2 - 0 Investment Course Day Two: Equity Analysis and Portfolio Strategies

2 - 1 Forming Equity Portfolios: An Overview After an investor’s strategic asset allocation (i.e., the percentage allocations to the broad asset classes) has been established, the next step in the portfolio management process is to form asset class-specific portfolios that we think will align with our investment objectives and constraints. Asset class-level (e.g., stock) portfolios can be formed by following one of two approaches:  Passive: Designed to match a broad equity index (e.g., S&P 500, Russell 1000, IPSA); implicitly assumes that equity markets are efficient  Active: Attempts to outperform a designated equity benchmark, usually through picking stocks perceived to have superior characteristics (e.g., valuation, style) Generally speaking, active equity management can be approached in one of two ways:  Top-Down (i.e., Three-Step) Approach  Bottom-Up (i.e., Stock-Picking) Approach The difference between the two approaches is the perceived importance of macroeconomic and industry influences on individual firms and stocks

2 - 2 The Three-Step Valuation Process 1. General economic influences  Decide how to allocate investment funds among countries, and within countries to bonds, stocks, and cash 2. Industry influences  Determine which industries will prosper and which industries will suffer on a global basis and within countries 3. Company analysis  Determine which companies in the selected industries will prosper and which stocks are undervalued

2 - 3 Example of a Global Portfolio: Texas Teachers Retirement System - September 30, 2004

2 - 4 Example of a Global Portfolio (cont.): Texas Teachers Retirement System - September 30, 2004

2 - 5 Examples of Style-Based Equity Portfolios

2 - 6 General Approaches to Equity Valuation

2 - 7 Enterprise Value vs. Equity Value

2 - 8 The Foundations of Stock Valuation

2 - 9 The Foundations of Stock Valuation (cont.)

The Foundations of Stock Valuation (cont.)

Constant Growth Valuation Example: CSR

Constant Growth Valuation Example: CSR (cont.)

Constant Growth Valuation Example: CSR (cont.)

Constant Growth Valuation Example: CSR (cont.)

The Foundations of Stock Valuation (cont.)

The Foundations of Stock Valuation (cont.)

The Foundations of Stock Valuation (cont.)

Two-Stage Growth Valuation Example: Duo Growth Company The Duo Growth Company just paid a dividend of $1 per share. The dividend is expected to grow at a rate of 25 percent per year for the next three years and then to level off to 5 percent per year forever. You think that the appropriate capitalization (i.e., discount) rate is 20 percent per year.  What is your estimate of the intrinsic value of a share of the stock?  If the market price of a share is equal to this intrinsic value, what is the expected dividend yield?  What do you expect its price to be in one year? Is the implied capital gain consistent with your estimate of the dividend yield and the discount rate? Valuation formula for problem:

Duo Growth Valuation Example: Solution

Estimating Cash Flow Growth Rates

Applying the Stock Valuation Model The discounted cash flow approach to security valuation is the most exhaustive method for establishing a stock’s intrinsic (i.e., fundamental) value. Depending on the level of confidence that the analyst has with regard to the myriad assumptions that he or she has made, the model implies the following trading strategy:  If (Value) > (Market Price)  Buy Stock  If (Value) < (Market Price)  Sell (or Short) Stock The valuation model also gives considerable guidance to help analysts understand what corporate managers must do to increase firm value:  Increase the cash flows generated by assets in place currently  Increase the expected growth rate of earnings  Increase the length of the abnormal growth period  Reduce the cost of capital that is applied to discount the cash flows

Applying the Stock Valuation Model: CFA Exam Question

Applying the Stock Valuation Model: Solution to CFA Exam Question

Applying the Stock Valuation Model: Solution (cont.)

Applying the Stock Valuation Model: Market-Implied Growth Rates

Implied Growth Rate Example: Empresas COPEC - February 2005

COPEC Implied Growth Rate Example (cont.)

Model Output for COPEC Implied Growth Estimate

Defining Measures of Cash Flow

Defining Measures of Cash Flow (cont.)

Defining Measures of Cash Flow (cont.)

