EQUITY MARKET-NEUTRAL can be a deceptive name. Equity-market-neutral strategies are not without risk; they merely neutralize one kind of risk in favor of another. In equity portfolios, there are two primary sources of risk: stock selection and the market. Selecting stocks involves uncertainty about the fate of a particular stock. MARKET RISK is exposure to uncertainty about what the stock market as a whole will do next. Because they think they can predict the fate of a particular stock better than the direction of the market as a whole, equity-market-neutral specialists try to neutralize systemic risks associated with the market in favor of exposure to STOCK SELECTION RISK. They do so by taking a large number of long positions in stocks that they think will outperform the market and an offsetting amount of short positions in stocks that they think will underperform the market. Most practitioners of the strategy rely on quantitative, computer-run models. Equity-market-neutral specialists use these quantitative models to create a statistical advantage in picking stocks and a strategic advantage in controlling exposure to systemic risk. This approach is designed to produce consistent returns with very low volatility in a variety of market environments.

Equity-market-neutral strategists may extend this logic across sectors, industries, and investment styles. For example, if they take a long position in an information technology stock that they think is undervalued, then they will take an offsetting short position in an information technology stock that they think is overvalued. By being long and short in equal amounts, the equity-market-neutral strategist insulates the portfolio from any systemic turn of events that affects the information technology sector as a whole and emphasizes the ability of the chosen model to pick over- and undervalued stocks.

At the heart of most equity-market-neutral strategies is a proprietary multifactor model (econometric or otherwise) of equity risk and return that constructs an optimal portfolio while neutralizing systemic risks. Equity-market-neutral strategists capitalize on the power of these quantitative models to analyze financial data for large numbers of stocks over multiple factors. Because quantitative models can analyze such large amounts of data once they are constructed, equity-market-neutral strategists sometimes use the entire breadth of the market to protect themselves from its caprices. They take large numbers of positions because they believe that their statistical advantage in picking stocks is similar to the advantage that the house enjoys in blackjack: any one bet may go against it, but in the long run the odds are statistically in its favor.

Next, an equity-market-neutral specialist applies a model to the defined universe of stocks. This model does two things: it identifies the most relatively overvalued and relatively undervalued stocks in the universe and defines the risk factors of owning those particular stocks. The model evaluates companies by using a set of indicators or factors. The INDICATORS that are plugged into the model are usually based on publicly available information and conceptually sound and stable economic ideas about value, they possess a good historical forecasting record, and have a low correlation with other indicators in the model. Indicators with more forecasting ability will be appropriately weighted in the model. A similar model is used to evaluate SYSTEMIC RISK FACTORS.

After evaluating the defined universe of stocks for both value and risk, the equity-market-neutral specialist creates the optimal bundle of equal amounts of undervalued and overvalued stocks while maintaining as close to a net zero exposure to the systemic risk factors as possible.

General Motors (GM) and Ford offer a simple illustration of a paired equity-market-neutral strategy. From a risk perspective, they both make autos and have finance subsidiaries and international operations. If the investment selection process ranks Ford highly and General Motors poorly, the investor can go long Ford and short GM. It is easy to have equal dollar-weighted positions of these very liquid stocks. By replicating this long/short construction process in each of the other sectors, you have built a paired long/short strategy.

Paired strategies are understandable, but the opportunity for execution is limited. In reality, there are very few combinations of liquid stocks with opposite performance expectations and identical risk profiles in the same industry.

Consider the challenge presented by a favorable investment selection ranking of General Electric (GE). Holding this company as a long position could require many other firms to be sold short to maintain industry neutrality. GE is in a wide variety of businesses and does not fit into one industry. Its businesses include jet engine manufacturing, leasing, appliances, investment management, electrical distribution, industrial controls, plastics, broadcasting, and our friend the light bulb.

