Final Report Summary - ASSETPRICINGPUZZLES (Cross Sectional Asset Pricing Puzzles: An Equilibrium Perspective)
This original research agenda aimed to proposes an inter-temporal asset pricing model featuring a formal cross section of firms characterized by mean-reverting expected dividend growth. There is indeed considerable empirical support for the cross-sectional implications of the model, as cash flow- and return-based measures of long-run risk exposure are both positively related to returns and offer a potential explanation for the size, value, and momentum effects in stock returns. Interestingly, the model implies a negative relation between average returns and exposures to systematic and firm-specific risks in the cross section. Higher cash-flow duration firms exhibit higher exposure to economic growth shocks while they are less sensitive to firm-specific news. Such firms command higher risk premiums but exhibit lower analyst forecast dispersion, idiosyncratic volatility, and distress risk. Overall, market anomalies are not at odds with rational asset pricing.
A follow up works explores commonalities across asset-pricing anomalies. In particular, it assesses implications of financial distress for the profitability of a comprehensive list of anomaly-based trading strategies. The evidence shows that strategies based on price momentum, earnings momentum, credit risk, dispersion, idiosyncratic volatility, and capital investments derive their profitability from taking short positions in high credit risk firms that experience deteriorating credit conditions. Such distressed firms are highly illiquid and hard to short sell, which could establish nontrivial hurdles for exploiting anomalies in real time. The value effect emerges from taking long positions in high credit risk firms that survive financial distress and subsequently realize high returns. The accruals anomaly is an exception - it is robust amongst high and low credit risk firms as well as during periods of deteriorating, stable, and improving credit conditions. This project got published in the Journal of Financial Economics and won the Fama-DFA best paper award. It also won the best paper award at the FMA meetings (Asia).
While the past two projects explore domestic (US) asset pricing models, I also examine international asset pricing. Indeed, up to date global asset-pricing models have failed to capture the cross section of average country equity returns. Emerging markets have displayed strikingly large and robust positive pricing errors. Country-level characteristics have played a significant role in pricing international equities, suggesting that financial markets may not be fully integrated. This project offers a risk-based explanation that resolves such deviations from global asset pricing. A world credit risk factor fully explains the positive pricing errors in emerging market equities. Moreover, in the presence of this credit risk factor, country-level characteristics no longer play a role in pricing global equities. Factor models that account for the world credit risk factor uniformly outperform competing specifications, in both the time-series and cross-section, which exclude this factor. Over the 1989-2009 period, the risk premium for systematic credit risk exposure is 83 basis points per month and its importance has increased dramatically in recent years. This paper won the best paper award at the Review of Asset Pricing Studies – a Journal affiliated with the Review of Financial Studies.
This original research agenda –the one that promotes an inter-temporal asset pricing model - is then used for asset allocation purposes. Indeed, in a follow up research paper proposes a structural approach to long-horizon asset allocation. In particular, the investor draws inferences about asset returns from a vector auto-regression (VAR) with economic restrictions on the intercept, slope, and covariance matrix implied by rational asset pricing. Thus far, published papers in economics and finance journals have analysed asset allocation using a reduced form approach. Comparing the optimal allocations of investors using the long run risk VAR versus an unrestricted reduced-form VAR reveals stark differences in portfolio strategies. Investors using structural models are quite conservative relative to their reduced-form counterparts due to inter-temporal hedging concerns. Despite the differing strategies, both investors achieve success in timing the market. The gains of the long-run risk investor appear to arise from his ability to avoid exposure to large negative events, while the reduced-form investor better capitalizes on periods of high average returns.
I have also used the economic setup described above to develop a simple dividend discount model in which to resolve the conflicting evidence of a large negative (Ang, Hodrick, Xing, and Zhang (AHXZ, 2006)) versus large positive (Fu (2009)) relation between idiosyncratic volatility (IVOL) and average returns. In the proposed model, IVOL strongly predicts the cross section of average returns, even when it is unpriced. That predictive ability is attributable to the relations of IVOL with dividend size and expected dividend growth, both of which are related to risk premiums. In particular, firms with small dividends exhibit high IVOL and high expected returns, while low dividend growth firms have high IVOL and low expected returns. Empirical evidence strongly supports the model’s novel prediction of a negative relation between IVOL and firm growth. Moreover, consistent with model predictions, IVOL is positively related to returns in the dividend size dimension and negatively along the dividend growth dimension. Finally, the AHXZ and Fu measures are more closely aligned with dividend growth and dividend size, respectively, consistent with their opposing relations with IVOL.