Equity Valuation Example: Southwest Airlines (LUV) – January 2003 Positive analyst report in January 2003 by S&P Outlook Basis for the opinion was the forecast of improved growth due to cost-cutting measures at the firm and the company’s position in the industry DCF analysis based on both analyst forecasts and a market-implied scenario Refer to Excel workbook “LUV DCF Model” for the details of the stock valuation

LUV Stock Valuation Example (cont.)

LUV DCF Valuation Model Output

LUV DCF Valuation Model Output (cont.)

LUV Stock Valuation Example (cont.)

Valuing Special Situations: No Current Earnings

Valuing Special Situations (cont.)

Valuing a Negative EPS Company: AMZN in January 2001

Valuing a Negative EPS Company: AMZN in January 2001 (cont.)

Overview of Comparable Multiples Approach to Valuation

Relationship Between DCF and Comparable Multiple Valuation Approaches

DCF and Comparable Multiple Valuation Approaches (cont.)

DCF and Comparable Multiple Valuation Approaches (cont.)

Using Comparable Multiples in Practice: CFA Exam Question

Solution to CFA Exam Question

Solution to CFA Exam Question (cont.)

Using Comparable Multiples in Security Valuation Asset-based valuation multiples (i.e., those using book value) generally produce smaller valuation errors than those using sales (from Lie and Lie, Financial Analysts Journal, 2002)

Comparable Multiple Valuation Example: LUV

Comparable Multiple Valuation Example: LUV (cont.)

Comparable Multiple Valuation Example: LUV (cont.)

LUV Earnings Forecast Model: Bear Stearns – January 2005

LUV Stock Recommendation: Bear Stearns – February 2005

Comparable Multiple Valuation Example: COPEC – February 2005

Comparable Multiple Valuation Example: COPEC (cont.)

Comparable Multiple Valuation Example: COPEC (cont.)

Overview of Equity Portfolio Management Strategies

An Efficient Capital Market A capital market is considered to be efficient if, through their trading activities, investors set the price of any particular security in a manner that impounds new information about that security in an instantaneous manner. Said differently, an efficient market is one in which all security prices are set as if all available information has already been assimilated by investors and traders and that information has been acted upon in the proper way. Thus, the only thing that will change the security’s market price is the arrival of new information which, by definition, is not fully predictable. Notice from the preceding discussion that the critical concept defining an efficient market is not if new information about a particular security is reflected in the security’s market price, but how rapidly the price adjusts to this new information. In establishing whether capital markets are efficient, it is often useful to consider the nature of the information that the market is expected to react to:  Weak Form Efficiency: Information contained in past price movements only.  Semi-Strong Form Efficiency: Public information announcements (e.g., earnings announcements, corporate restructurings)  Strong Form Efficiency: Non-public information (e.g., insider trading)

Efficient vs. Inefficient Information Processing

Market Efficiency: Implications and Evidence One direct implication of capital markets that are economically (if not perfectly) efficient is that it will be impossible over time for a money manager to consistently add “alpha” to a client’s portfolio through such activities as market timing or superior stock selection. This in turn suggests that a passive indexing of asset class investments with the appropriate risk level is the appropriate strategy to follow. Empirical research on capital market efficiency has established the following stylized “facts”:  Markets are generally efficient in both the weak and semi-strong forms over time, but there are some important and consistent deviations from this rule.  Markets are generally not strong form efficient, but the number of people who genuinely possess inside information is smaller than those who think they do.  It is very difficult to establish market efficiency without specifying a model for expected returns (e.g., CAPM, Fama-French three-factor model). This means that any conclusions about market efficiency are subject to the possibility that the expected return model was mis-specified. (This is sometimes referred to as the joint hypothesis problem.)

