8/2019 Lecture 14 Week 13
30/53
30
4 Hedge funds
New evidence:
Alpha = -4.5% (annual excess of market
return) Beta = 0.84 (vs benchmark of 1.0)
Source: Asness et al (2001)
Only 1 in 4 hedge funds earn significantexcess returns
Capocci & Hubner (2004)
8/8/2019 Lecture 14 Week 13
31/53
31
4 Hedge funds
8/8/2019 Lecture 14 Week 13
32/53
32
4 Hedge funds
Research casts doubt on ability of hedge
funds to earn superior returns
Average hedge fund is less risky than themarket but not low risk
Variable across fund strategy
Appears that hedge funds do not earn
superior risk-adjusted returns
8/8/2019 Lecture 14 Week 13
33/53
33
4 Hedge funds
But, hedge funds do have lower
correlations
Enhance a traditional portfolio in certaincircumstances
Portfolio efficiency is improved
Suggestion of 1
0
-20%
mix of hedge funds
8/8/2019 Lecture 14 Week 13
34/53
Performance evaluation of managed
funds key questions
is past performance relevant?
how can fund management be measured?
what has been the evidence on fund managers
performance? Typically regarded as important input in investment
decisions Sweeney Research found that 54% of investors regard
long-term performance as the most important factor
Australian Securities and Investments Commission (ASIC)revealed that past performance is included in 70% ofcommercial advertisements
8/8/2019 Lecture 14 Week 13
35/53
35
2 The relevance of past
information Empirical research find past performance
correlated with future fund flows.
That is funds with good past performancegenerate greater investor interest.
Sirri and Tufano (1998)
investors are attracted to good performers in the USA Sawicki (2000) and Frino, Heaney and Service
(2005)
similar results for the Australian market.
8/8/2019 Lecture 14 Week 13
36/53
36
3 Performance measures
The managed funds industry places an
emphasis on performance measures
Examples include;
star ratings (from * to *****) of ASSIRT and
Morningstar
publication of league tables
Australian Financial Reviewand PersonalInvestmentregularly carry statistics and rankings
of funds based on past performance
8/8/2019 Lecture 14 Week 13
37/53
37
3 Performance measures
Index benchmarks
comparison to a pre-selected benchmarkportfolio, which is typically an index (eg. S&P/ASX200
or 300
) benchmark related to fund objective
Success measured by tracking error
where Rpt = portfolio return over time period t
RBt = benchmark return over time period t
!
!T
1t
Btpt RR
T
1ATP
8/8/2019 Lecture 14 Week 13
38/53
38
3 Performance measures
Index benchmarks Example: index portfolio designed to track the
S&P/ASX 200 index
8/8/2019 Lecture 14 Week 13
39/53
39
3 Performance measures
Index benchmarks the absolute average tracking performance
(AATP) measure is sometimes used.
This measure is sensitive to errors in both
directions. overcomes averaging problem
where |x| = the absolute value of x
T
1t
tpt
T
1T
8/8/2019 Lecture 14 Week 13
40/53
40
3 Performance measures
Index benchmarks Yet another alternative that overcomes the
problem of the average measure is to measure
the standard deviation of tracking errors.
This measure has the effect of penalizing large
tracking errors
WT
1t
2
tptT
1
)T(
8/8/2019 Lecture 14 Week 13
41/53
41
3 Performance measures
Index benchmarks: Example: consider the following returns on
mimicking portfolio of world market index.
8/8/2019 Lecture 14 Week 13
42/53
42
3 Performance measures
Traditional performance measures
Jensen's alpha
Jensens (1968) alpha relies upon the security
market line.
If a fund is performing to expectations (relative to
the CAPM) then E would be zero. Superior performance is indicated positive Ewhile
under-performance negative E
relies on CAPM being correct model
fmpfpp FE
8/8/2019 Lecture 14 Week 13
43/53
43
3 Performance measures
Traditional performance measures
The Sharpe Index
based on the capital market line
The benchmark value is the Sharpe index for the
market
does not rely on an asset pricing model
captures jointly aspects of return and risk
p
fp
p
RRSI
!
8/8/2019 Lecture 14 Week 13
44/53
44
3 Performance measures
Traditional performance measures
The Treynor index
similar to the Sharpe index except that it is based
on the ex-post security market line
superior performance indicated where Treynorindex exceeds the market risk premium (MRP)
problems include correct value of MRP and need toestimate beta. Also appropriateness of CAPM
p
fp
pTIF
8/8/2019 Lecture 14 Week 13
45/53
45
3 Performance measures
Traditional performance measures
The information ratio
claimed to be an efficiency measure
ie. how much risk was taken to earn the excessreturn
values close to 1 indicate good performance
!
!
T
1t
2
Btpt
Btpt
p
RR
T
1
)RR(IR
8/8/2019 Lecture 14 Week 13
46/53
46
3 Performance measures
Traditional performance measures
Example: Using the following data, compare the
performance of the following 3 funds.
8/8/2019 Lecture 14 Week 13
47/53
47
3 Performance measures
Traditional performance measures
Example (cont.):
8/8/2019 Lecture 14 Week 13
48/53
48
3 Performance measures
Traditional performance measures
Example (cont.): Summary of key points
First, both Funds A and B are judged to be superior
performers. Their values of Jensens alpha are positive
both the Sharpe and Treynor indices exceed those of themarket index.
However, Fund A is considered to be the most efficient
given the values of the information ratio
Second, Fund C is judged to have poor performance
negative Jensens alpha, Sharpe and Treynor indices forFund C are less than those of the market index.
8/8/2019 Lecture 14 Week 13
49/53
49
3 Performance measures
Traditional performance measures
Example (cont.): Summary of key points
Third, there is inconsistency in rankings across the
measures. Fund A is ranked highest under both Jensens alpha, the
Treynor index and the information ratio
Fund B is ranked highest under the Sharpe index.
The inconsistency in rankings is due to differences in the
unit risk measure.
The Sharpe index uses standard deviation whereas theTreynor index uses beta risk. Note: if fund is welldiversified, these measures will become similar.
8/8/2019 Lecture 14 Week 13
50/53
50
3 Performance measures
Market timing measures
seek to specifically measure fund manager
attributes such as market timing
A positive value of
Ep is indicative of superior stockselection performance
a positive value for p indicates superior market
timing ability.
pt2
ftmtpftmtppftpt I]FE
8/8/2019 Lecture 14 Week 13
51/53
51
3 Performance measures
Market timing measures Merton (1981) defines market timing as
performance relative to risk-free rate.
Managers can switch between equity and bonds, soportfolio return is comprised of a return on the equitymarket plus a put option on the equity market
option valuable when equity return falls below risk-freerate
positive values ofJp indicate market timing ability.
? Aptftmtpftmtppftpt ,0Max IJFE
8/8/2019 Lecture 14 Week 13
52/53
52
4 Performance studies
Performance
Early studies found that managed funds, on
average, under-performed the benchmarks.
Sharpe (1966) average Sharpe index was lessthan the Dow Jones Market Index
Jensen (1968) average Jensen's alpha was -1.1%
recent evidence mixed
depends on sample period used, benchmark
index and fees
8/8/2019 Lecture 14 Week 13
53/53
53
4 Performance studies
Performance persistence
In essence, the research has examined whether
winners repeat over time
mild evidence of top-performing fundsexhibiting performance persistence
stronger evidence is towards poorly performing
funds, which tend to perform poorly in future
periods
potentially related to interaction of the business
cycle and investment style