A manager who wants to be as close to neutral as quantifiably possible must offset a variety of market and industry risk factors. This calls for an iterative approach to portfolio construction. Rather than pairing a series of companies together in a portfolio, the long and short portfolios are viewed holistically. The key concern is that the risk characteristics of the long and short portfolios are mirror images. Quantitative risk characteristics can be used to create a risk sensitivity measure for each controlled factor. The long portfolio is built relative to the short portfolio, while the short portfolio is built relative to the long portfolio.¹

More comprehensively, this can be done at the portfolio level. The risk characteristics of the long and the short portfolio can be matched (beta risk, economic risk, interest-rate risk, and so forth) while building the optimal strategy.

An example from our history is fairly recent. Some stock selection models that are fundamental in orientation analyze price-to-earnings ratios in order to determine whether a stock is undervalued or overvalued. From 2002 to 2004, small-cap stocks greatly outperformed big-cap stocks, leaving the model biased towards big caps, which looked more attractive compared to their small-cap counterparts. Meanwhile, the concurrent slide of the dollar against overseas currencies caused companies that generate much of their business overseas to outperform the market, and thus appear unattractive from a P/E ratio standpoint. The portfolio manager must balance the trading strategy’s predilection for high alpha stocks with the need to neutralize the overall portfolio’s exposure to market-capitalization and currency risks. He must decide on the importance of these attributes relative to each stock, balance the risk profile of each stock, and balance the transaction cost associated with each stock. Because of these complex interactions, computer algorithms are used to fully balance the portfolio.

The quantitative nature of equity-market-neutral strategies creates an image of a black box that, once established, runs of its own accord. In fact, equity-market-neutral specialists expend a great deal of time and resources on constantly improving and refining their models. At the trading level, they will rebalance their portfolios continuously to reflect the model’s changing opinions of individual stocks and to maintain neutrality over the chosen risk factors. In addition, equity-market-neutral specialists must develop state-of-the-art trading systems that allow them to implement their model-driven strategies in a cost-effective manner.²

In many markets, all stocks are not available to short. Equity-market-neutral specialists try to get around this difficulty by screening the liquidity of stocks in their investment universe to eliminate stocks that are or will be in short supply. Another worry for equity-market-neutral specialists is getting caught in a short squeeze. They try to avoid short squeezes by taking short positions in stocks in which investors have shown little interest. A positive feature of short selling is the interest that is collected after the borrowed stock is sold and before it is bought back, which is called the short interest rebate. Nevertheless, short selling is a complicated trading process that requires resources to implement. Equity-market-neutral specialists try to build these implementation costs into their models.

Equity-market-neutral strategies generate returns on both the long and short sides; these returns have a low correlation to the returns of long-only market indexes. Because of its low correlation to other asset classes, an equity-market-neutral strategy can provide diversification relative to those other asset classes.

FIGURE 5.2 shows the total strategy assets and net asset flows per year from 1990 to 2004 for equity market neutral. The year-end asset total equals the previous year’s asset size plus annual performance plus net asset flows. Since the end of 1998, approximately $10 billion in net inflows has increased the strategy’s total assets under management almost threefold to over $21 billion at the end of 2004.

FIGURE 5.3 shows the return distribution for equity market neutral compared to the overall hedge fund industry, stocks, and bonds. Note that performance in this strategy is focused in the 0 to 2 percent per month range which results in its consistent low-volatility performance.

FIGURE 5.4 shows the average upside and downside capture since 1990 for equity-market-neutral funds. Note that the strategy’s performance beats the total hedge fund industry, stocks, and bonds during down months. This example of downside protection reflects the essence of market-neutral investing.

Dollar neutrality. A zero net exposure that characterizes all equity-market-neutral managers.

Equity-market-neutral portfolio. A portfolio composed of balanced exposure to long stock positions and offsetting short stock positions.

Indicators. Financial data used to forecast the future performance of a company.

Market exposure. The amount of a portfolio exposed to market risk because it is not matched by an offsetting position.

Short selling.The practice of borrowing a stock on collateral and immediately selling it on the market with the intention of buying it back later at a lower price.

Stock selection risk. Exposure to uncertainty about the future valuation of a particular stock.

Systemic or market risk. Exposure to uncertainty about systemic rises and falls in stock market prices that affect the prices of all stocks in a market or sector.

Systemic risk factors. Factors, such as interest rates or the price of oil, that have the ability to affect the valuation of a whole range of securities, or an entire market, if they change.