Two Important Market Efficiency “Anomalies” Market Overreaction

Two Important Market Efficiency “Anomalies” (cont.) Market Underreaction (i.e., Momentum)

Active Equity Management: Technical vs. Fundamental Approaches Technical Approaches: A contrarian investment strategy is based on the belief that the best time to buy (sell) a stock is when the majority of other investors are the most bearish (bullish) about it. In this way, the contrarian investor will attempt to always purchase the stock when it is near its lowest price and sell it (or even short sell it) when it nears its peak. Implicit in this approach is the belief that stock returns are mean-reverting, indicating that over time stocks will be priced so as to produce returns consistent with their risk-adjusted expected (i.e., mean) returns. The overreaction hypothesis shows that investing on this basis can provide consistently superior returns. At the other extreme, active portfolios can also be formed on the assumptions that recent trends in past prices will continue. A price momentum strategy, as it is more commonly called, assumes that stocks that have been hot will stay hot, while cold stocks will also remain so. Although there may well be sound economic reasons for these trends to continue (e.g., company revenues and earnings that continue to grow faster than expected), it may also simply be the case that investors periodically underreact to the arrival of new information. Thus, a pure price momentum strategy focuses just on the trend of past prices alone and makes purchase and sale decisions accordingly.

Active Equity Management: Technical vs. Fundamental Approaches (cont.) Fundamental Approaches: An earnings momentum strategy is a somewhat more formal active portfolio approach that purchases and holds stocks that have “accelerating” earnings and sells (or short sells) stocks with disappointing earnings. The notion behind this strategy is that ultimately a company’s share price will follow the direction of its earnings, which is one “bottom line” measure of the firm’s economic success. In judging the degree of momentum in a firm’s earnings, it is often the case in practice that investors will compare the company’s actual EPS to some level of what was expected. Two types of expected earnings are used most frequently: (i) those generated by a statistical model and (ii) the consensus forecast of professional stock analysts. The previous chart shows that over the period earnings momentum strategies were generally successful as well, although surprisingly not to the same degree as price momentum strategies. A more promising approach to active anomaly investing involves forming portfolios based on various characteristics of the companies themselves. Two characteristics that consistently matter in the stock market are the total capitalization of the firm’s outstanding equity (i.e., firm size) and the financial position of the firm, as indicated by its various financial ratios (e.g., P/E, P/BV). Both attributes are commonly used to define the nature of style investing. There are two general conclusions we can make about these firm characteristics. First, over time, firms with smaller market capitalizations produce different risk-adjusted returns than those with large market capitalizations. Second, over time, firms with lower P/E and P/BV ratios (i.e., value stocks) produce bigger risk-adjusted returns than those with higher levels of those ratios (i.e., growth stocks).

Equity Portfolio Strategy Example: HACAX

Equity Portfolio Strategy Example: HACAX (cont.)

Equity Portfolio Strategy Example: HACAX (cont.)

Equity Portfolio Strategy Example: HACAX (cont.)

Equity Portfolio Strategy Example: HACAX (cont.)

Active vs. Passive Equity Portfolio Management The “conventional wisdom” held by many investment analysts is that there is no benefit to active portfolio management because:  The average active manager does not produce returns that exceed those of the benchmark  Active managers have trouble outperforming their peers on a consistent basis However, others feel that this is the wrong way to look at the Active vs. Passive management debate. Instead, investors should focus on ways to:  Identifying those active managers who are most likely to produce superior risk-adjusted return performance over time This discussion is based on research authored jointly with Van Harlow of Fidelity Investments titled: “The Right Answer to the Wrong Question: Identifying Superior Active Portfolio Management”

The Wrong Question Stylized Fact: Most active mutual fund managers cannot outperform the S&P 500 index on a consistent basis

Defining Superior Investment Performance Over time, the “value added” by a portfolio manager can be measured by the difference between the portfolio’s actual return and the return that the portfolio was expected to produce. This difference is usually referred to as the portfolio’s alpha. Alpha = (Actual Return) – (Expected Return)

Measuring Expected Portfolio Performance In practice, there are three ways commonly used to measure the return that was expected from a portfolio investment:  Benchmark Portfolio Return Example: S&P 500 or Russell 1000 indexes for a U.S. Large-Cap Blend fund manager Pros: Easy to identify; Easy to observe Cons: Hypothetical return ignoring taxes, transaction costs, etc.; May not be representative of actual investment universe; No explicit risk adjustment  Peer Group Comparison Return Example: Median Return to all U.S. Small-Cap Growth funds for a U.S. Small-Cap Growth fund manager Pros: Measures performance relative to manager’s actual competition Cons: Difficult to identify precise peer group; “Median manager” may ignore large dispersion in peer group universe; Universe size disparities across time and fund categories  Return-Generating Model Example: Single Risk-Factor Model (CAPM); Multiple Risk-Factor Model (Fama- French Three-Factor, Carhart Four-Factor) Pros: Calculates expected fund returns based on an explicit estimate of fund risk; Avoids arbitrary investment style classifications Cons: No direct investment typically; Subject to model misspecification and factor measurement problems; Model estimation error

