Investment Course - 2005

1
Investment Course - 2005

• Day One
• Global Asset Allocation and Portfolio Formation

2
Two Important Concepts Involving Expected
Investment Returns

• 1. Investors perform two functions for capital
  markets
• - Commit Financial Capital
• - Assume Risk
• so,
• E(R) (Risk-Free Rate) (Risk Premium)
• 2. The expected return (i.e., E(R)) of an
  investment has a number of alternative names
  e.g., discount rate, cost of capital, cost of
  equity, yield to maturity. It can also be
  expressed as
• k (Nominal RF) (Risk Premium)
• (Real RF) E(Inflation) (Risk Premium)
• where
• Risk Premium f(business risk, liquidity risk,
  political risk, financial risk)

3
Historical Real Returns, 1954-2003 The Global
Experience
Chile Returns 1/54 6/03 Chile Returns 1/54
12/71 1/76 6/03 Source Global Financial Data
4
Global Historical Volatility Measures, 1954-2003
5
Global Historical Risk Premia, 1954-2003
6
Historical Returns and Risk for Various U.S.
Asset Classes
7
Historical Global Stock Market Volatility
8
More on Historical Asset Class Returns U.S.
Experience
9
Historical Risk Premia vs. T-bills U.S.
Experience
Stocks Bonds Stock - Bond Difference
1926-2004 8.63 2.43 6.20
1980-2004 8.64 4.96 3.68
1995-2004 10.08 5.53 4.55
2000-2004 -3.42 7.20 -10.62
10
Performance of U.S.-Oriented Investment
Strategies 1975-2004
Growth of 1 Avg. Ann. Ret. Std. Dev. Sharpe Ratio
100 Stock 47.52 14.90 16.13 0.540
100 Bond 16.06 10.23 11.26 0.359
100 Cash 6.19 6.19 3.09 nm
60-30-10 Mix 30.70 12.63 11.12 0.579
11
Portfolio Management Strategy Broad View

• Passive Management
• Attempt to generate normal returns over time
  commensurate with investor risk tolerance
• Typically achieved through diversified asset
  class selection and asset-specific portfolio
  formation
• Active Management
• Attempt to generate above-normal returns over
  time relative to acceptable risk level
• Typically achieved either through periodic asset
  class or security-specific portfolio adjustments

12
Two Ways to Increase Returns (i.e., Add Alpha)

• Tactical Allocation Decisions
• - Global Market Timing
• - Asset Class Timing
• - Style/Sector Timing
• Security Selection Decisions
• - Stock or Bond Picking

13
Allure of Tactical Market Timing

• Suppose that on January 1st each year from
  1975-2004, you put 100 of your money in what
  turned out to be the best asset class (stocks,
  bonds, or cash) at the end of the year.
• This is equivalent to owning a perfect lookback
  option that entitles you to receive the return
  for the best performing asset class each year.
• What difference would that type of tactical
  portfolio rebalancing make to your investment
  performance?

14
Allure of Tactical Market Timing (cont.)
Growth of 1 Avg. Ann. Ret. Std. Dev. Sharpe Ratio
100 Stock 47.52 14.90 16.13 0.540
100 Bond 16.06 10.23 11.26 0.359
100 Cash 6.19 6.19 3.09 nm
60-30-10 Mix 30.70 12.63 11.12 0.579
Perfect Foresight 237.68 20.48 10.92 1.309
15
Danger of Missing the Boat (i.e., Not Being
Invested)
Investment Period SP 500 Annualized Return 1980-1989 SP 500 Annualized Return 1990-1999
Entire Decade (2,528 Days) 12.6 15.3
Less 10 Best Days 7.7 11.1
Less 20 Best Days 4.7 8.1
Less 30 Best Days 2.1 5.6
Less 40 Best Days -0.3 3.4

Less 10 Worst Days 21.0 20.1
Less 20 Worst Days 24.7 23.4
Less 30 Worst Days 27.5 26.4
Less 40 Worst Days 30.5 28.9
16
The Asset Allocation Decision

