Research Review | 15 April 2022 | Risk Factor Premia

A Look Under the Hood of Momentum Funds
Ayelen Banegas and Carlo Rosa (Federal Reserve)
February 2022
Momentum investing has surged over the past few years, with assets growing at three times the rate of conventional funds. Using a comprehensive dataset of US equity funds, this paper examines the economic value of momentum funds. Overall, we find that risk-adjusted returns of momentum funds are, on average, negative, and most of the time series variation of those returns is explained by exposure to the market factor. Furthermore, momentum funds do not improve the performance of investors who already invest in Fama-French factors.

Factor Information Decay: A Global Study
Emlyn Flint (Peresec) and Rademeyer Vermaak (STANLIB)
December 2021
This research addresses a simple but important unanswered question in the factor investing literature: how do the factor exposures of equity factor strategies decay over time? The answer to this question has two important practical consequences. Firstly, understanding how a strategy’s factor exposures change over time informs the optimal rebalancing period. Secondly, when coupled with factor risk premia estimates, it describes the term structure of expected returns per factor strategy. To answer this question, we conduct a large-scale empirical study of five well-known factors – Value, Momentum, Quality, Investment and Low Volatility – across 12 developed and emerging markets over the last 20 years. We calculate factor exposure, or information, distributions per market for both pure and quartile long/short factor portfolios, and then analyse how these distributions decay over a 36-month holding period. In order to formally measure the rate of information decay, we introduce the idea of a factor half-life metric and use the global half-life results to propose optimal rebalancing periods per factor.

Anomaly or Possible Risk Factor? Simple-To-Use Tests
Benjamin Holcblat (University of Luxembourg), et al.
March 2022
Basic asset pricing theory predicts high expected returns are a compensation for risk. However, high expected returns might also constitute anomalies due to frictions or behavioral biases. We propose two complementary simple-to-use tests to assess whether risk can explain differences in expected returns. We provide general theoretical equilibrium foundations for the tests and show their properties in simulations. The tests take into account risks disliked by risk-averse individuals, including high-order moments and tail risks. None of the tests rely on the validity of a factor model nor other parametric statistical models. Empirically, we find risk cannot explain a large majority of variables predicting differences in expected returns. In particular, value, momentum, operating profitability, and investment appear to be anomalies.

Momentum and Short-Term Reversals: Theory and Evidence
Narasimhan Jegadeesh (Emory University), et al.
March 2022
How might markets exhibit both short-term reversals and longer-term momentum? Motivated by this question, we develop a dynamic model which includes noise traders and investors who underreact to signals that they do not themselves produce. Our setting implies the following: Return predictability transitions from reversals to weak predictability to momentum as the lag horizon lengthens. Short-term reversals weaken following earnings announcements, and increase when retail trading is higher. These predictions are supported empirically. If noise trader demands are positively autocorrelated, our model generates sharp buildups and collapses of stock prices as in the recent GameStop episode.

Risky Value Meets Behavioral Momentum
Aleksandr Zotov (University of Southern California)
January 2022
This paper demonstrates that risk-based and behavioral cross-sectional asset pricing anomalies can plausibly coexist. To this end, I build a model in which risk-based value premium exists along with behavioral momentum. The value premium stems from differential exposures of stocks to rare disaster risk. Momentum is the result of behavioral underreaction to firm-specific news. The model reproduces several key patterns about value and momentum factor returns, including average excess returns, factors’ correlation and the failure of CAPM in explaining both anomalies. The model also generates the reversal of momentum returns precisely due to the existence of a persistent value premium. The behavior of value and momentum during market crashes lends support to the model mechanism.

Style Timing around the World
Javier Vidal-García (Complutense U. of Madrid) and M. Vidal
April 2022
In this paper we examine whether mutual fund managers around the world are able to implement synchronization strategies with respect to different investment styles, a fundamental aspect in the efficient management of an investment portfolio. We also analyze the skills of these managers to properly select stocks that make up their portfolios. For this purpose, we use a sample of equity mutual funds registered in 35 countries around the world for the 1990-2021 period, for our analysis we employ multifactor and conditional versions of the market timing models of Treynor and Mazuy, and Henriksson and Merton. The results obtained are very similar across countries. We find a correct stock selection and synchronization skills with respect to the book-to-market style and a negative ability to synchronize size and 1-year momentum investment styles.