The Wrong Question (Revisited) Stylized Fact: Across all investment styles, the “median manager” cannot produce positive risk-adjusted returns (i.e., PALPHA using return model)

The Right Answer When judging the quality of active fund managers, the important question is not whether:  The average fund manager beats the benchmark  The median manager in a given peer group produces a positive alpha The proper question to ask is whether you can select in advance those managers who can consistently add value on a risk-adjusted basis  Does superior investment performance persist from one period to the next and, if so, how can we identify superior managers?

Lessons from Prior Research Fund performance appears to persist over time  Original View: Managers with superior performance in one period are equally likely to produce superior or inferior performance in the next period  Current View: Some evidence does support the notion that investment performance persists from one period to the next The evidence is particularly strong that it is poor performance that tends to persist (i.e., “icy” hands vs. “hot” hands) Security characteristics, return momentum, and fund style appear to influence fund performance  Security Characteristics: After controlling for risk, portfolios containing stocks with different market capitalizations, price-earnings ratios, and price-book ratios produce different returns Funds with lower portfolio turnover and expense ratios produce superior returns  Return Momentum: Funds following return momentum strategies generate short-term performance persistence When used as a separate risk factor, return momentum “explains” fund performance persistence

Lessons from Prior Research (cont.) Security characteristics, return momentum, and fund style appear to influence fund performance (cont.)  Fund Style Definitions: After controlling for risk, funds with different objectives and style mandates produce different returns Value funds generally outperform growth funds on a risk-adjusted basis  Style Investing: Fund managers make decisions as if they participate in style-oriented return performance “tournaments” The consistency with which a fund manager executes the portfolio’s investment style mandate affects fund performance, in both up and down markets Active fund managers appear to possess genuine investment skills  Stock-Picking Skills: Some fund managers have security selection abilities that add value to investors, even after accounting for fund expenses A sizeable minority of managers pick stocks well enough to generate superior alphas that persist over time  Investment Discipline: Fund managers who control tracking error generate superior performance relative to traditional active managers and passive portfolios  Manager Characteristics: The educational backgrounds of managers systematically influence the risk-adjusted returns of the funds they manage

CRSP (Center for Research in Security Prices) US Mutual Fund Database  Survivor-Bias Free database of monthly returns for mutual funds for the period Screens Diversified domestic equity funds only Eliminate index funds Require 30 prior months of returns to be included in the analysis on any given date Assets greater than $1 million Period 1979 – 2003 in order to analyze performance versus an index fund and have sufficient number of mutual funds Return-generating model: Fama-French E(R p ) = RF + {  m [E(R m ) – RF] +  sml [SML] +  hml [HML]} Style classification  Map funds to Morningstar-type style categories based on Fama-French SML and HML factor exposures (LV, LB, LG, MV, MB, MG, SV, SB, SG) Data and Methodology for Performance Analysis

Methodology: Fund Mapped by Style Group

Use past 36 months of data to estimate model parameters  Standardized data within each peer group on a given date to allow for time- series and cross-sectional pooling [Brown, Harlow, and Starks (JF, 1996)] Evaluate performance  Use estimated model parameters to calculate out-of-sample alphas based on factor returns from the evaluation period Roll the process forward one quarter (one month) and estimate all parameters again, etc. Estimate Model Evaluate Performance 36 Months 3 Months (1 Month) Time Methodology (cont.)