Finally, I have also taken the anomaly literature into mutual funds, hedge funds, and options. In particular, I have currently been working on three independent working papers with different co-authors aiming to exploit the asset pricing anomaly based literature into predicting mutual fund performance, hedge fund performance, and strategies involving call and put options. Here is a brief description. I take 11 anomalies and give each stock a rank based on the anomaly. I then average the sore across 11 anomalies to get a measure at the stock level of stock overpricing. This measure is then used in three different studies. The first attempts to understand performance of mutual fund managers. The second attempts to understand performance of hedge fund managers. The third attempts to detect mispricing in put and call options. All these projects are under construction and I believe they have good odds of publication.
A follow up works explores commonalities across asset-pricing anomalies. In particular, it assesses implications of financial distress for the profitability of a comprehensive list of anomaly-based trading strategies. The evidence shows that strategies based on price momentum, earnings momentum, credit risk, dispersion, idiosyncratic volatility, and capital investments derive their profitability from taking short positions in high credit risk firms that experience deteriorating credit conditions. Such distressed firms are highly illiquid and hard to short sell, which could establish nontrivial hurdles for exploiting anomalies in real time. The value effect emerges from taking long positions in high credit risk firms that survive financial distress and subsequently realize high returns. The accruals anomaly is an exception - it is robust amongst high and low credit risk firms as well as during periods of deteriorating, stable, and improving credit conditions. This project got published in the Journal of Financial Economics and won the Fama-DFA best paper award. It also won the best paper award at the FMA meetings (Asia).
While the past two projects explore domestic (US) asset pricing models, I also examine international asset pricing. Indeed, up to date global asset-pricing models have failed to capture the cross section of average country equity returns. Emerging markets have displayed strikingly large and robust positive pricing errors. Country-level characteristics have played a significant role in pricing international equities, suggesting that financial markets may not be fully integrated. This project offers a risk-based explanation that resolves such deviations from global asset pricing. A world credit risk factor fully explains the positive pricing errors in emerging market equities. Moreover, in the presence of this credit risk factor, country-level characteristics no longer play a role in pricing global equities. Factor models that account for the world credit risk factor uniformly outperform competing specifications, in both the time-series and cross-section, which exclude this factor. Over the 1989-2009 period, the risk premium for systematic credit risk exposure is 83 basis points per month and its importance has increased dramatically in recent years. This paper won the best paper award at the Review of Asset Pricing Studies – a Journal affiliated with the Review of Financial Studies.
This original research agenda –the one that promotes an inter-temporal asset pricing model - is then used for asset allocation purposes. Indeed, in a follow up research paper proposes a structural approach to long-horizon asset allocation. In particular, the investor draws inferences about asset returns from a vector auto-regression (VAR) with economic restrictions on the intercept, slope, and covariance matrix implied by rational asset pricing. Thus far, published papers in economics and finance journals have analysed asset allocation using a reduced form approach. Comparing the optimal allocations of investors using the long run risk VAR versus an unrestricted reduced-form VAR reveals stark differences in portfolio strategies. Investors using structural models are quite conservative relative to their reduced-form counterparts due to inter-temporal hedging concerns. Despite the differing strategies, both investors achieve success in timing the market. The gains of the long-run risk investor appear to arise from his ability to avoid exposure to large negative events, while the reduced-form investor better capitalizes on periods of high average returns.
I have also used the economic setup described above to develop a simple dividend discount model in which to resolve the conflicting evidence of a large negative (Ang, Hodrick, Xing, and Zhang (AHXZ, 2006)) versus large positive (Fu (2009)) relation between idiosyncratic volatility (IVOL) and average returns. In the proposed model, IVOL strongly predicts the cross section of average returns, even when it is unpriced. That predictive ability is attributable to the relations of IVOL with dividend size and expected dividend growth, both of which are related to risk premiums. In particular, firms with small dividends exhibit high IVOL and high expected returns, while low dividend growth firms have high IVOL and low expected returns. Empirical evidence strongly supports the model’s novel prediction of a negative relation between IVOL and firm growth. Moreover, consistent with model predictions, IVOL is positively related to returns in the dividend size dimension and negatively along the dividend growth dimension. Finally, the AHXZ and Fu measures are more closely aligned with dividend growth and dividend size, respectively, consistent with their opposing relations with IVOL.
Finally, I have also taken the anomaly literature into mutual funds, hedge funds, and options. In particular, I have currently been working on three independent working papers with different co-authors aiming to exploit the asset pricing anomaly based literature into predicting mutual fund performance, hedge fund performance, and strategies involving call and put options. Here is a brief description. I take 11 anomalies and give each stock a rank based on the anomaly. I then average the sore across 11 anomalies to get a measure at the stock level of stock overpricing. This measure is then used in three different studies. The first attempts to understand performance of mutual fund managers. The second attempts to understand performance of hedge fund managers. The third attempts to detect mispricing in put and call options. All these projects are under construction and I believe they have good odds of publication.