Jacobs Levy - Plan Architecture and Portfolio Engineering

The articles listed here focus on Jacobs Levy Equity Management's philosophy of portfolio management, including the scope of the security selection/portfolio engineering problem, the goal of portfolio management, and the place of an individual portfolio within the investor's overall investment scheme.

As the “Security Selection” introduction noted, our process considers a wide range of return predictors designed to capture economic and behavioral effects, as well as company-specific information and events. But the power of these predictors can differ across different types of stock. The selection process must thus include breadth in terms of coverage of stocks, as well as return predictors. This does not mean that one should ignore the very real differences in price behavior that distinguish particular market subsets, or that one cannot choose to focus on a particular subset, such as value, growth, or small-capitalization stocks. It simply means that the model used for analyzing individual stocks should incorporate all information available from a broad universe of stocks.

“Engineering Portfolios: A Unified Approach,” which appeared as the lead article in a Special Technology Issue of the Journal of Investing (1995), discusses the many benefits of taking a broad, unified approach to the investment problem. Such an approach offers a coherent framework for analysis, one in which each stock in the universe has one and only one alpha, and in which each can be related to every other stock in the universe. A unified approach can also take advantage of more information than a narrower view of the market can provide. The effects of interest rates on value stocks, for example, may have repercussions for growth stock prices, which a focus on growth stocks alone would not indicate. Of practical importance is the fact that a broad, unified approach allows the investment manager to “engineer” portfolios designed to outperform various client-specified mandates.

A broad, unified approach, combined with the power of a security selection system based on an appropriate multivariate analysis of a large number of return predictors, allows for numerous insights into profit opportunities and improves the goodness of those insights; this in turn can lead to superior portfolio performance. The process of translating the insights into the performance is the process of portfolio engineering.

A portfolio optimization process that is customized to include exactly the same dimensions found relevant by the stock selection process helps to ensure that all the opportunities detected by the modeling process are exploited, while all the risks detected are accounted for and controlled. The aim of portfolio engineering should be to provide the maximum possible expected return for the desired level of risk.

“Residual Risk: How Much Is Too Much?” the lead article in the Spring 1996 issue of the Journal of Portfolio Management, considers the portfolio engineering problem within the broader context of the investor's risk policy. In particular, it demonstrates that the investor must factor into the portfolio selection decision the level of manager skill—the manager's ability to deliver incremental return for each unit of incremental risk taken. Taking too little risk may end up costing as much as taking too much!

Key Articles:

· “Residual Risk: How Much is Too Much?” by Bruce I. Jacobs and Kenneth N. Levy, The Journal of Portfolio Management, Spring 1996; and abstracted in The CFA Digest, Winter 1997. article
The optimal level of residual risk for a portfolio is the level that allows the portfolio to provide the highest expected return the manager can generate within the limits of the investor's risk tolerance parameters. As it is not always easy to determine investor risk tolerance or manager ability to add value, portfolios are often pigeonholed” according to residual risk levels alone. “Enhanced passive” or “index-plus” portfolios, for example, are expected to offer excess returns of up to 1% at residual risk levels not to exceed 2%. But such artificial constraints as a 2% bound on residual risk can lead to selection of suboptimal portfolios. In particular, they can lead investors to assume too little risk, hence allow too little expected return, for their actual risk tolerances, or to accept less skillful managers when more highly skilled managers are available. They may also encourage suboptimal manager behavior.

· “Engineering Portfolios: A Unified Approach,” by Bruce I. Jacobs and Kenneth N. Levy, The Journal of Investing, Winter 1995; and abstracted in The CFA Digest, Summer 1996.(1) article
Many traditional equity managers focus on particular subsets of the investment universe—value or growth stocks, for example—and structure their portfolios from preselected groups. By contrast, a “unified” approach starts with a blank slate, having no built-in biases regarding any particular type of stock, and searches the widest possible stock universe and the largest number of investment variables. At the same time, it recognizes differences in stock price behavior across different types of stocks and over time, as well as possible nonlinearities in stock price response to gradations in exposure to a given variable. A unified approach to stock valuation is poised to take advantage of more information and to discover a greater number of potentially profitable investment opportunities. These opportunities are maximized by a portfolio optimization process that is customized along the same dimensions as the valuation process. This ensures a portfolio whose risks and return opportunities are balanced in accordance with the insights garnered from the unified valuation approach. Given its range and depth of coverage, a unified approach provides a firm with substantial flexibility to engineer portfolios to meet a variety of client risk/return requirements.

Other Articles:

· “Alpha Transport With Derivatives,” by Bruce I. Jacobs and Kenneth N. Levy, The Journal of Portfolio Management, May 1999; and abstracted in The CFA Digest, Fall 1999.(2) article
Investors can use derivatives to transport the excess returns available from the selection of securities within a given asset class or subclass to virtually any other asset class. For example, an investor can pursue the return possibilities in small-cap stocks, while using futures or a swap to neutralize exposure to the small-cap asset subclass and establish exposure to the large-cap segment. The investor can thus benefit from both the security selection opportunities in small-cap stocks and the asset class performance of large-cap stocks. Using derivatives in conjunction with market-neutral long-short portfolios can offer further performance enhancement.

· “The Law of One Alpha,” by Bruce I. Jacobs and Kenneth N. Levy, The Journal of Portfolio Management, Summer 1995. article
Firms that use one valuation model for their core portfolio and different models for subsets of that core may end up with multiple estimates of alpha. But as every asset has only one price, doesn't it follow that the asset should have only one mispricing? It is argued here that it hardly makes sense for a single firm to begin the investment selection process with an approach that allows for the possibility of multiple mispricings for a given stock over a given horizon.

