Equity Market Neutral Strategies

Equity market neutral strategies attempt to provide a return that is uncorrelated with the overall market. In order to accomplish this goal, equity market neutral managers match long and short stock positions of related companies such that the net exposure to market risk factors (i.e., beta, country, currency, industry, market cap, style, or a combination of these factors) is neutralized and the expected out-performance of the long position relative to the short position is captured. There are two general types of equity market neutral strategies: statistical arbitrage trading and market neutral long/short equity.

Statistical Arbitrage

Statistical arbitrage strategies utilize quantitative and technical analysis to detect undervalued and overvalued stocks of closely associated companies. Undervalued stocks are purchased, and overvalued stocks are sold short with the expectation that over time prices will revert to their mean (i.e., prices will return to the appropriate fair value). Generally, statistical arbitrage strategies use proprietary models that are tested on historical data to determine statistically significant profit opportunities that are expected to repeat. The general process of creating and implementing a statistical arbitrage strategy involves theorizing a relationship and profit opportunity among securities, translating the.profit opportunity into a set of trading rules, and then back-testing the strategy on historical data to determine its ability to generate profits. Critics of statistical arbitrage strategies have labeled the strategies "black box" investing since investors often are not given details of the trading model.

Market Neutral Long/Short Equity-

Market neutral long/short equity strategies build portfolios by u tilizing computerized optimization programs that select strong companies for long positions and weak companies for short positions based on specified selection criteria. There are three steps to implement the market neutral long/short equity strategy:

1. Screen and rank—stocks are screened and ranked from best to worst based on the specified criteria and universe of stocks.

2. Select stocks—stocks are chosen based on value factors (i.e., price-to-book, price-to-earnings, etc.) and momentum factors (i.e., price or earnings momentum, strength indicators, moving averages, etc.).

3. Construct the portfolio—long positions in strong companies and short positions in weak companies are established based upon the optimization model.

Pair Trading

Pair trading is a type of statistical arbitrage strategy. In a pair-trading strategy, the hedge fund manager takes a long position and a short position in two related stocks (i.e., two small capitalization stocks within a certain industry and geographic region) with the expectation that the long position will rise to its fair value and the short position will fall to its fair value. An example will help solidify the pair-trading concept.

Example: Pair trading

A.hedge.fund.manager has decided.to implement a pair trade by purchasing $2,500,000 . (62,500 shares) worth of BCS stock and simultaneously shorting $2,500,000 - ■ \

(approximately 45,455 shaxes) of RMY stock, both of which operate in the U.S.'biotech industry. Currently, BCS stock has a market value of $40 pet share, but the manager believes the fair value is actually $45 per share. RMY's current market value is $55 per ; share, but the manager believes the fair value is actually $50 per share. BCS and RMY are: expected to pay dividends of $1.00 per share and $1.50 per. share, respectively. As part of the short sale, the manager must post 50% margin with an associated borrowing cost of 5%. Transaction costs are expected to be $ 1,000 per trade. Determine the return on the. . strategy assuming BCS and RMY return to their projected values in six months.


Time Period Action

Short 45,455 shares of RMY stock at $55 Transaction costs for two trades

T = 6 months Sell 62,500 shares of BCS at $45 Buy 45,455 shares of RMY at $50 Dividend on BCS ($1.00 per share) Dividend on RMY ($1.50 per share) Transaction costs for two trades

2,812,500 -2,2.72,750 62,500 -68,183 -2,000 -30,822

Profit from strategy


Summing all of the cash flows from the inception of the strategy to its completion six months later, we find that the profit from the strategy is $499,245. The annualized percent return from the strategy is calculated as follows:

annualized return from the pair-trading strategy :

$499,245 ]



Note that the AIMS do not specifically ask for a calculation of the profit and return from a pair trading strategy. We have included the example to demonstrate the mechanics of the strategy.

Market Inefficiencies Exploited by Market-Neutral Hedge Fund Managers

In an efficient market, security prices established through market trading reflect their theoretical fair value. When the market develops inefficiencies, the market value of a security diverges from the theoretical fair value for a short period of time. Market neutral hedge fund managers attempt to profit from inefficiencies that persist as the market slowly digests information and eliminates price discrepancies.

Generally, market neutral strategies look for inefficiencies related to value or momentum factors and exhibit biases toward these factors. Academic research demonstrates that value stocks (i.e., stocks priced below fair value) achieve higher returns than predicted by the capital asset pricing model (CAPM) and that momentum strategies (i.e., buying recent out-performers and selling recent under-performers) generate positive excess returns. In addition, market neutral managers invest in small capitalization stocks where information inefficiencies and a lack of analyst coverage allow for excess return opportunities. Fama and French confirm the usefulness of these factor biases in research demonstrating the positive performance from three simple investment strategies: (1) high minus low (HML)—long high book-to-market (value) stocks and short low book-to-market (growth) stocks; (2) small minus big (SMB)—long small cap-stocks and short large-cap stocks; and (3) up minus down (UMD)—-long recent out-performers and short recent under-performers.

Much debate exists over the source of returns from following value, momentum, and small-cap strategies. Some, including Fama and French,1 argue that risk premia not captured by models such as the CAPM are the cause, while others claim that irrational investors create inefficiencies in the market. Whatever the source of return, market neutral managers continue to pursue profit opportunities by using value, momentum, and small-cap strategies.

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