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Transcript
```Portfolio Performance
Evaluation
Chapter 24
McGraw-Hill/Irwin
Introduction
Complicated subject
Theoretically correct measures are difficult
to construct
Different statistics or measures are
appropriate for different types of
investment decisions or portfolios
are different
The nature of active management leads to
measurement problems
24-2
Dollar- and Time-Weighted Returns
Dollar-weighted returns
Internal rate of return considering the cash
flow from or to investment
Returns are weighted by the amount invested
in each stock
Time-weighted returns
Not weighted by investment amount
Equal weighting
24-3
Text Example of Multiperiod Returns
Period
Action
0
Purchase 1 share at \$50
1
Purchase 1 share at \$53
Stock pays a dividend of \$2 per
share
2
Stock pays a dividend of \$2 per
share
Stock is sold at \$54 per share
24-4
Dollar-Weighted Return
Period
Cash Flow
0
-50 share purchase
1
+2 dividend -53 share purchase
2
+4 dividend + 108 shares sold
Internal Rate of Return:
 51
112
 50 

1
(1  r ) (1  r ) 2
r  7.117%
24-5
Time-Weighted Return
53  50  2
r1 
 10%
50
54  53  2
r2 
 5.66%
53
Simple Average Return:
(10% + 5.66%) / 2 = 7.83%
24-6
Averaging Returns
Arithmetic Mean:
Text Example Average:
n
rt
r
t 1 n
(.10 + .0566) / 2 = 7.83%
Geometric Mean:
Text Example Average:
1/ n


r   (1  rt )  1
 t 1

n
[ (1.1) (1.0566) ]1/2 - 1
= 7.81%
24-7
Geometric & Arithmetic Means Compared
Past Performance - generally the geometric mean is
preferable to arithmetic mean because it represents a
constant rate of return we would have needed to earn
in each year to match actual performance over past
period.
Predicting Future Returns from historical returns
arithmetic is preferable to geometric mean, because
it is an unbiased estimate of the portfolio’s expected
return. In contrast while the geometric mean is
always less than the arithmetic mean, it constitutes a
downward- biased estimator of the stock’s expected
return.
24-8
Abnormal Performance
What is abnormal?
Abnormal performance is measured:
Benchmark portfolio
Market model / index model adjusted
Reward to risk measures such as the Sharpe
Measure:
E (rp-rf) / p
24-9
Market timing
Superior selection
Sectors or industries
Individual companies
24-10
1) Sharpe Index
rp - rf
p
rp = Average return on the portfolio
rf = Average risk free rate
=
Standard
deviation
of
portfolio
 p return
24-11
M2 Measure
Developed by Modigliani and Modigliani
Equates the volatility of the managed
portfolio with the market by creating a
hypothetical portfolio made up of T-bills
and the managed portfolio
If the risk is lower than the market,
leverage is used and the hypothetical
portfolio is compared to the market
24-12
M2 Measure: Example
Managed Portfolio: return = 35%
standard deviation = 42%
Market Portfolio: return = 28%
T-bill return = 6%
standard deviation = 30%
Hypothetical Portfolio:
30/42 = .714 in P (1-.714) or .286 in T-bills
(.714) (.35) + (.286) (.06) = 26.7%
Since this return is less than the market, the managed portfolio
underperformed
24-13
2) Treynor Measure
rp - rf
ßp
rp = Average return on the portfolio
rf = Average risk free rate
ßp = Weighted average for portfolio
24-14
3) Jensen’s Measure
 p= rp - [ rf + ßp ( rm - rf) ]
 p = Alpha for the portfolio
rp = Average return on the portfolio
ßp = Weighted average Beta
rf = Average risk free rate
rm = Avg. return on market index port.
24-15
Appraisal Ratio (Information Ratio)
Appraisal Ratio = p / (ep)
Appraisal Ratio divides the alpha of the portfolio
by the nonsystematic risk
Nonsystematic risk could, in theory, be
eliminated by diversification
24-16
Which Measure is Appropriate?
It depends on investment assumptions
1) If the portfolio represents the entire
investment for an individual, Sharpe Index
compared to the Sharpe Index for the market.
2) If many alternatives are possible, use the
Jensen or the Treynor measure
The Treynor measure is more complete
24-17
Limitations
Assumptions underlying measures limit
their usefulness,
When the portfolio is being actively
managed, basic stability requirements are
not met,
Practitioners often use benchmark portfolio
comparisons to measure performance.
24-18
Market Timing
Adjusting portfolio for up and down
movements in the market
Low Market Return - low ßeta
High Market Return - high ßeta
24-19
Example of Market Timing
rp - rf
* *
* *
*
*
* *
* **
* *
* * *
** *
*
*
* *
rm - rf
24-20
Decomposing overall performance into
components
Components are related to specific
elements of performance
Example components
Industry
Security Choice
Up and Down Markets
24-21
Attributing Performance to Components
Set up a ‘Benchmark’ or ‘Bogey’ portfolio
Use indexes for each component
Use target weight structure
24-22
Attributing Performance to Components
Calculate the return on the ‘Bogey’ and on
the managed portfolio,
Explain the difference in return based on
component weights or selection,
Summarize the performance differences
into appropriate categories.
24-23
n
n
i 1
i 1
rB   wBi rBi & rp   w pi rpi
n
n
i 1
i 1
rp  rB   w pi rpi   wBi rBi 
n
 (w
i 1
r  wBi rBi )
pi pi
Where B is the bogey portfolio and p is the managed portfolio
24-24
Contributions for Performance
Contribution for asset allocation
+ Contribution for security selection
(wpi - wBi) rBi
wpi (rpi - rBi)
= Total Contribution from asset class wpirpi -wBirBi
24-25
Complications to Measuring Performance
Two major problems
Need many observations even when portfolio
mean and variance are constant
Active management leads to shifts in parameters
making measurement more difficult
To measure well
You need a lot of short intervals
For each period you need to specify the makeup
of the portfolio
24-26
Style Analysis
Based on regression analysis