Books:

Chinese Translation
Copyright © 2006

· Equity Management: Quantitative Analysis for Stock Selection, by Bruce I. Jacobs and Kenneth N. Levy. McGraw-Hill, New York, NY, 2000. Authorized Chinese translation from English language edition, McGraw-Hill, China Machine Press, 2006.
Bruce Jacobs and Ken Levy have long been recognized as pioneers in quantitative equity management. In the 1980s, they began to publish a series of articles in the peer-reviewed Financial Analysts Journal, Journal of Portfolio Management, and Journal of Investing. These articles were based on the authors' own research into and experience with detecting and exploiting the recurring profit opportunities available in a supposedly "efficient" marketplace. Together, they outline an approach for selecting stocks and constructing portfolios that has the potential to deliver superior returns over time.

Equity Management collects 15 of these articles, from 1988's "Disentangling Equity Return Regularities" through 1999's "Alpha Transport with Derivatives." These are grouped into three parts that cover the range of Jacobs and Levy's investment philosophy and strategy, from selecting securities to engineering portfolios to expanding opportunities with short selling and derivatives. New introductory material provides a perspective on the articles, placing each within the broader context of the investment body of knowledge.

The authors' approach to security selection begins with the concept of a complex market. In their view, U.S. security prices are not efficient, nor random and unpredictable. Neither, however, is the market a simple system; simple "rules" such as "buy low P/E" or "buy value" will not be able to yield consistent investment profits. Rather, a complex market is permeated by a web of return regularities. Furthermore, these regularities are interrelated and must be "disentangled" in order to arrive at real sources of return. Disentangling requires analyzing multiple promising return-predictor relationships simultaneously. The resulting "pure" estimated returns are additive and more robust than those from simpler, one-factor analyses.

The breadth of return-predictors considered in the security selection process, as well as the depth of analysis, help to capture the complexity of market pricing. But predictors can differ across different types of stocks. This dimension of complexity is best captured by viewing the broadest possible range of stocks through a wide-angle analytical lens. This is the case when the model used for analyzing individual stocks incorporates all the information available from the broad universe of stocks. This approach offers a coherent framework for analysis and is poised to take advantage of more information than a narrower view of the market (one focusing on particular styles or segments, for example) might provide.

Maximizing the opportunities detected in the security selection process requires a disciplined approach to portfolio construction. Quantitative techniques such as optimization are best suited to ensuring that opportunities are maximized, while risks are controlled. Proprietary portfolio optimization, in which the portfolio is optimized along the same dimensions that are considered in the security selection process, can further enhance portfolio performance.

Allowing for short sales expands investment opportunities, hence has the potential to improve performance. When long and short positions are balanced, the resulting portfolio is market neutral; its performance should reflect the returns and risks of the individual constituent securities, but not the performance of the market from which those securities were selected. Long and short positions are best determined in a single, integrated optimization. This frees the portfolio from benchmark weight constraints and allows it more flexibility in the pursuit of return and control of risk.

A long-short portfolio reflects the ability of the manager to select securities. The alpha, or excess return, from this security selection can be transported (along with its associated risk) to virtually any desired asset class via the purchase of derivatives on that asset class. The investor can thus take advantage of manager skill, wherever it lies, while maintaining an asset allocation that would not ordinarily encompass the securities exploited by the skilled manager.

Together, the articles in Equity Management provide a fascinating review of the concepts that form the foundation of modern active equity management.

Book Chapters:

· “An Architecture for Equity Portfolio Management,” by Bruce I. Jacobs and Kenneth N. Levy, in Frank J. Fabozzi and Harry M. Markowitz, Eds. Equity Valuation and Portfolio Management. John Wiley and Sons, Hoboken, NJ, September 2011. Earlier versions appeared as “Investment Management: An Architecture for the Equity Market,” in Frank J. Fabozzi, Ed. Handbook of Finance, Volume II: Investment Management and Financial Management. John Wiley & Sons, Hoboken, NJ, 2008; Chapter 1 in Frank J. Fabozzi, Ed. Active Equity Portfolio Management. Frank J. Fabozzi Associates, New Hope, PA, 1998; and in Fabozzi, Ed. Handbook of Portfolio Management. Frank J. Fabozzi Associates, New Hope, PA, 1998.
A blueprint of the U.S. equity market reveals three basic building blocks—a comprehensive core representing all U.S. equity issues; static style subsets, comprising large-cap growth stocks, large-cap value stocks, and small-cap stocks; and a dynamic entity reflecting differing relative performance in different market environments. Investment approaches, too, can be categorized into three groups—passive, traditional active, and engineered active. Engineered active management has the potential to provide the best match between client risk/return goals and investment returns, because it can offer consistent performance relative to the equity market core or its various subsets.

Industry Press Publications:

· “How to Build a Better Equity Portfolio,” by Bruce I. Jacobs and Kenneth N. Levy, Pension Management, June 1996.
Investors in U.S. equity can choose among a variety of selection universes, from the broad core including all stocks to various style subsets. They can also choose from a variety of investment approaches, from passive to traditional active to engineered active. Investors may be able to make more informed decisions if they understand the “architecture” of investing that links selection universes and investment approaches to their potential risks and returns.

· “Broader Indexes Widen Horizons,” by Kenneth N. Levy and Bruce I. Jacobs, Pensions & Investments, August 20, 1984.
The S&P 500 is not truly representative of the broader U.S. equity market. It is biased toward large-cap stocks, for example, and exhibits less earnings variability, growth and market variability than the broader universe. This has implications for passive investors in search of a proxy for the U.S. equity market return.