Abstract The value effect and the idiosyncratic volatility (IVol) discount arise because growth firms and high IVol firms beat the CAPM during periods of increasing aggregate volatility (market volatility and average IVol), that makes their risk low. All else equal, growth options’ value increases with volatility, an effect that is stronger for high IVol firms, for which growth options take a larger fraction of the firm value and firm volatility responds more to aggregate volatility changes. The factor model with the market factor, the market volatility risk factor, and the average IVol factor explains the value effect and the IVol discount. (JEL G12, G13, E44) Received August 5, 2021; editorial decision February 7, 2023 by Editor Hui Chen. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns","authors":"Alexander Barinov, Georgy Chabakauri","doi":"10.1093/rapstu/raad006","DOIUrl":"https://doi.org/10.1093/rapstu/raad006","url":null,"abstract":"Abstract The value effect and the idiosyncratic volatility (IVol) discount arise because growth firms and high IVol firms beat the CAPM during periods of increasing aggregate volatility (market volatility and average IVol), that makes their risk low. All else equal, growth options’ value increases with volatility, an effect that is stronger for high IVol firms, for which growth options take a larger fraction of the firm value and firm volatility responds more to aggregate volatility changes. The factor model with the market factor, the market volatility risk factor, and the average IVol factor explains the value effect and the IVol discount. (JEL G12, G13, E44) Received August 5, 2021; editorial decision February 7, 2023 by Editor Hui Chen. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136329585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a dynamic equilibrium model with stochastic interest rates in which agents hold heterogeneous valuations for the same asset and take on positions against each other. The model shows that interest rate uncertainty and investor heterogeneity are key determinants of price dispersion. Higher search intensity reduces price dispersion, while raising volume, leading to a negative volatility-volume relation. The sensitivity of volatility to volume is high when liquidity is low, interest rate variations are high and investors' valuations are more heterogeneous. Evidence supports our model's predictions and shows that search frictions play an important role in driving the volatility-volume relation.
{"title":"Stochastic Interest Rates, Heterogeneous Valuations, and the Volatility-Volume Relation with Search Frictions","authors":"Sheen X. Liu, Junbo Wang, Chunchi Wu","doi":"10.1093/rapstu/raad004","DOIUrl":"https://doi.org/10.1093/rapstu/raad004","url":null,"abstract":"\u0000 We propose a dynamic equilibrium model with stochastic interest rates in which agents hold heterogeneous valuations for the same asset and take on positions against each other. The model shows that interest rate uncertainty and investor heterogeneity are key determinants of price dispersion. Higher search intensity reduces price dispersion, while raising volume, leading to a negative volatility-volume relation. The sensitivity of volatility to volume is high when liquidity is low, interest rate variations are high and investors' valuations are more heterogeneous. Evidence supports our model's predictions and shows that search frictions play an important role in driving the volatility-volume relation.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76215032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Factors related to carry, duration, equity momentum, and the term structure are the most important risk factors in corporate bond markets. From a large set of factor candidates, we condense an optimal model with a two-step approach. First, we filter out factors that do not systematically move bond prices. Second, we use a Bayesian model selection approach to determine the optimal, parsimonious model. Many prominent factors do not move prices or are redundant. We document the new model’s good performance compared to that of existing models in time-series and cross-sectional tests and analyze the economic drivers of the factors. (JEL G12, C11, C52)
{"title":"Which Factors for Corporate Bond Returns?","authors":"Thuy Duong Dang, Fabian Hollstein, Marcel Prokopczuk","doi":"10.1093/rapstu/raad005","DOIUrl":"https://doi.org/10.1093/rapstu/raad005","url":null,"abstract":"Abstract Factors related to carry, duration, equity momentum, and the term structure are the most important risk factors in corporate bond markets. From a large set of factor candidates, we condense an optimal model with a two-step approach. First, we filter out factors that do not systematically move bond prices. Second, we use a Bayesian model selection approach to determine the optimal, parsimonious model. Many prominent factors do not move prices or are redundant. We document the new model’s good performance compared to that of existing models in time-series and cross-sectional tests and analyze the economic drivers of the factors. (JEL G12, C11, C52)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136174814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract When brokers, analysts, and fund managers buy or sell stocks for their own accounts, these “access employees” of financial institutions outperform retail investors over short windows up to a month. They earn particularly high abnormal returns when they trade before earnings announcements, revisions of analyst recommendations, and large stock price changes. We also find evidence