This paper investigates the influence of global equity market value shocks on institutional investors’ (IIs’) hedging behavior and the resultant effects on exchange rates. Employing unique granular daily data on Israeli IIs’ foreign exchange (FX) forward flows and prices and a granular instrumental variable estimation approach, we find that foreign equity market value shocks generate significant selling of U.S. dollar forwards by IIs, as a hedge against heightened FX exposure, along with significant exchange rate appreciation. A value-shock-induced one-standard-deviation increase in IIs’ supply of forward flows appreciates IIs’ forward rate by 0.53%. (JEL E44, F3, F31, G15, G23)
{"title":"Shorting the Dollar When Global Stock Markets Roar: The Equity Hedging Channel of Exchange Rate Determination","authors":"Nadav Ben Zeev, Daniel Nathan","doi":"10.1093/rapstu/raae012","DOIUrl":"https://doi.org/10.1093/rapstu/raae012","url":null,"abstract":"This paper investigates the influence of global equity market value shocks on institutional investors’ (IIs’) hedging behavior and the resultant effects on exchange rates. Employing unique granular daily data on Israeli IIs’ foreign exchange (FX) forward flows and prices and a granular instrumental variable estimation approach, we find that foreign equity market value shocks generate significant selling of U.S. dollar forwards by IIs, as a hedge against heightened FX exposure, along with significant exchange rate appreciation. A value-shock-induced one-standard-deviation increase in IIs’ supply of forward flows appreciates IIs’ forward rate by 0.53%. (JEL E44, F3, F31, G15, G23)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"27 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196601","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}
Given the complex and controversial nature of short-selling regulation, we review the academic literature and provide insights for policy makers and academics. We organize the complex history of short-selling regulation into three areas: trading restrictions, securities lending regulations, and disclosure requirements. We identify, analyze, and discuss 45 distinct regulations promulgated from 1896 to 2021, primarily by reviewing the academic literature and the data sources employed. We provide several insights regarding the effectiveness of regulatory approaches and the wider impact of short-selling regulation on markets. (JEL G2, G12, G14, G15, G34)
{"title":"A Survey of Short-Selling Regulations","authors":"Amy K Edwards, Adam V Reed, Pedro A C Saffi","doi":"10.1093/rapstu/raae011","DOIUrl":"https://doi.org/10.1093/rapstu/raae011","url":null,"abstract":"Given the complex and controversial nature of short-selling regulation, we review the academic literature and provide insights for policy makers and academics. We organize the complex history of short-selling regulation into three areas: trading restrictions, securities lending regulations, and disclosure requirements. We identify, analyze, and discuss 45 distinct regulations promulgated from 1896 to 2021, primarily by reviewing the academic literature and the data sources employed. We provide several insights regarding the effectiveness of regulatory approaches and the wider impact of short-selling regulation on markets. (JEL G2, G12, G14, G15, G34)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"9 13 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196628","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}
This paper revisits the relation between systematic skewness and returns, showing two main findings. First, the systematic skewness premium in individual stocks is time varying. When either skewness preference or systematic skewness is above rather than below the median, the premium is 4% higher. The combined effect of the two induces time variation in the premium of about 7%. Second, systematic skewness has significant additional explanatory power in explaining returns relative to most common characteristics, except size and momentum. These two results imply that skewness preference is an important determinant of expected returns providing a possible rationale for size and momentum. (JEL G11, G12)
{"title":"Systematic Skewness and Stock Returns","authors":"Paul Karehnke","doi":"10.1093/rapstu/raae010","DOIUrl":"https://doi.org/10.1093/rapstu/raae010","url":null,"abstract":"This paper revisits the relation between systematic skewness and returns, showing two main findings. First, the systematic skewness premium in individual stocks is time varying. When either skewness preference or systematic skewness is above rather than below the median, the premium is 4% higher. The combined effect of the two induces time variation in the premium of about 7%. Second, systematic skewness has significant additional explanatory power in explaining returns relative to most common characteristics, except size and momentum. These two results imply that skewness preference is an important determinant of expected returns providing a possible rationale for size and momentum. (JEL G11, G12)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"41 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141502708","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}