• A basic decision that every investor must make is
  how to distribute his or her investable funds
  amongst the various asset classes available in
  the marketplace
• Stocks (e.g., Domestic, Global, Large Cap, Small
  Cap, Value, Growth)
• Fixed-Income (e.g., Government, Investment
  Grade, High Yield)
• Cash Equivalents (e.g., T-bills, CDs, Commercial
  Paper)
• Alternative Assets (e.g., Private Equity, Hedge
  Funds)
• Real Estate (e.g., Residential, Commercial)
• Collectibles (e.g., Art, Antiques)
• The Strategic (or Benchmark) allocation is the
  proportion of wealth the investor decides to
  place in each of these asset classes. It is
  sometimes also referred to as the investors
  long-term normal allocation because it is
  presumed to be the baseline allocation that
  will remain in place until the investors life
  circumstances change appreciably (e.g.,
  retirement)

17
The Importance of the Asset Allocation Decision

• In an influential article published in Financial
  Analysts Journal in July/August 1986, Gary
  Brinson, Randolph Hood, and Gilbert Beebower
  examined the issue of how important the initial
  strategic allocation decision was to an investor
• They looked at quarterly return data for 91
  pension funds over a ten-year period and
  decomposed the average returns as follows
• Actual Overall Return (IV)
• Return due to Strategic Allocation (I)
• Return due to Strategic Allocation and Market
  Timing (II)
• Return due to Strategic Allocation and Security
  Selection (III)

18
The Importance of the Asset Allocation Decision
(cont.)

• Graphically
• In terms of return performance, they found that

19
The Importance of the Asset Allocation Decision
(cont.)

• In terms of return variation
• Ibbotson and Kaplan support this conclusion, but
  argue that the importance of the strategic
  allocation decision does depend on how you look
  at return variation (i.e., 40, 90, or 100).

20
Examples of Strategic Asset Allocations

• Public Endowments

21
Examples of Strategic Asset Allocations (cont.)

• Public Retirement Fund

22
Examples of Strategic Asset Allocations (cont.)
23
Asset Allocation and Building an Investment
Portfolio

• I. Global Market Analysis
• - Asset Class Allocation
• - Country Allocation Within Asset Classes
• II. Industry/Sector Analysis
• - Sector Analysis Within Asset Classes
• III. Security Analysis
• - Security Analysis Within Asset Classes
• and Sectors

24
Asset Allocation Strategies

• Strategic Asset Allocation The investors
  baseline asset allocation, taking into account
  his or her return requirements, risk tolerance,
  and investment constraints.
• Tactical Asset Allocation Adjustments to the
  investors strategic allocation caused by
  perceived relative mis-valuations amongst the
  available asset classes. Ordinarily, tactical
  strategies overweight the undervalued asset
  class. Also known as market timing strategies.
• Insured Asset Allocation Adjustments to the
  investors strategic allocation caused by
  perceived changes in the investors risk
  tolerance. Usually, the asset class that
  experiences the largest relative decline is
  underweighted. Portfolio insurance is a
  well-known application of this approach.

25
Sharpes Integrated Asset Allocation Model
26
Sharpes Integrated Asset Allocation Model (cont.)

• Notice that the feedback loops after the
  performance assessment box (M3) make the
  portfolio management process dynamic in nature.
• The strategic asset allocation process can be
  viewed as going through the model once and then
  removing boxes (C2) and (I2), thus removing any
  temporary adjustments to the baseline allocation.
• Tactical asset allocation effectively removes box
  (I2), but allows for allocation adjustments due
  to perceived changes in capital market conditions
  (C2).
• Insured asset allocation effectively removes box
  (C2), but allows for allocation adjustments due
  to perceived changes in investor risk tolerance
  conditions (I2).

27
Measuring Gains from Tactical Asset Allocation

• Example Consider the following return and
  allocation characteristics for a portfolio
  consisting of stocks and bonds only.
• Stock Bond
• Allocation Strategic 60 40
• Actual 50 50
• Returns Benchmark 10 7
• Actual 9 8
• The returns to active management (i.e., tactical
  and security selection) are
• Policy Performance (.6)(.10) (.4)(.07)
  8.80
• Actual Performance (.5)(.09)
  (.5)(.08) 8.50
• Active Return - 30 bp

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Measuring Gains from Tactical Asset Allocation
(cont.)