consistent with profitable front-running and information leakage around the execution of corporate insider trades and block trades by mutual funds, as well as the release of revised recommendations by analysts who work at the same brokerage firm. (JEL G12, G14, G18) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"The Other Insiders: Personal Trading by Brokers, Analysts, and Fund Managers","authors":"Henk Berkman, Paul Koch, P Joakim Westerholm","doi":"10.1093/rapstu/raad002","DOIUrl":"https://doi.org/10.1093/rapstu/raad002","url":null,"abstract":"Abstract When brokers, analysts, and fund managers buy or sell stocks for their own accounts, these “access employees” of financial institutions outperform retail investors over short windows up to a month. They earn particularly high abnormal returns when they trade before earnings announcements, revisions of analyst recommendations, and large stock price changes. We also find evidence consistent with profitable front-running and information leakage around the execution of corporate insider trades and block trades by mutual funds, as well as the release of revised recommendations by analysts who work at the same brokerage firm. (JEL G12, G14, G18) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135727307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Classic option pricing theory values a derivative contract via dynamic delta hedging and treating the contract as redundant relative to the underlying security. Dynamic delta hedging proves highly effective in practice, but the remaining risk is still large because of the practical limits of arbitrage. Derivatives can play primary roles in risk allocation. This paper quantifies the percentage variance reduction of delta hedging on U.S. stock options, proposes a top-down return attribution framework to identify the remaining risk sources of the delta-hedged option investment, and constructs a statistical return factor model to explain the variations of the delta-hedged option returns. (JEL C13, C51, G12, G13)
{"title":"Limits of Arbitrage and Primary Risk-Taking in Derivative Securities","authors":"Meng Tian, Liuren Wu","doi":"10.1093/rapstu/raad003","DOIUrl":"https://doi.org/10.1093/rapstu/raad003","url":null,"abstract":"Abstract Classic option pricing theory values a derivative contract via dynamic delta hedging and treating the contract as redundant relative to the underlying security. Dynamic delta hedging proves highly effective in practice, but the remaining risk is still large because of the practical limits of arbitrage. Derivatives can play primary roles in risk allocation. This paper quantifies the percentage variance reduction of delta hedging on U.S. stock options, proposes a top-down return attribution framework to identify the remaining risk sources of the delta-hedged option investment, and constructs a statistical return factor model to explain the variations of the delta-hedged option returns. (JEL C13, C51, G12, G13)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135727306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This paper explores the impact of product market competition on the positive relation between labor mobility (LM) and future returns. We develop a production-based model and formalize the intuition that low exposure to systematic risk in a concentrated industry limits LM’s amplifying effect on operating leverage. Therefore, the model predicts a stronger positive relation between LM and expected returns for firms in competitive industries. Consistent with the model’s prediction, we empirically find that LM predicts returns only among firms in competitive industries. This evidence suggests that the intensity of competition in firms’ product market potentially drives the positive LM-return relation. (JEL G12, G14, J69) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"Product Market Competition, Labor Mobility, and the Cross-Section of Stock Returns","authors":"Shamim Ahmed, Ziwen Bu, Xiaoxia Ye","doi":"10.1093/rapstu/raad001","DOIUrl":"https://doi.org/10.1093/rapstu/raad001","url":null,"abstract":"Abstract This paper explores the impact of product market competition on the positive relation between labor mobility (LM) and future returns. We develop a production-based model and formalize the intuition that low exposure to systematic risk in a concentrated industry limits LM’s amplifying effect on operating leverage. Therefore, the model predicts a stronger positive relation between LM and expected returns for firms in competitive industries. Consistent with the model’s prediction, we empirically find that LM predicts returns only among firms in competitive industries. This evidence suggests that the intensity of competition in firms’ product market potentially drives the positive LM-return relation. (JEL G12, G14, J69) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136378272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a naïve model averaging (NMA) method that averages the OLS out-of-sample forecasts and the historical means and produces mostly positive out-of-sample R2s for the variables significant in sample in forecasting market returns. Surprisingly, more sophisticated weighting schemes that combine the predictive variable and historical mean do not consistently perform better. With unstable economic relations and a limited sample size, sophisticated methods may lead to overfitting or be subject to more estimation errors. In such situations, our simple methods may work better. Model misspecification, rather than declining return predictability, likely explains the predictive performance of the NMA method.