Distributions of Out-of-Sample Future Alphas (FALPHA) Quarterly – Equally Weighted Performance Analysis

Pooled Regressions – Fund Characteristics versus Future Alpha Time Series Analysis Parameter Variable Parameter Estimate Prob Estimate Prob Diversify (R-Sq) Expense Ratio Turnover Assets Intercept Past Alpha 1 Month Alpha 3 Month Alpha (0.036) (0.012) (0.055) (0.023) Volatility(0.012) (0.006)

Use past 36 months of data to estimate model parameters Run a sequence of Fama-MacBeth cross-sectional regressions of future performance against fund characteristics and model parameters (alpha and R 2 ) Average the coefficient estimates from regressions across the entire sample period T-statistics based on the time-series means of the coefficients Cross-Sectional Analysis

Cross-Sectional Performance Results Parameter Variable Parameter Estimate Prob Estimate Prob Diversify (R-Sq) Expense Ratio Turnover Assets Past Alpha 1 Month Alpha 3 Month Alpha (0.021) (0.012) (0.023) (0.019) Volatility(0.011) (0.022) Fama-MacBeth Regressions – Fund Characteristics versus Future Alpha

Logit Performance Analysis Fund Characteristics versus a Positive Future Alpha Parameter Variable Parameter Estimate Prob Estimate Prob Diversify (R-Sq) Expense Ratio Turnover Assets Intercept Past Alpha 1 Month Alpha 3 Month Alpha (0.085) (0.021) (0.159) (0.117) (0.033) (0.228) Volatility(0.003) (0.022)

Probability of Finding a Superior Active Manager Probability of Future Positive 3-month Alpha Median Manager Controls for Turnover, Assets, Diversify, and Volatility

Probability of Finding a Superior Active Manager (cont.) Probability of Future Positive 3-month Alpha “Best” Manager Controls for Turnover, Assets, Diversify, and Volatility EXPR: Std. Dev. Group -2 (Low)0+1+2 (High)(High – Low) PALPHA:-2 (Low) (0.0333) (0.0333) (0.0331) (0.0328) +2 (High) (0.0324) (High – Low)

Portfolio Strategies Based on Active Manager Search Asset Weighted Alpha Deciles - Quarterly Rebalance

Asset Weighted - Quarterly Rebalance Formation Variables Separated by Upper and Lower Quartile Values Portfolio Strategies (cont.)

Use past 9 months of daily data to estimate model and in- sample alpha Optimize portfolio based on an assumption of risk aversion, i.e., risk-return tradeoff preference Compute the performance of the portfolio over the next three (one) months Roll the process forward each quarter and estimate all parameters again, etc. Implementing a “Fund of Funds” Strategy: An Example Estimate Model Evaluate Performance 9 Months 3 Months (1 Month) Time Methodology

“Fund of Funds” Strategy Fidelity Advisor Diversified Equity Fund Styles (6/04)

“Fund of Funds” Portfolio Strategy Portfolio Weights Over Time Portfolio Characteristics

Cumulative Returns versus S&P 500

Active vs. Passive Management: Conclusions Both passive and active management can play a role in an investor’s portfolio Strong evidence for both positive and negative performance persistence (i.e., alpha persistence)  Prior alpha is the most significant variable for forecasting future alpha  Expense ratio, risk measures, turnover and assets are also useful in forecasting future alpha The existence of performance persistence provides a reasonable opportunity to construct portfolios that add value on a risk-adjusted basis

Overview of the Hedge Fund Industry Generally speaking, a hedge fund is an organizational structure for managing private investment capital in a relatively unrestricted manner. Unlike the mutual fund industry we have just studied—which typically imposes severe restrictions on investment activities (e.g., short sale constraints, leverage restrictions)—hedge funds generally face fewer or no such restrictions. Hedge funds are usually classified in the alternative asset category in a portfolio’s strategic asset allocation. Formally, a hedge fund is a managed portfolio that attempts to preserve invested capital, reduce volatility, and provide positive returns under all market conditions. Hedge fund managers attempt to accomplish these goals by taking long and short positions in various securities, using leverage and derivatives, employing arbitrage strategies, and taking positions in virtually any security in which a superior return opportunity is attainable. Sometimes hedge funds are categorized under the more generally heading of absolute return investment strategies because they seek to provide investors with positive returns regardless of the direction of general market movements. However, it is important to recognize that there are a wide variety of investment strategies under the hedge fund umbrella, representing a significant range of the investment risk spectrum.