• Also
• (Policy Timing) (.5)(.10)
  (.5)(.07) 8.50
• (Policy Selection) (.6)(.09)
  (.4)(.08) 8.60
• so
• Timing Effect 8.50 8.80
  -0.30
• Selection Effect 8.60 8.80
  -0.20
• Other 8.50 8.60 8.50 8.80
  0.20
• Total Active
  -0.30

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Example of Tactical Asset Allocation Fidelity
Investments
30
Example of Tactical Asset Allocation Texas TRS
31
Example of Tactical Asset Allocation Texas TRS
32
Overview of Equity Style Investing

• The top-down approach to portfolio formation
  involves prudent decision-making at three
  different levels
• Asset class allocation decisions
• Sector allocation decisions within asset classes
• Security selection decisions within asset class
  sectors
• The equity style decision (e.g., large cap vs.
  small cap, value vs. growth) is essentially a
  sector allocation decision
• There is tremendous variation in the returns
  produced by the myriad style class-specific
  portfolios, so investors must pay attention to
  this aspect of the portfolio management process

33
Defining Equity Investment Style

• The investment style of an equity portfolio is
  typically defined by two dimensions or
  characteristics
• - Market Capitalization (i.e., Shares
  Outstanding x Price)
• - Relative Market Valuation (i.e., Value
  versus Growth)

34
Equity Style Classification Specific Terminology

• Market Capitalization
• - Large (gt 10 billion)
• - Mid (1 - 10 billion)
• - Small (lt 1 billion)
• Relative Valuation
• - Value (Low P/E, Low P/B, High Dividend
  Yield, Low
• EPS Growth)
• - Blend
• - Growth (High P/E, High P/B, Low Dividend
  Yield, High
• EPS Growth)

35
Equity Style Grid
Value
Growth
Large-Cap Value (LV) Large-Cap Blend (LB) Large-Cap Growth (LG)
Mid-Cap Value (MV) Mid-Cap Blend (MB) Mid-Cap Growth (MG)
Small-Cap Value (SV) Small-Cap Blend (SB) Small-Cap Growth (SG)
Large
Small
36
Style Indexes Representative Stock Positions
January 2005
Value
Growth
- Russell 1000 Value - ExxonMobil Citigroup - Russell 1000 - General Electric Pfizer - Russell 1000 Growth - Microsoft Wal-Mart
- Russell Mid Value - Archer Daniels Midlan Norfolk Southern - Russell Mid - Monsanto Kroger - Russell Mid Growth - Apple Computer Adobe Systems
- Russell 2000 Value - Goodyear Tire Rubber Energen - Russell 2000 - First Bancorp Crown Holdings - Russell 2000 Growth - Allegheny Technologies Aeropostale
Large
Small
37
Comparative Classification Ratios January
2005(Source Morningstar)
Value
Growth
Fwd P/E 15.3 P/B 2.1 Div Yld 2.2 Fwd P/E 17.8 P/B 2.8 Div Yld 1.6 Fwd P/E 21.6 P/B 3.7 Div Yld 0.9
Fwd P/E 16.1 P/B 2.1 Div Yld 1.8 Fwd P/E 18.4 P/B 2.5 Div Yld 1.2 Fwd P/E 22.9 P/B 3.6 Div Yld 0.4
Fwd P/E 13.7 P/B 1.7 Div Yld 1.7 Fwd P/E 13.1 P/B 2.1 Div Yld 1.1 Fwd P/E 12.3 P/B 3.0 Div Yld 0.3
Large
Small
38
Historical Equity Style Performance 1991-2004
(Source Frank Russell)
Style Class Avg Ann Ret Std Deviation Sharpe Ratio
LV 13.75 13.36 0.731
LB 12.67 14.44 0.602
LG 11.38 17.78 0.416
MV 16.01 13.42 0.896
MB 15.25 15.02 0.751
MG 14.03 21.76 0.462
SV 16.98 14.51 0.896
SB 14.58 18.40 0.576
SG 12.34 23.78 0.352
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Equity Style Rotation 1991-2004
40
Relative Return PerformanceValue vs. Growth
LV Outperforms
LG Outperforms
41
Relative Risk Performance Value vs. Growth
LV Riskier
LG Riskier
42
Relative Return Performance Large Cap vs.
Small Cap
LB Outperforms
SB Outperforms
43
Relative Risk PerformanceLarge Cap vs. Small Cap
LB Riskier
SB Riskier
44
Value vs. Growth Global Evidence (Source Chan
and Lakonishok, Financial Analysts Journal, 2004)
45
Equity Style Investing Instruments and Strategies

