This new edition of Equity Management reflects 30 years of research and investment practice by two pioneers of quantitative equity investing. In the 1980s, Bruce Jacobs and Ken Levy published in peer-reviewed journals a series of articles on detecting and exploiting the factors that significantly influence stock returns. Since then, they have examined short selling in the context of long-short portfolios, optimization of portfolios with short sales or other leveraged positions, markets in crisis, and models that can simulate realistic market behavior.
Equity Management: The Art and Science of Modern Quantitative Investing includes the classic 15 articles from the original edition plus 24 articles that were published since the first edition appeared. Together, they present a compelling argument for the benefits of a quantitative approach in a complex, multidimensional, and dynamic factor world.
The chapters are grouped into eight parts, with introductory material that places each section within the broader context of the investment body of knowledge. Part 1 examines the intricacies of stock price behavior and focuses on detecting the characteristics, or factors, behind them. Security prices are neither efficient nor random and unpredictable. Rather, the market is a complex system, permeated by a web of return regularities. These regularities must be "disentangled" to arrive at the real sources of return. This requires analyzing numerous promising return-predictor relationships simultaneously.
Part 2 looks at how best to exploit the investment opportunities detected. The chapters outline a holistic approach that is multidimensional and dynamic. Viewing the market as integrated allows for greater breadth of investigation and greater depth of analysis, hence enhances the potential for more and better insights. A dynamic, multidimensional, proprietary approach that can adapt to changes in the underlying environment is better poised to capture opportunities than an approach that restricts itself to a small number of well-known and static factors.
Part 3 examines how short sales can expand investment opportunities and improve performance. Balancing long and short positions within a portfolio creates a market-neutral portfolio whose performance should reflect the returns and risks of the constituent securities, but not the performance of the overall market. The return from security selection can be transported to virtually any asset class via derivatives, allowing the investor to take advantage of manager skill, wherever it lies, while maintaining any desired asset allocation.
Part 4 focuses on another long-short approach—enhanced active equity, or 130-30 type portfolios. These portfolios retain full exposure to the market return, while pursuing excess returns via short positions and leveraged long positions. The development of 130-30 type portfolios was motivated by Jacobs and Levy’s research into optimization of long-short portfolios, which showed that the optimization process should consider long positions, short positions, and any benchmark holding simultaneously.
The authors also tackled a problem that arises when optimizing portfolios that contain both long and short positions. As the chapters in Part 5 explain, the factor or scenario models of covariance that simplify the optimization process for long-only portfolios do not necessarily apply to long-short portfolios. Jacobs and Levy, working with Harry Markowitz, provide a solution they call “trimability.”
Part 6 addresses the unique risks of leverage, which are distinct from the risk captured by standard deviation, or volatility; most notable is the risk that a margin call can force the unwinding of positions. The mean-variance model central to modern portfolio theory does not consider these unique risks and can thus lead to “optimal” portfolios with very high leverage. The authors present an alternative model—mean-variance-leverage optimization—that allows an investor who is both volatility-averse and leverage-averse to assess the utility of a portfolio.
High levels of leverage almost led to the demise of hedge fund Long-Term Capital Management in 1998 and to the disruption of the entire financial system in 2008-2009. Part 7 examines these episodes and other periods of market crisis, including the 1987 stock market crash. One conclusion is that products and strategies that promise increased returns at reduced risk have attracted investors, encouraged leverage, and too often precipitated not only their own demise, but also the near-collapse of the global economy.
Part 8 presents work undertaken with Harry Markowitz on a model for simulating market behavior. The Jacobs Levy Markowitz Market Simulator (JLMSim) allows users to create their own market models from the bottom up by specifying the numbers and types of market entities, including portfolio analysts, traders, and investors, as well as their decision rules. The results so far suggest that types of investors (value versus momentum), as well as trading rules, can have significant impacts on market stability.