Risk-based Momentum
Sophia Zhengzi Li (Rutgers University), et al.
March 2022
Based on intraday data for a large cross section of individual stocks, we find that the risk component of stock returns exhibits strong intraday momentum, and this pattern holds from previous market close to 10:00, and every half hour since then until market close at 16:00. Strikingly, the return on the long-short tradable spread portfolio sorted by the risk component exhibits a similar return momentum, which is the first cross-sectional return momentum in the intraday literature. The risk-based momentum effect is strong, generating an annualized return around 40% before transaction cost for a strategy based on last 30-minute to one-day risk with a one-day holding period. The effect lasts up to five days and is stronger in the mornings, during periods with more frequent firm news arrivals, when aggregate idiosyncratic volatility is high, and among stocks with higher risk concentration. The risk-based momentum can be explained by limits to arbitrage that allow arbitrageurs to correct mispricing only gradually.

ESG Momentum in Regional Equity Markets
Yuanfang Ma and Nicholas McLoughlin (HSBC Global Asset Management)
January 2022
This article investigates the use of ESG metrics for asset allocation decisions. We analyse a basic active allocation strategy within regional equity markets, assessing the usefulness of ESG information via two dimensions: the impact on active returns and the predictability of future ESG scores. Our results suggest tilting portfolios on the basis of ESG information can enhance both portfolio returns and future portfolio ESG scores.

A Trend Factor in Commodity Futures Markets: Any Economic Gains From Using Information Over Investment Horizons?
Yufeng Han (U. of North Carolina at Charlotte) and Lingfei Kong
October 2021
This paper identifies a trend factor that exploits the short-, intermediate-, and long-run moving averages of settlement prices in commodity futures markets. The trend factor generates statistically and economically large returns during the post-financialization period 2004-2020. It outperforms the well-known momentum factor by more than nine times the Sharpe ratio and has less downside risk. The trend factor cannot be explained by the existing factor models and is priced cross-sectionally. Finally, we find that the trend factor is correlated with funding liquidity measured by the TED spread. Overall, the results indicate that there are significant economic gains from using the information on historical prices in commodity futures markets.

Skewness Preference, Range-based Expectations, and Stock Market Momentum
Soroush Ghazi and Mark Schneider (University of Alabama)
February 2022
Momentum is a pervasive characteristic of financial markets that lacks a broadly accepted explanation. In addition to its longstanding challenge to asset pricing theory, recent work finds that momentum poses a challenge for expected utility (EU) theory, opening an avenue for new decision theoretic explanations. In this paper, we provide a new decision theoretic and equilibrium foundation for momentum in stock returns. We consider a representative agent who exhibits a disciplined deviation from EU (exhibiting a preference for positively skewed returns), and who exhibits a disciplined deviation from rational expectations (exhibiting range-based expectations in which an asset is expected to trade next period within its price range over the past year). In a general equilibrium setting that generalizes the classical consumption capital asset pricing model, our representative agent economy exhibits momentum in stock returns. Momentum arises from a new mechanism in which the representative agent truncates the tails of the distribution at an asset’s historical trading range. Consequently, a current price near the bottom (top) of the trading range is perceived by the agent as more positively (negatively) skewed, which by skewness preference has lower (higher) subsequent average returns. We conduct a simulation where the agent’s preference parameters are calibrated to prior experimental estimates and show quantitatively that the model generates a sizeable momentum premium as in the data. We further provide an aggregation result in which the same asset prices arise in equilibrium from an economy with some behavioral agents (exhibiting skewness preference) and some traditional EU agents.

Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return

By James Picerno

One thought on “Research Review | 15 April 2022 | Risk Factor Premia

  1. Pingback: Quantocracy's Daily Wrap for 04/18/2022 - Quantocracy

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.