by Perry J. Kaufman
In "Alpha Trading: Profitable Strategies That Remove Directional Risk," Perry Kaufman, an experienced trading systems developer, provides insights on making profitable trades in markets devoid of obvious trends. The book addresses the challenge of finding alpha when markets seem irrational, experiencing price shocks that disrupt diversification and make hedging seemingly impossible. Kaufman offers strategies for trading in directionless markets and those marked by constant price shocks.
Drawing from Kaufman's 30 years of experience in trading across various market conditions, "Alpha Trading" serves as a valuable resource for both professional and serious individual traders. The book provides practical strategies to thrive in markets where traditional trend trading approaches may be less effective.
Chapter 1: Uncertainty
The investment world experienced a significant downturn in August and September 2008, marked by a 47% drop in the Standard & Poor's (S&P) 500 from August 28 to the following March 9. Surprisingly, all types of investments, including hedge funds, commodities, real estate, and stocks worldwide, were negatively impacted. Despite the origin of the subprime disaster in the United States, the U.S. dollar strengthened against the euro during the crisis, emphasizing the global tendency to seek safety in the U.S. during uncertain times.
The key takeaway from this period is the realization that the world of investments is more uncertain than commonly believed. The tendency to overlook risks during prolonged periods of market stability was evident, as seen in the late 1990s tech stock movement and the 1987 crash. In contrast to previous market downturns, the 2008-2009 drop in the S&P lasted longer, emphasizing the unpredictability of market recovery.
As of the present writing, the stock market is down 15% from its highs. Investors who remained invested are experiencing losses, but not devastating ones. Those who panicked and moved their portfolios to money market funds locked in their losses, highlighting the challenge of making the right decisions in the midst of market turbulence—decisions that are only clear in hindsight.
Chapter 2: The Importance of Price Noise
Market noise, characterized by erratic and inconclusive price movements, plays a crucial yet challenging role in price dynamics. It often leads to traders being stopped out of trades, only to witness prices reversing in their favor later. Recognizing noise is not difficult for traders, and extreme cases of noise manifest as price shocks, where a large move is followed by a sharp reversal the next day. However, determining whether a price shock signifies a structural change or is just noise is elusive.
Key questions arise: How can one differentiate between a structural change and a price shock? When does a price move signal a trend change, and when is it mere noise? How can traders capitalize on price noise? While there are no straightforward answers to these questions, exploring them is valuable, shedding light on critical decision-making in trading, which will be further delved into in the subsequent chapters.
Chapter 3: Pairs Trading: Understanding the Process
Pairs trading is a fundamental market arbitrage strategy that is accessible to any diligent trader and is not an industry secret. While increased competition may necessitate more careful trade selection, opportunities still exist. The basic approach involves choosing two fundamentally related companies, preferably direct competitors, such as Dell and Hewlett-Packard. A simple correlation tool or chart observation can help identify pairs that move in a similar manner, reacting similarly to news.
The best pairs trades are typically between direct competitors, offering opportunities even during periods when prices move significantly apart. However, it's crucial to avoid pairs that track each other too closely, as this limits potential opportunities. Traders need to remain vigilant about structural changes in the companies and how these changes might affect their relationship within the industry.
The trade itself involves selling the stronger stock and buying the weaker one, anticipating their prices to correct or come close to each other. The exit point is when the prices have corrected, and the trade is exited. Equalizing the risk of the long and short positions is achieved by calculating the number of shares traded for each stock. This approach aligns with the basic principles of statistical arbitrage (stat-arb). While the selection of pairs, the targeted distortion size, position sizes, and exit criteria may vary among traders, the core concept remains consistent.
Chapter 4: Pairs Trading Using Futures
Pairs trading is effective, but the returns for many stocks are often small, and executing it successfully demands precision. The previous chapter explored pairs trading in airlines and home builders, revealing challenges like insufficient volatility in airline stocks and only marginally favorable results with home builders. While using volatility and distortion filters can enhance results, it typically reduces the number of trades. An unexpected gain was found through capping, which not only improved results but also reduced risk. Despite these challenges, the fundamental concept of trading pairs remains robust, showcasing profits across a broad range of parameter values.
To boost returns, leveraging can be employed by borrowing a portion of the capital needed for trading. If interest rates are low and trading returns are high, borrowing becomes a profitable option. Another approach is using stock options instead of stocks, especially since the traded companies are generally large and liquid, making options a viable choice. Options also provide flexibility in going long or short, and selling one leg allows for receiving a premium that offsets the cost of buying the other leg. While the bullish or bearish bias in the market may keep costs low, evaluating the slippage or bid-asked spread, combined with the net premium of the two legs, is crucial to determine the viability of using options, though it is not the main focus of the discussion.
