Time-Series Efficient Factors (with Juhani Linnainmaa)

R&R, Journal of Financial Economics

WFA 2021, SFS Cavalcade 2021, AFA 2021

Factors in popular asset pricing models are unconditionally minimum-variance inefficient. We turn factors ``time-series efficient'' by implementing momentum- and volatility-management programs. These factors achieve 64% higher Sharpe ratios than the original factors, span them, and significantly improve the pricing of the factor zoo. Momentum strategies' profits relate to factor inefficiency. Whereas the standard five-factor model does nothing to the momentum factor, the efficient version subsumes it. The time-series efficiency program may add value by disentangling risk factors' priced and unpriced components.

Replication Code: Out-of-sample time-series efficient factors Link 

Correcting Asset Pricing Models (with Juhani Linnainmaa)

A betting-against-beta portfolio is the optimal adjustment for the flatness of any one factor's security factor line. A portfolio sorted on the intercepts of a multi-factor model (the invisible portfolio) is a theoretically founded adjustment for all such distortions. Augmenting the Fama-French five factor model with its invisible portfolio stabilizes optimal factor allocations, increases the model's out-of-sample Sharpe ratio, increases its explanatory power, and lowers its pricing error in asset pricing tests. 

What Does Residual Momentum Tell Us About Firm-Specific Momentum? (with Juhani Linnainmaa)

AFA 2023

Residual momentum strategies earn significant alphas. The common interpretation for this result - that momentum resides in firm-specific returns - is unwarranted: even in the absence of firm-specific momentum, a strategy sorted on residuals is profitable because it is also a bet against betas. A UMD-like factor that removes these bets to capture true firm-specific momentum earns an alpha of 63 basis points per month (t-value = 9.20). Firm-specific momentum strategies, unlike residual momentum strategies, are almost uncorrelated across regions. Our results indicate that there was a strong firm-specific momentum effect in stock returns until 2002, after which it has been almost fully arbitraged away. 

The Factor Risk in Low-Risk Anomalies 

The low variance strategy always bets against the volatile leg of common factor-portfolios. The factor exposure of the strategy is perfectly predictable based on the status of factor portfolio variances during the formation period. I find that the strategy earns alpha only when traders have to bear major factor risk to arbitrage it away. This result is consistent with a risk based story: arbitrageurs are reluctant to eliminate mispricing when factor risk is high. I study the sources of risk and return to well-known volatility trading strategies within this framework.

Is Sector-Neutrality in Factor Investing a Mistake? (with Cam Harvey and Feifei Li)

Financial Analyst Journal, 2023

A characteristic might be valuable in identifying high or low expected returns across industries or it might be useful in identifying individual stock expected returns within an industry. Past studies generally find that the firm-specific component is the strongest predictor, leading many to sector neutralize their factor exposures. We show that this problem is equivalent to the classic two risky-asset problem and derive the condition that decides when the sector component of a characteristic should be omitted. The long–short investor is more likely to benefit from hedging out sector bets, whereas the long-only investor is more likely to benefit from investing in the factor as it stands. 

Compensated and Uncompensated Risks In Global Factor Investing  (with Michael Hunstad and Manan Mehta)

Long-short global equity risk factors contain embedded region and sector exposures. We show that hedging out both region and sector exposures simultaneously increases the Sharpe ratio of the typical long-short global factor by 50%. Hedged factors, individually or in a model, always subsume their non-hedged counterparts.