This paper proposes a novel approach to estimating the probability weighting function (PWF) of investors in the option market. We match observed option prices to the option pricing bounds under stochastic dominance rules. Using 1-month S&P 500 index option data, we find that investors could subjectively employ an inverse S-shaped probability weighting function, which increases the weights on extreme returns and asymmetrically assigns greater weights to extremely low returns than to extremely high returns. Our findings suggest that the inverse S-shaped nature of the PWFs is robust across various estimation specifications, such as adopting an alternative methodology to construct the return distribution, and employing option data with different times to maturity. (JEL G12)
本文提出了一种估算期权市场投资者概率加权函数（PWF）的新方法。我们将观察到的期权价格与随机支配规则下的期权定价边界相匹配。通过使用 1 个月的 S&P 500 指数期权数据，我们发现投资者可以主观地使用反 S 型概率加权函数，该函数增加了极端收益的权重，并不对称地赋予极低收益比极高收益更大的权重。我们的研究结果表明，逆 S 型概率加权函数的性质在不同的估计规格下都是稳健的，例如采用另一种方法来构建回报率分布，以及采用不同到期时间的期权数据。(JEL G12)
{"title":"Estimating Probability Weighting Functions through Option Pricing Bounds","authors":"Tzu-Ying Chen, Yo-Lan Lin, Larry Y Tzeng","doi":"10.1093/rapstu/raae008","DOIUrl":"https://doi.org/10.1093/rapstu/raae008","url":null,"abstract":"This paper proposes a novel approach to estimating the probability weighting function (PWF) of investors in the option market. We match observed option prices to the option pricing bounds under stochastic dominance rules. Using 1-month S&P 500 index option data, we find that investors could subjectively employ an inverse S-shaped probability weighting function, which increases the weights on extreme returns and asymmetrically assigns greater weights to extremely low returns than to extremely high returns. Our findings suggest that the inverse S-shaped nature of the PWFs is robust across various estimation specifications, such as adopting an alternative methodology to construct the return distribution, and employing option data with different times to maturity. (JEL G12)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"48 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140812955","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}
This paper reappraises the usefulness of combining individual forecasts for predicting the U.S. equity premium. For comparison, we also consider penalized regression and dimension reduction approaches. We fail to find evidence of predictive ability in recent decades, regardless of the forecasting method used. Further analysis shows that an increase in the correlation of individual forecast errors is an important factor in the declining performance of combination forecasts. (JEL C53, G12, G17)
{"title":"Predicting the Equity Premium with Combination Forecasts: A Reappraisal","authors":"Sebastian Denk, Gunter Löffler","doi":"10.1093/rapstu/raae009","DOIUrl":"https://doi.org/10.1093/rapstu/raae009","url":null,"abstract":"This paper reappraises the usefulness of combining individual forecasts for predicting the U.S. equity premium. For comparison, we also consider penalized regression and dimension reduction approaches. We fail to find evidence of predictive ability in recent decades, regardless of the forecasting method used. Further analysis shows that an increase in the correlation of individual forecast errors is an important factor in the declining performance of combination forecasts. (JEL C53, G12, G17)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"109 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140573254","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 implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function. (JEL L200; C110; C350)
{"title":"An Empirical Assessment of Characteristics and Optimal Portfolios","authors":"Christopher G Lamoureux, Huacheng Zhang","doi":"10.1093/rapstu/raae006","DOIUrl":"https://doi.org/10.1093/rapstu/raae006","url":null,"abstract":"We implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function. (JEL L200; C110; C350)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"13 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168122","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}