Chapter 5: Risk-Adjusted Spreads
Not all risk-averse trading follows a mean-reverting pattern. There are instances when two related markets exhibit a steady divergence, driven by factors such as one product being more desirable than another or one company outperforming another. Numerous examples exist in the stock market, with a classic case being the dynamic between Dell and Compaq.
Compaq, an early success story in personal computers and the first to use MS-DOS (Microsoft's first product) in the early 1980s, faced a shift in fortunes. In 1998, Compaq acquired Digital Equipment Corporation, a prestigious minicomputer company. However, Dell's innovative business model, focusing on direct sales without retail outlets, gained rapid traction and outpaced other manufacturers. By 2002, Compaq was compelled to merge with Hewlett-Packard, and eventually, even the Compaq name faded away. This example illustrates how market dynamics can lead to a sustained divergence rather than a mean-reverting pattern.
Chapter 6: Cross-Market Trading and the Stress Indicator
In this chapter, the focus is on evolving times and enhanced technology that enable more versatile trading solutions. The stress indicator is introduced as a method with greater flexibility for identifying buy and sell levels compared to the momentum difference approach used in prior chapters. This indicator is applied to previously discussed pairs, providing the ability to trade across vastly different markets, such as combining physical commodities with stocks dependent on those products.
Previous chapters delved into the classic method of statistical arbitrage (stat-arb), specifically pairs trading. Pairs trading relies on a fundamental relationship between the stock prices of two companies in the same business, influenced by similar events. Correlations between their price movements may vary, presenting both opportunities and risks. Lower correlations offer more opportunities but with increased risk, while higher correlations require careful selection of trades due to potential small profits after accounting for costs.
Stat-arb, represented by pairs trading, has become more challenging as its methods are widely known, leading to increased competition. The chapter explores pairs involving U.S. and European index markets, inflation hedges, and LME metals. The unit returns varied, with some pairs showing promise and others appearing successful but yielding insufficient returns.
The method used to trigger signals is relative value trading, employing a stochastic indicator to calculate the value of each leg over the same period. The stress indicator is introduced as an alternative way to identify trigger points for buy and sell decisions in pairs trading. This indicator is viewed as a more general and robust approach for identifying trade points in various pairs, leading to exploration of additional trading opportunities.
Chapter 7: Revisiting Pairs Using the Stress.Indicator
Following the introduction of the stress indicator in the previous chapter, the focus now shifts to examining the most crucial pairs discussed in Chapter 4, titled "Pairs Trading Using Futures." This time, the stress indicator is employed to generate signals for pairs consisting of equity index and interest rate futures. These sectors are highly liquid, presenting favorable opportunities for pairs trading. The results obtained using the stress indicator are highlighted, revealing notable differences compared to the original momentum difference calculations.
Chapter 8: Traditional Market-Neutral Trading
A market-neutral strategy involves balancing long positions with short positions, aiming for directional neutrality and avoiding exposure to outright price direction risk. By exploiting relationships between different assets, such as buying the Russell 2000 and selling the Dow or S&P during economic shifts, traders can generate profits based on relative gains, irrespective of whether the market moves up or down.
Market-neutral strategies offer immunity to price shocks. For instance, during the aftermath of September 11, 2001, a market-neutral position involving being long the Russell and short the S&P would have offset losses in the long Russell position with short profits in the S&P, providing a hedge against market volatility and closures.
While this book primarily focuses on pairs trading, which involves selecting a small set of markets and a modest investment, traditional market-neutral programs are broader and serve a different purpose. The chapter explores a more general hedging technique, applying it to related and unrelated stocks as well as futures markets, emphasizing the universality of the method across different asset classes.
Chapter 9: Other Stat-Arb Methods
Stat-arb, short for statistical arbitrage, is a traditional method for identifying and capitalizing on price distortions in related stocks. The term pairs trading is used interchangeably with stat-arb. Institutions historically employed this approach by observing companies within a sector performing differently and executing trades that profited from the convergence of their stock prices. However, increased competition, particularly in stat-arb, has made it more challenging.
With the rise of high-frequency trading and the focus on systems that eliminate directional risk and withstand price shocks, competition has intensified. Major investment houses have shifted toward high-frequency trading, gaining advantages in data proximity measured in milliseconds. Despite this trend, there are still selected areas where profitability is possible without directional risk, as discussed in previous chapters.
This chapter explores different approaches to trades without directional risk. It examines the creation of an index for one leg of a pair or the use of mutual funds as alternatives. Additionally, the chapter explores the possibility of forming pairs from components of the Dow or the S&P, as well as creating a market-neutral strategy using stock rankings provided by specialized companies.
Alpha Trading: Profitable Strategies That Remove Directional Risk
February 11, 2011
by Perry J. Kaufman
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