• Passive Style Alternatives
• - Index Mutual Funds
• - Exchange-Traded Funds (ETFs)
• Active Style Alternatives
• - Investor Portfolio Formation
• - Open-Ended Mutual Funds

46
Methods of Indexed Investing

• Open-End Index Mutual Funds There is a
  long-standing and active market for mutual funds
  that hold broad collections of securities that
  mimic various sectors of the stock market.
  Examples include the Vanguard 500 Index Fund,
  which recreates the holdings and weightings of
  the Standard Poors 500, and the various
  Fidelity Select Funds, which reproduce the
  profiles of different industry sectors.
• Exchange-Traded Funds (ETF) A more recent
  development in the world of indexed investment
  products has been the development of
  exchange-tradable index funds. Essentially, ETFs
  are depository receipts that give investors a
  pro-rata claim on the capital gains and cash
  flows of the securities held in deposit.

47
Index Fund Example VFINX
48
Index Fund Example (cont.)
49
Top ETFs in the Large Blend Style Category
50
ETF Example SPY
51
ETF Example (cont.)
52
Growth of U.S. Equity Mutual Funds
53
Mutual Fund Performance Characteristics1991-2003
54
Mutual Fund Performance Characteristics1991-2003
(cont.)
55
Notion of Tracking Error
56
Notion of Tracking Error (cont.)
57
Notion of Tracking Error (cont.)

• Generally speaking, portfolios can be separated
  into the following categories by the level of
  their annualized tracking errors
• Passive (i.e., Indexed) TE lt 1.0 (Note TE lt
  0.5 is normal)
• Structured 1.0 lt TE lt 3
• Active TE gt 3 (Note TE gt 5 is normal for
  active managers)

58
Large Blend Active Manager DGAGX
59
Tracking Errors for VFINX, SPY, DGAGX
60
Risk and Expected Return Within a Portfolio

• Portfolio Theory begins with the recognition that
  the total risk and expected return of a portfolio
  are simple extensions of a few basic statistical
  concepts.
• The important insight that emerges is that the
  risk characteristics of a portfolio become
  distinct from those of the portfolios underlying
  assets because of diversification. Consequently,
  investors can only expect compensation for risk
  that they cannot diversify away by holding a
  broad-based portfolio of securities (i.e., the
  systematic risk)
• Expected Return of a Portfolio
• where wi is the percentage investment in the i-th
  asset
• Risk of a Portfolio
• Total Risk (Unsystematic Risk) (Systematic
  Risk)

61
Example of Portfolio Diversification Two-Asset
Portfolio

• Consider the risk and return characteristics of
  two stock positions
• Risk and Return of a 50-50 Portfolio
• E(Rp) (0.5)(5) (0.5)(6) 5.50
• and
• sp (.25)(64) (.25)(100) 2(.5)(.5)(8)(10)(.4
  )1/2 7.55
• Note that the risk of the portfolio is lower than
  that of either of the individual securities

E(R1) 5 s1 8 r1,2 0.4
E(R2) 6 s2 10
62
Another Two-Asset Class Example
63
Example of a Three-Asset Portfolio
64
Diversification and Portfolio Size Graphical
Interpretation
Total Risk
0.40
0.20
Systematic Risk
Portfolio Size
40
1
20
65
Advanced Portfolio Risk Calculations
66
Advanced Portfolio Risk Calculations (cont.)
67
Advanced Portfolio Risk Calculations (cont.)
68
Advanced Portfolio Risk Calculations (cont.)
69
Example of Marginal Risk Contribution Calculations
70
Fidelity Investments PRISM Risk-Tracking System
Chilean Pension System March 2004
71
Chilean Sistema Risk Tracking Example (cont.)
72
Chilean Sistema Risk Tracking Example (cont.)
73
Notion of Downside Risk Measures

