Research Review | 21 DEC 2023 | Portfolio Design & Risk Factors

Factor Zoo (.zip)
Alexander Swade (Lancaster University) et al.
October 2023
The number of factors allegedly driving the cross-section of stock returns has grown steadily over time. We explore how much this ‘factor zoo’ can be compressed, focusing on explaining the available alpha rather than the covariance matrix of factor returns. Our findings indicate that about 15 factors are enough to span the entire factor zoo. This evidence suggests that many factors are redundant but also that merely using a handful of factors, as in common asset pricing models, is insufficient. While the selected factor styles remain persistent, the specific style representatives vary over time, underscoring the importance of continuous factor innovation.

Volatility, dividend yield and stock returns
Seong Jin Ahn (Korea Advanced Institute of Science and Technology, et al.
November 2023
We provide empirical evidence that dividend yield significantly predicts future returns and that excessively volatile prices are the source of this return predictability. In the cross-section, we show dividend yield better predicts returns amongst volatile firms. Inter-temporal analysis shows that yield strategies are highly profitable following periods of heightened volatility, generating approximately 1.5% per month, but insignificantly negative following periods of depressed volatility. During these periods of depressed volatility, dividend yield strategies are more profitable when scaling by stale prices. Our findings differ from prior research, which concludes that dividends are not useful for return prediction, primarily because we include more recent data that includes the past forty years. During this more recent period, the ratio of dividend volatility has been low relative to return volatility, leading dividend strategies to perform relatively well. Cross-sectional tests show that dividend yield better predicts future returns among dividend payers relative to variables from a recent asset pricing model (e.g. Fama and French 2016), consistent with dividend yield being a useful return predictor amongst mature firms that are easier to value.

Inflation news coverage, expectations and risk premium
Daniel Perico Ortiz (University of Erlangen-Nuremberg)
September 2023
This paper investigates the effects of inflation news coverage on market-based inflation expectations and outcomes in the inflation-protected securities market. We employ a large corpus of news headlines from top U.S. newspapers and market data on the U.S. yield curve and inflation-protected securities. Our results indicate that news coverage, particularly regarding specific topics, exerts a significant influence on inflation compensation, expectations, and risk premiums. We observe that the impact of news diminishes as the maturity increases and varies across different news topics. This study contributes to the understanding of media influence on financial markets, specifically in shaping inflation expectations.

Outperforming Equal Weighting
Antonello Cirulli (OLZ AG) and Patrick S. Walker (U. of Zurich)
December 2023
The equally-weighted strategy is a popular benchmark in academic studies to evaluate the merit of optimized portfolios or investment strategies. This naive diversification approach has been shown to outperform many more sophisticated portfolios, despite being trivial in the sense that no computations are required, and thus has also caught the interest of practitioners. We demonstrate that the equally-weighted stock portfolio can be consistently enhanced by avoiding negative exposure to some of the most prominent factor anomalies documented in asset pricing literature. Remarkably, this can be achieved while preserving the simplicity of the portfolio construction process. Specifically, we introduce three simple long-only portfolios that rely solely on historical return data. These portfolios exhibit slight deviations from the equally-weighted strategy, yet they consistently generate significantly higher risk-adjusted returns in realistic out-of-sample assessments. Consequently, our research offers the most straightforward illustrations to challenge the prevailing notion that outperforming the equally-weighted strategy is difficult. Moreover, these findings carry implications for the selection of benchmarks in both academic studies and practical investment management.

Pockets of Factor Pricing
Sophia Zhengzi Li (Rutgers University)
December 2023
Current factor models assume certain pre-specified factors can price or explain asset returns with the same level of ability across time. In contrast with this conventional wisdom, we find that the factor’s pricing ability exhibits notable temporal variations, and it tends to cluster in certain periods referred to as “pockets.” We propose a real-time approach to effectively identify the pockets, and apply it to a comprehensive set of firm characteristics. We find episodic and distinct dynamics of return predictability for different types of characteristics, challenging the notion of continuous presence of the same factors with consistent pricing ability. By leveraging the time-varying predictive power of factors, we construct a composite predictor that achieves a value-weighted hedge return of 3.94% per month with a high t-statistic of 13.87. Furthermore, the composite factor pricing model, which incorporates a selection of factors with factor timing, demonstrates superior effectiveness in both explaining and predicting market anomalies. The factor also provides a comprehensive explanation for factor momentum, which is shown as a consequence of the past performance of factor returns.

Navigating Inflation Risk in Corporate Bond Markets: Evidence from Mutual Funds
Luis Ceballos (U. of San Diego) and Han Xiao (Chinese University of Hong Kong)
November 15, 2023
The global inflation surge has refocused attention on the impact of inflation risks. We investigate whether mutual fund managers time the inflation risks in the corporate bond market. Our findings reveal a significant and robust timing ability among managers in different investment subcategories, translating into a sizable fund performance of around 4% per annum. Timing is associated with managers adjusting portfolio holdings to bet on future risks rather than past realizations. Cross-sectional evidence suggests that over 40% individual funds exhibit strong inflation risk timing ability, controlling alternative timing abilities, factor structures, and monetary policy shocks. The bootstrapping exercise further validates managerial skills rather than pure luck. Our results provide policy implications for monetary policy transmission in corporate bond markets.

Momentum, Bubble and Information Transmission
Yu Yan (Peking University), et al.
November 2023
We propose a continuous-time model of investors with heterogeneous beliefs and incomplete information to integrate the momentum effect, reversal effect and the bubble into a unified framework. Our model demonstrates that the slow transmission of correct information leads to the momentum effect, while the slow transmission of a rumor leads to the reversal effect and bubble phenomenon. The results of numerical simulations reveal that the model generates a pattern in the prices of risky assets characterized by short-term momentum and long-term reversal. An increase in the information transmission speed is found to enhance the short-term momentum effect while reducing the mid-term momentum effect.

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

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