Taming the Factor Zoo in Investments

Selecting factors that affect returns

The shift from actively managed to passively managed funds in the $47 trillion investment management industry is one of the most significant trends in recent years. Passive fund assets surpass those of active funds. Passive funds usually aim to replicate an index or benchmark through a set procedure (without manager discretion) to decide on asset allocation. Funds utilizing factor-based/smart beta strategies have emerged as some of the fastest-growing passively managed investment options, overseeing close to two trillion dollars across 1,000 mutual funds and ETFs.

The following and subsequent articles offer an overview of factor investing, tracing its roots from the Capital Asset Pricing Model to contemporary methods and debates. Initially, we delve into CAPM, the primary model for elucidating and predicting asset returns. CAPM relies solely on one factor in its computation - risk, characterized by a security's volatility and quantified through beta, representing the security's volatility relative to the broader market. As time progressed, CAPM underwent modifications by incorporating supplementary factors into the assessment of asset returns. This expansion of factors prompted one author to coin the term "zoo of factors."

The following article analyzes a newly released book titled Popularity: A Link Between Classical and Behavioral Finance. This book presents a framework for pricing assets that revolves around the idea of popularity, defined as investors' inclination or reluctance towards various factor attributes, be they financial, behavioral, or economic. By integrating behavioral and non-monetary factors alongside traditional risk factors, the model enhances the CAPM. Consequently, it offers significantly improved insights and predictions regarding asset pricing compared to the CAPM, all while staying consistent with the equilibrium model of the CAPM.

The third paper, "Hedge Funds and Factor Investing," explores the incorporation of factor investing into the strategies of numerous hedge funds. It includes case studies of various hedge funds and assesses the effectiveness of these strategies.

A note on terminology. "Factor investing" is the term used to describe the technique of analyzing asset prices with factors as explanatory variables and conducting statistical analysis of historical data. "Smart Beta" is a label for products offerred by mutual funds or ETFs that employ the factor investing method.

Factor Investing and Valuation of Assets 

Factors drive asset returns and help predict the return of a security, index, or fund through statistical analysis of historical data. They are used in a regression model with a linear formula: Y = a + b (factor 1) + c (factor 2) +d (factor 3). Betas of each factor (b, c, and d) calculate the statistical relationship between the factor and the price of asset Y. Larger beta values indicate a stronger impact on the asset's price, while a p-statistic below 0.05 suggests causality.

From Investment Alpha to Beta 

Until recently, "alpha" was commonly utilized by investors for selecting securities or funds. Alpha represents the residual in factor analysis when compared to an index or the performance of peers, measuring the portion of a fund's return attributed to manager skill. Academic studies have revealed that alpha (and therefore the manager's impact on return) can be broken down into factors like company size and security liquidity. As these factors were found to affect returns, many investors sought to benefit from this strategy and the magnitude of alpha decreased along with its explanatory capability.

The pivotal analysis that propelled factors into the spotlight happened in 2009 with the release of a study titled Evaluation of Active Management of the Norwegian Government Pension Fund – Global by professors Andrew Ang, William Goetzmann, and Stephen Schaefer.

The authors demonstrated that the extra benefit of the fund's active management did not truly showcase manager skill but was actually due to implicit exposure to various systematic factors. They suggested embracing a factor investing strategy as a remedy. This analysis has led to the creation of numerous investment products centered on factor investing (or "smart beta"), aiming to offer investors enhanced portfolio diversification and/or better risk-adjusted returns.

Zoo of Factors and Multifactor Models 

The Capital Asset Pricing Model (CAPM), the most commonly used asset pricing model, relies on risk, typically measured by an asset’s market volatility or beta, as the sole determinant of an asset's price. This model, known for its risk/return relationship, became too limiting as additional factors were discovered to influence asset returns. Following the emergence of various factors, over 400 have been proposed by scholars and financial professionals, prompting one researcher to characterize the field as a "Zoo of Factors." Nevertheless, a small number of factors that have withstood thorough scrutiny now underpin the framework of factor investing.

The initial well-known multifactor model, the Fama-French three-factor model, consisted of three factors: the primary market (i.e., the S&P 500), value versus growth, and size (market capitalization). Later, two additional factors (investment in the company and profitability) were included to create a 5-factor model. Andrew Lo then introduced momentum as an additional factor in explaining hedge fund and mutual fund returns. A study by Hansanhodzik & Lo, titled “Can Hedge Fund Returns be Replicated: The Linear Case,” highlights five factors that are correlated and presumed to influence hedge fund performance: equity markets, US Dollar, Credit spreads, bonds, and Commodities. Cliff Assness, the founder of AQR, the largest hedge fund utilizing factor investing, identifies six factors as drivers of investment returns: value, momentum, profitability, low volatility, interest rate carry, and defensive company stock. S&P has developed factor indices for the following factors: Volatility, high beta, size, style, quality, momentum, enhanced value, dividends, capital expenditures, and multi-factor funds. Finally, Invesco utilizes six factors in constructing investor portfolios: Value, Size, Momentum, Low Volatility, Quality, and Dividend Yield.

One ongoing issue with factor selection is the reliance on "data mining." This involves letting a statistical program freely analyze a database of asset return and factor statistics to identify correlations between asset returns and the factors. This frequently leads to statistical correlations lacking economic or financial rationale.

The remedy for data mining is to confirm that a factor is incorporated into a model only when there is a legitimate financial or economic justification for its inclusion.ctor statistics to find correlations between asset returns and the factors. The result is often statistical correlations that have no economic or financial explanation. The antidote to data mining is to ensure that a factor is only used in a model if there is a credible financial or economic explanation for its inclusion.

What is “Smart Beta?” 

Traditional asset allocation typically employs either the market cap-weighted or equally weighted method for portfolio construction. In cap-weighted portfolios, a stock representing 5% of the S&P 500 index in terms of market capitalization (calculated by multiplying the number of outstanding shares by the stock price) would receive a 5% allocation within an S&P 500 index fund. Conversely, in the equally weighted approach, each stock is allocated an equal share within the portfolio.

Smart refers to an alternative methodology to size-based (market-cap) allocations where a security’s price determines its portfolio allocation. A smart beta investment strategy aims to add value by strategically selecting, weighting, and rebalancing index companies based on factors other than market capitalization. These factors are deemed “smart” as they are chosen from economic and financial research results.