• As we have seen, the variance statistic is a
  symmetric measure of risk in that it treats a
  given deviation from the expected outcome the
  same regardless of whether that deviation is
  positive of negative.
• We know, however, that risk-averse investors have
  asymmetric profiles they consider only the
  possibility of achieving outcomes that deliver
  less than was originally expected as being truly
  risky. Thus, using variance (or, equivalently,
  standard deviation) to portray investor risk
  attitudes may lead to incorrect portfolio
  analysis whenever the underlying return
  distribution is not symmetric.
• Asymmetric return distributions commonly occur
  when portfolios contain either explicit or
  implicit derivative positions (e.g., using a put
  option to provide portfolio insurance).
• Consequently, a more appropriate way of capturing
  statistically the subtleties of this dimension
  must look beyond the variance measure.

74
Notion of Downside Risk Measures (cont.)

• We will consider two alternative risk measures
  (i) Semi-Variance, and (ii) Lower Partial Moments
• Semi-Variance The semi-variance is calculated
  in the same manner as the variance statistic, but
  only the potential returns falling below the
  expected return are used
• Lower Partial Moment The lower partial moment
  is the sum of the weighted deviations of each
  potential outcome from a pre-specified threshold
  level (t), where each deviation is then raised to
  some exponential power (n). Like the
  semi-variance, lower partial moments are
  asymmetric risk measures in that they consider
  information for only a portion of the return
  distribution. The formula for this calculation
  is given by

75
Example of Downside Risk Measures
76
Example of Downside Risk Measures (cont.)
77
Example of Downside Risk Measures (cont.)
78
Example of Downside Risk Measures (cont.)
79
Overview of the Portfolio Optimization Process

• The preceding analysis demonstrates that it is
  possible for investors to reduce their risk
  exposure simply by holding in their portfolios a
  sufficiently large number of assets (or asset
  classes). This is the notion of naïve
  diversification, but as we have seen there is a
  limit to how much risk this process can remove.
• Efficient diversification is the process of
  selecting portfolio holdings so as to (i)
  minimize portfolio risk while (ii) achieving
  expected return objectives and, possibly,
  satisfying other constraints (e.g., no short
  sales allowed). Thus, efficient diversification
  is ultimately a constrained optimization problem.
  We will return to this topic in the next
  session.
• Notice that simply minimizing portfolio risk
  without a specific return objective in mind
  (i.e., an unconstrained optimization problem) is
  seldom interesting to an investor. After all, in
  an efficient market, any riskless portfolio
  should just earn the risk-free rate, which the
  investor could obtain more cost-effectively with
  a T-bill purchase.

80
The Portfolio Optimization Process

• As established by Nobel laureate Harry Markowitz
  in the 1950s, the efficient diversification
  approach to establishing an optimal set of
  portfolio investment weights (i.e., wi) can be
  seen as the solution to the following non-linear,
  constrained optimization problem
• Select wi so as to minimize
• subject to (i) E(Rp) R
• (ii) S wi 1
• The first constraint is the investors return
  goal (i.e., R). The second constraint simply
  states that the total investment across all 'n'
  asset classes must equal 100. (Notice that this
  constraint allows any of the wi to be negative
  that is, short selling is permissible.)
• Other constraints that are often added to this
  problem include (i) All wi gt 0 (i.e., no short
  selling), or (ii) All wi lt P, where P is a fixed
  percentage

81
Example of Mean-Variance Optimization (Three
Asset Classes, Short Sales Allowed)
82
Example of Mean-Variance Optimization (Three
Asset Classes, No Short Sales)
83
Mean-Variance Efficient Frontier With and Without
Short-Selling
84
Efficient Frontier Example Five Asset Classes
85
Example of Mean-Variance Optimization (Five
Asset Classes, No Short Sales)
86
Efficient Frontier Example 2003 Texas Teachers
Retirement System
87
Efficient Frontier Example Texas Teachers
Retirement System (cont.)
88
Efficient Frontier Example Texas Teachers
Retirement System (cont.)
89
Efficient Frontier Example Chilean Pension
System (Source Fidelity Investments)