Overview of the Hedge Fund Industry (cont.) The global hedge fund industry has grown quite rapidly over the past decade. From about 1,000 funds at the start of the 1990s controlling less than $50 billion in assets, by 2004 there were almost 9,000 active funds controlling an estimates $975 billion in assets. The adjacent charts summarize the rapid growth in the assets of the hedge fund industry, which have been growing at about 20% per annum in recent years.

Overview of the Hedge Fund Industry (cont.)

Overview of Hedge Fund Strategies Saying you manage a hedge fund is like saying you play a sport; that comment offers some information, but it is not very specific. In practice, there are several different broad categories of hedge fund investment strategies: Equity-Based Strategies  Long-Short Equity: Perhaps the most “basic” form of hedge fund investing, managers attempt to identify misvalued stocks and take long positions in the undervalued ones and short positions in the overvalued ones. Given that managers may participate in both the long and the short side of the market, one major advantage of the long-short strategy is the ability to generate “double alpha,” unlike the long-only possibilities in the mutual fund industry  Equity Market Neutral: Like the long-short strategy, fund returns are generated via the exploitation of pricing inefficiencies between securities. However, equity market neutral strategies also attempt to limit the overall volatility exposure of the fund by taking offsetting risk positions on the long and short side, an effort that might also entail adopting derivative positions. Absent leverage, these strategies are expected to produce returns of 3%-4% above cash.

Hedge Fund Strategies (cont.) Arbitrage-Based Strategies  Fixed-Income Arbitrage: Fixed income arbitrage returns are generated via the exploitation of valuation disparities caused by market events, investor preferences, shocks to supply or demand, or structural features of the fixed- income market. Because the valuation disparities are typically small, managers usually employ leverage to exaggerate returns. The ability to generate alpha is driven largely by the manager’s skill at modeling, structuring, executing, and managing fixed-income instruments. In order to extract decent returns, leverage of 4 to 8x is common.  Convertible Arbitrage: Convertible arbitrage returns are generated via several sources, including interest income on the convertible bonds, interest on the proceeds of related equity short sales, and the price appreciation of the convertible bonds, as the instruments gradually assume the value of the equity into which they are exchangeable. The intrinsic value that positions are expected to converge upon is based on the optionality of the convertibles, a value derived from the manager’s assumptions about input variables; and is impacted by share price volatility. Convertible bonds frequently change their character through time and if the issuer does well, the bond behaves like a stock, if the issuer does poorly the bond behaves like distressed, and if little happens the convertible will behave like a bond. Due to the changing characteristics of these securities, convertibles will usually sell at a discount to their intrinsic value. Leverage is often employed to enhance returns.

Hedge Fund Strategies (cont.) Arbitrage-Based Strategies (cont.)  Merger Arbitrage: Merger arbitrage returns are dependent upon the magnitude of the spread on merger transactions, which are directly related to the likelihood of the deal not being completed due to regulatory, financial, or company-specific reasons. As the probability of the merger improves, the spread narrows, generating profits for the position. Opportunistic Strategies  High Yield & Distressed: Distressed strategy position returns are generated if and when the corporate turnaround develops. When companies are distressed, their securities can be purchased at deep discounts. As the turnaround materializes, security prices will approach their intrinsic value, generating profits for the distressed manager.

Hedge Fund Strategies (cont.) Opportunistic Strategies (cont.)  Global Macro: Aims to profit from changes in global economies, typically brought about by shifts in government policy that impact interest rates, in turn affecting currency, stock, and bond markets. Participates in all major markets—equities, bonds, currencies and commodities—though not always at the same time. Uses leverage and derivatives to accentuate the impact of market moves. Utilizes hedging, but the leveraged directional investments tend to make the largest impact on performance.  Special situations: Special situation returns depend upon a variety of corporate events. These strategies may involve restructurings or recapitalizations, spinoffs, or carveouts, and directional positions that may not be fully arbitraged. Depending on the manager’s specific strategy, event-driven returns are realized when the catalyst necessary to release the position’s intrinsic value takes place.