{"title":"Predicting Returns Out of Sample: A Naïve Model Averaging Approach","authors":"Huafeng (Jason) Chen, Liang Jiang, Weiwei Liu","doi":"10.1093/rapstu/raac021","DOIUrl":"https://doi.org/10.1093/rapstu/raac021","url":null,"abstract":"We propose a naïve model averaging (NMA) method that averages the OLS out-of-sample forecasts and the historical means and produces mostly positive out-of-sample R2s for the variables significant in sample in forecasting market returns. Surprisingly, more sophisticated weighting schemes that combine the predictive variable and historical mean do not consistently perform better. With unstable economic relations and a limited sample size, sophisticated methods may lead to overfitting or be subject to more estimation errors. In such situations, our simple methods may work better. Model misspecification, rather than declining return predictability, likely explains the predictive performance of the NMA method.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The distribution of long-run compound returns to portfolio strategies is greatly affected by periodic rebalancing. Over time, buy-and-hold portfolios gradually lose diversification as extreme long-run skewness in individual stock returns leads to increasingly concentrated holdings. For long investment horizons, small rebalanced portfolios holding only a fraction of all stocks therefore achieve better diversification than much larger marketwide buy-and-hold portfolios. Consequently, over long horizons, rebalanced portfolios tend to outperform buy-and-hold portfolios, and risk-averse investors prefer the former. Empirical results strongly support the theoretical predictions and add further evidence to the strong empirical performance of (small) equal-weighted portfolios.
{"title":"Small Rebalanced Portfolios Often Beat the Market over Long Horizons","authors":"Ádám Faragó, Erik Hjalmarsson","doi":"10.1093/rapstu/raac020","DOIUrl":"https://doi.org/10.1093/rapstu/raac020","url":null,"abstract":"\u0000 The distribution of long-run compound returns to portfolio strategies is greatly affected by periodic rebalancing. Over time, buy-and-hold portfolios gradually lose diversification as extreme long-run skewness in individual stock returns leads to increasingly concentrated holdings. For long investment horizons, small rebalanced portfolios holding only a fraction of all stocks therefore achieve better diversification than much larger marketwide buy-and-hold portfolios. Consequently, over long horizons, rebalanced portfolios tend to outperform buy-and-hold portfolios, and risk-averse investors prefer the former. Empirical results strongly support the theoretical predictions and add further evidence to the strong empirical performance of (small) equal-weighted portfolios.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73188251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In contrast with theoretical predictions, high-fee active equity funds generate worse net-of-expenses performance. We show that this fee-performance puzzle is driven by the preference of high-fee funds for stocks with low operating profitability and high investment rates, characteristics associated with low expected returns. After controlling for exposures to profitability and investment factors, we find high-fee funds significantly outperform low-fee funds before expenses and achieve similarly poor net-of-fees performance. In resolving the fee-performance puzzle, our findings provide support to the theoretical prediction that net alphas are unrelated to fees and challenge the common advice to prefer low-fee funds over high-fee counterparts.
{"title":"Cheaper Is Not Better: On the ‘Superior’ Performance of High-Fee Mutual Funds","authors":"Jinfei Sheng, Mikhail Simutin, Terry Zhang","doi":"10.1093/rapstu/raac019","DOIUrl":"https://doi.org/10.1093/rapstu/raac019","url":null,"abstract":"In contrast with theoretical predictions, high-fee active equity funds generate worse net-of-expenses performance. We show that this fee-performance puzzle is driven by the preference of high-fee funds for stocks with low operating profitability and high investment rates, characteristics associated with low expected returns. After controlling for exposures to profitability and investment factors, we find high-fee funds significantly outperform low-fee funds before expenses and achieve similarly poor net-of-fees performance. In resolving the fee-performance puzzle, our findings provide support to the theoretical prediction that net alphas are unrelated to fees and challenge the common advice to prefer low-fee funds over high-fee counterparts.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We perform portfolio-level analyses to understand insurance firms’ preferred habitat behavior in the government bond market. Based on portfolio durations and portfolio weights across maturities, we find that interest rate risk exposures of insurers’ portfolios are related to their operating liabilities and financing constraints. We show that this habitat behavior significantly affects bond pricing. During the “quantitative easing” era, bond purchases by the Federal Reserve have a larger impact on the yields of Treasury bonds with a higher habitat demand.
{"title":"In Search of Habitat","authors":"Xuanjuan Chen, Zhenzhen Sun, Tong Yao, Tong Yu","doi":"10.1093/rapstu/raac018","DOIUrl":"https://doi.org/10.1093/rapstu/raac018","url":null,"abstract":"We perform portfolio-level analyses to understand insurance firms’ preferred habitat behavior in the government bond market. Based on portfolio durations and portfolio weights across maturities, we find that interest rate risk exposures of insurers’ portfolios are related to their operating liabilities and financing constraints. We show that this habitat behavior significantly affects bond pricing. During the “quantitative easing” era, bond purchases by the Federal Reserve have a larger impact on the yields of Treasury bonds with a higher habitat demand.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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