• Base Case Assumptions
• Expected real returns based on 1954 2003 risk
  premiums
• Real returns for developed market stocks and
  bonds areGDP-weighted excluding US
  (equally-weighted returns for stocks and bonds
  are 5.73 and 1.39, respectively)
• Chilean risk-premium volatility estimates
  exclude the period 1/72 12/75

90
Efficient Frontier Example Chilean Pension
System (cont.)
- Correlation matrix is based on real returns
from the period 1/93 6/03 using Chilean
inflation and based in Chilean pesos - Real
returns for developed market stocks and bonds
areGDP-weighted excluding US
91
Efficient Frontier Example Chilean Pension
System (cont.)
Unconstrained Frontier
92
Efficient Frontier Example Chilean Pension
System (cont.)
Constraint Set
93
Efficient Frontier Example Chilean Pension
System (cont.)
Constrained Frontier for Fund A
94
Efficient Frontier Example Chilean Pension
System (cont.)
Asset Allocations of Various Funds Using Point 20
on Unconstrained Frontier
95
Example of Mean-Lower Partial Moment Portfolio
Optimization(Five Asset Classes, No Short Sales)
96
Estimating the Expected Returns and Measuring
Superior Investment Performance

• We can use the concept of alpha to measure
  superior investment performance
• a (Actual Return) (Expected Return) Alpha
• In an efficient market, alpha should be zero for
  all investments. That is, securities should, on
  average, be priced so that the actual returns
  they produce equal what you expect them to given
  their risk levels.
• Superior managers are defined as those investors
  who can deliver consistently positive alphas
  after accounting for investment costs
• The challenge in measuring alpha is that we have
  to have a model describing the expected return to
  an investment.
• Researchers typically use one of two models for
  estimating expected returns
• Capital Asset Pricing Model
• Multi-Factor Models (e.g., Fama-French
  Three-Factor Model)

97
Developing the Capital Asset Pricing Model
98
Developing the Capital Asset Pricing Model (cont.)
99
Using the SML in Performance Measurement An
Example

• Two investment advisors are comparing
  performance. Over the last year, one averaged a
  19 percent rate of return and the other a 16
  percent rate of return. However, the beta of the
  first investor was 1.5, whereas that of the
  second was 1.0.
• a. Can you tell which investor was a better
  predictor of individual stocks (aside from the
  issue of general movements in the market)?
• b. If the T-bill rate were 6 percent and the
  market return during the period were 14 percent,
  which investor should be viewed as the superior
  stock selector?
• c. If the T-bill rate had been 3 percent and the
  market return were 15 percent, would this change
  your conclusion about the investors?

100
Using the SML in Performance Measurement (cont.)
101
Using CAPM to Estimate Expected Return Empresa
Nacional de Telecom
102
Estimating Mutual Fund Betas FMAGX vs. GABAX
103
Estimating Mutual Fund Betas FMAGX vs. GABAX
(cont.)
104
Estimating Mutual Fund Betas FMAGX vs. GABAX
(cont.)
105
The Fama-French Three-Factor Model

• The most popular multi-factor model currently
  used in practice was suggested by economists
  Eugene Fama and Ken French. Their model starts
  with the single market portfolio-based risk
  factor of the CAPM and supplements it with two
  additional risk influences known to affect
  security prices
• A firm size factor
• A book-to-market factor
• Specifically, the Fama-French three-factor model
  for estimating expected excess returns takes the
  following form

106
Estimating the Fama-French Three-Factor Return
Model FMAGX vs. GABAX
107
Fama-French Three-Factor Return Model FMAGX vs.
GABAX (cont.)
108
Fama-French Three-Factor Return Model FMAGX vs.
GABAX (cont.)
109
Style Classification Implied by the Factor Model
Value
Growth
FMAGX
GABAX

Large
Small
110
Fund Style Classification by Morningstar

• FMAGX

• GABAX

111
Does Investment Style Consistency Matter?
Consider the style classification of two funds (A
B) over time
112
Does Investment Style Consistency Matter? (cont.)