Hedge Fund Strategies (cont.) Fund of Funds Investing  Although not formally a separate strategic category, a fund of funds acts like a mutual fund of hedge funds. The primary benefit to the investor of a fund of funds position is that is a convenient method for achieving a well-diversified allocation to the hedge fund investment space.  A fund of funds can either offer concentration in a particular strategy (e.g., long-short equity) and then diversify across different hedge fund managers—this is a multiple manager approach—or it can diversify across strategies, which is the multiple strategy approach.  Another benefit of a fund of funds is that the manager may have access to some individual hedge fund investments that the investor might not have otherwise.  The primary disadvantage to the fund of funds investor is that there will be an extra layer of fees necessary to compensate the fund of funds manager. This additional fee can be as high as 3% of the assets under management.

Risk and Return in the Hedge Fund Industry It is important to note that hedge fund strategies are not riskless. Joseph Nicholas, author of Investing in Hedge Funds, summarizes the risk-return tradeoff to the various hedge fund strategies as follows:

Teacher’s Retirement System of Texas: Absolute Return Fund Portfolio, July 2004

Merger Arbitrage Investing: Example Suppose the shareholders of Company XYZ receive an unsolicited cash tender offer for $30/share. At the time of the offer—which we’ll assume was a complete surprise—XYZ’s shares traded for $20. Suppose further that shortly after the takeover announcement—which still must be approved by regulatory authorities—the price of XYZ’s shares rise to $28. A simple estimate of the market’s implied probability that the takeover bid will ultimately be successful is: [28 – 20] / [30 – 20] = 80% Generally, given the pre-announcement price (P i ), the tender offer (P T ) and the post- announcement market price (P m ) this probability can be expressed: [P m – P i ] / [P T – P i ] P T = 30 P m = 28 P i = 20

Merger Arbitrage Investing: Example (cont.) The essence of merger arbitrage investing is to try to predict better than the market which announced deals will be completed successfully and which will ultimately fail. A merger arbitrage hedge fund manager will take long positions in those deals that he or she thinks have an implied market probability of success that is too low. Also, short positions can be taken in those deals for which the manager’s subjective probability of success is below that of the market. The chart at the right summarizes a recent empirical study that looked at the takeover success probabilities set by the market for collections of deals that succeeded (both competitive and non-competitive tender offers) and a collection that failed. The display indicates that the market can, on average, distinguish good and bad deals early in the process.

Merger Arbitrage Example: JP Morgan H&Q

Merger Arbitrage Example: JP Morgan H&Q (cont.)

Comparing Hedge Funds and Mutual Funds Investor Characteristics  Mutual Funds: Mixture of individuals (54%) and institutions (46%); minimum investments start at $500-$1,000  Hedge Funds: Some individuals, but mostly institutional, consisting endowments (58%), corporate pensions (11%), and public pensions (8%); minimum investments start at $250,000-$1,000,000 Regulatory Requirements  Mutual Funds: Highly regulated; investment activities subject to the Investment Company Act of 1940, also must register with (and be monitored by) National Association of Securities Dealers and Securities and Exchange Commission  Hedge Funds: Except for antifraud standards, they are exempt from regulation by the SEC under the federal securities laws. Generally not subject to any limitations in the management of the fund and not required to disclose information about the hedge fund's holdings and performance, beyond what the sponsor voluntarily agrees to provide to investors.

Comparing Hedge Funds and Mutual Funds (cont.) Fees  Mutual Funds: Both manager fees and sales charges are limited by federal regulation, which also compels explicit and prompt disclosure of those fees to investors  Hedge Funds: Generally, there are no limits on fees. Typically, manager takes a fee of 1-2% of AUM, plus 20% of the profits over a contractually negotiated level. Some funds have sales charges as well. Leverage/Derivative Use  Mutual Funds: Investment restrictions often prohibit the use of margin accounts (91% of all funds) and short sales (69% of funds). Derivative security prohibitions are less common (about 30% of funds).  Hedge Funds: Essentially free to follow any investment strategy that is defined in the contract between investor and manager. In fact, the use of leverage and short positions are two of the distinguishing features that separate hedge funds and mutual funds.