• Study conducted using several thousand mutual
  funds from all nine style classes over the period
  1991-2003
• (see K. Brown and V. Harlow, Staying the
  Course Performance Persistence and the Role of
  Investment Style Consistency in Professional
  Asset Management)
• Calculates style consistency measure for each
  fund using two different methods (i.e., R-squared
  from three-factor model, tracking error from
  style benchmark) and correlated these statistics
  with several portfolio characteristics, including
  returns
• Estimated regressions of future fund returns on
  past performance, style consistency, and other
  controls (e.g., fund expenses, turnover, assets
  under management)

113
Correlation of Style Consistency (i.e.,
R-Squared) With Other Fund Characteristics
114
Regression of Future Predicted Returns on (i)
Past Performance (i.e., Alpha), (ii) Style
Consistency (i.e., RSQ), and (iii) Portfolio
Control Variables in both Up and Down Markets
115
Investment Style Consistency Conclusions

• In general, the findings strongly suggest that
  fund style consistency does matter in evaluating
  future fund performance
• Overall, there is a positive relationship between
  fund style consistency and subsequent investment
  performance
• However, the nature of how style consistency
  matters is somewhat complicated
• In up markets, style-consistent funds
  outperform style- inconsistent funds, everything
  else held equal
• The reverse is true in down markets
  style-inconsistent funds outperform
  style-consistent funds, everything else held
  equal
• Up and down markets are predictable in
  advance
• Being able to maintain a style-consistent
  portfolio is a valuable skill for a manager to
  have

116
Using Derivatives in Portfolio Management

• Most long only portfolio managers (i.e.,
  non-hedge fund managers) do not use derivative
  securities as direct investments.
• Instead, derivative positions are typically used
  in conjunction with the underlying stock or bond
  holdings to accomplish two main tasks
• Repackage the cash flows of the original
  portfolio to create a more desirable risk-return
  tradeoff given the managers view of future
  market activity.
• Transfer some or all of the unwanted risk in the
  underlying portfolio, either permanently or
  temporarily.
• In this context, it is appropriate to think of
  the derivatives market as an insurance market in
  which portfolio managers can transfer certain
  risks (e.g., yield curve exposure, downside
  equity exposure) to a counterparty in a
  cost-effective way.

117
The Cost of Synthetic Restructuring With
Derivatives
118
The Hedging Principle
119
The Hedging Principle (cont.)

• Consider three alternative methods for hedging
  the downside risk of holding a long position in a
  100 million stock portfolio over the next three
  months
• 1) Short a stock index futures contract expiring
  in three months. Assume the current contract
  delivery price (i.e., F0,T) is 101 and that
  there is no front-expense to enter into the
  futures agreement. This combination creates a
  synthetic T-bill position.
• 2) Buy a stock index put option contract expiring
  in three months with an exercise price (i.e., X)
  of 100. Assume the current market price of the
  put option is 1.324. This is known as a
  protective put position.
• 3) (i) Buy a stock index put option with an
  exercise price of 97 and (ii) sell a stock index
  call option with an exercise price of 108.
  Assume that both options expire in three months
  and have a current price of 0.560. This is
  known as an equity collar position.

120
1. Hedging Downside Risk With Futures
121
1. Hedging Downside Risk With Futures (cont.)
122
2. Hedging Downside Risk With Put Options
123
2. Hedging Downside Risk With Put Options (cont.)
124
3. Hedging Downside Risk With An Equity Collar
125
3. Hedging Downside Risk With An Equity Collar
(cont.)
Terminal Position Value
Collar-Protected Stock Portfolio
108
97
97
108
Terminal Stock Price
126
Zero-Cost Collar Example IPSA Index Options
127
Zero-Cost Collar Example IPSA Index Options
(cont.)
128
Another Portfolio Restructuring

• Suppose now that upon further consideration, the
  portfolio manager holding 100 million in U.S.
  stocks is no longer concerned about her equity
  holdings declining appreciably over the next
  three months. However, her revised view is that
  they also will not increase in value much, if at
  all.
• As a means of increasing her return given this
  view, suppose she does the following
• Sell a stock index call option contract expiring
  in three months with an exercise price (i.e., X)
  of 100. Assume the current market price of the
  at-the-money call option is 2.813.
• The combination of a long stock holding and a
  short call option position is known as a covered
  call position. It is also often referred to as a
  yield enhancement strategy because the premium
  received on the sale of the call option can be
  interpreted as an enhancement to the cash
  dividends paid by the stocks in the portfolio.

129
Restructuring With A Covered Call Position
130
Restructuring With A Covered Call Position (cont.)
131
Some Thoughts on Currency Hedging and Portfolio
Management
Question How much FX exposure should a portfolio
manager hedge?
Weakening CLP
Strengthening CLP
132
Conceptual Thinking on Currency Hedging in
Portfolio Management

• There are at least three diverse schools of
  thought on the optimal amount of currency
  exposure that a portfolio manager should hedge
  (see A. Golowenko, How Much to Hedge in a
  Volatile World, State Street Global Advisors,
  2003)
• Completely Unhedged Froot (1993) argues that
  over the long term, real exchange rates will
  revert to their means according to the Purchasing
  Power Parity Theorem, suggesting currency
  exposure is a zero-sum game. Further, over
  shorter time frameswhen exchange rates can
  deviate from long-term equilibrium
  levelstransaction costs make involved with
  hedging greatly outweigh the potential benefits.
  Thus, the manager should maintain an unhedged
  foreign currency position.
• Fully Hedged Perold and Schulman (1988) believe
  that currency exposure does not produce a
  commensurate level of return for the size of the
  risk in fact, they argue that it has a long-term
  expected return of zero. Thus, since the
  investor cannot, on average, expect to be
  adequately rewarded for bearing currency risk, it
  should be fully hedged out of the portfolio.
• Partially Hedged An optimal hedge ratio
  exists, subject to the usual caveats regarding
  parameter estimation. Black (1989) demonstrates
  that this ratio can vary between 30 and 77
  depending on various factors. Gardner and
  Wuilloud (1995) use the concept of investor
  regret to argue that a position which is 50
  currency hedged is an appropriate benchmark.

133
Hedging the FX Risk in a Global Portfolio Some
Evidence

• Consider a managed portfolio consisting of five
  different asset classes
• Chilean Stocks (IPSA), Bonds (LVAC Govt), Cash
  (LVAC MMkt)
• US Stocks (SPX), Bonds (SBBIG)
• Monthly returns over two different time periods
• February 2000 February 2005
• February 2002 February 2005
• Five different FX hedging strategies (assuming
  zero hedging transaction costs)
• 1 Hedge US positions with selected hedge ratio,
  monthly rebalancing
• 2 Leave US positions completely unhedged
• 3 Fully hedge US positions, monthly rebalancing
• 4 Make monthly hedging decision (i.e., either
  fully hedged or completely unhedged) on a monthly
  basis assuming perfect foresight about future FX
  movements
• 5 Make monthly hedging decision (i.e., either
  fully hedged or completely unhedged) on a monthly
  basis assuming always wrong about future FX
  movements

134
Investment Performance for Various Portfolio
Strategies February 2000-February 2005
135
Investment Performance for Various Portfolio
Strategies February 2002-February 2005
136
Sharpe Ratio Sensitivities for Various Managed
Portfolio Hedge Ratios
137
Currency Hedging and Global Portfolio Management
Final Thoughts

• Foreign currency fluctuations are a major source
  of risk that the global portfolio manager must
  consider.
• The decision of how much of the portfolios FX
  exposure to hedge is not clear-cut and much has
  been written on all sides of the issue. It can
  depend of many factors, including the period over
  which the investment is held.
• It is also clear that tactical FX hedging
  decisions have potential to be a major source of
  alpha generation for the portfolio manager.
• Recent evidence (Jorion, 1994) suggests that the
  FX hedging decision should be optimized jointly
  with the managers basic asset allocation
  decision. However, this is not always possible
  or practical.
• Currency overlay (i.e., the decision of how much
  to hedge made outside of the portfolio allocation
  process) is rapidly developing specialty area in
  global portfolio management.