This paper highlights a positive and significant beta-return relationship in high expected market return states, as suggested by the ICAPM. The ICAPM has strong out-of-sample predictive power for equity returns. As a result, timing strategies exploiting this predictive power have Sharpe ratios about double those of the buy-and-hold strategies, alphas of about 5% per annum, and average returns increasing sharply with unconditional betas. Our findings relate to the positive beta-return relation uncovered overnight, on macroeconomic announcement days, and in low inflation times because these periods share an important common feature: high market returns. (JEL D53, G11, G12)
{"title":"Equity Return Predictability with the ICAPM","authors":"Michael Hasler, Charles Martineau","doi":"10.1093/rapstu/raae007","DOIUrl":"https://doi.org/10.1093/rapstu/raae007","url":null,"abstract":"This paper highlights a positive and significant beta-return relationship in high expected market return states, as suggested by the ICAPM. The ICAPM has strong out-of-sample predictive power for equity returns. As a result, timing strategies exploiting this predictive power have Sharpe ratios about double those of the buy-and-hold strategies, alphas of about 5% per annum, and average returns increasing sharply with unconditional betas. Our findings relate to the positive beta-return relation uncovered overnight, on macroeconomic announcement days, and in low inflation times because these periods share an important common feature: high market returns. (JEL D53, G11, G12)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"91 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155313","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}
Using contingent-claims valuation, we introduce novel hedge ratios for credit exposures using put options. Option hedge ratios are generally in line with the empirical sensitivities of credit spread changes to put option returns and, relative to stock hedge ratios, produce further reductions in volatility for a portfolio of North American firms. We show that option hedge ratios capture option-specific credit exposure related to the VIX index and the default spread, which is unaccounted for by Merton’s (1974) equity hedge ratios alone. Combining stocks and put options for credit risk hedging can be done effectively using the volatility smirk. (JEL E43, E44, G10)
{"title":"Contingent Claims and Hedging of Credit Risk with Equity Options","authors":"Davide E Avino, Enrique Salvador","doi":"10.1093/rapstu/raae005","DOIUrl":"https://doi.org/10.1093/rapstu/raae005","url":null,"abstract":"Using contingent-claims valuation, we introduce novel hedge ratios for credit exposures using put options. Option hedge ratios are generally in line with the empirical sensitivities of credit spread changes to put option returns and, relative to stock hedge ratios, produce further reductions in volatility for a portfolio of North American firms. We show that option hedge ratios capture option-specific credit exposure related to the VIX index and the default spread, which is unaccounted for by Merton’s (1974) equity hedge ratios alone. Combining stocks and put options for credit risk hedging can be done effectively using the volatility smirk. (JEL E43, E44, G10)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"86 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140097401","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}
Regulations introduce significant fixed costs and add to operating leverage. Fixed regulatory costs that contribute to operating leverage should generate a risk premium. To explore whether such a premium exists, we introduce a measure of “regulatory operating leverage” that reflects the importance of fixed regulatory costs in a firm’s cost structure. Regulatory operating leverage predicts stock returns in the cross-section, and a zero-cost high-low regulatory operating leverage strategy generates positive and significant risk-adjusted return. Finally, the impact of regulatory operating leverage on returns is due to the (systematic) risk contribution of fixed regulatory costs. (JEL G12, G18, G28)
{"title":"Price of Regulations: Regulatory Costs and the Cross-section of Stock Returns","authors":"Baris Ince, Han Ozsoylev","doi":"10.1093/rapstu/raae001","DOIUrl":"https://doi.org/10.1093/rapstu/raae001","url":null,"abstract":"Regulations introduce significant fixed costs and add to operating leverage. Fixed regulatory costs that contribute to operating leverage should generate a risk premium. To explore whether such a premium exists, we introduce a measure of “regulatory operating leverage” that reflects the importance of fixed regulatory costs in a firm’s cost structure. Regulatory operating leverage predicts stock returns in the cross-section, and a zero-cost high-low regulatory operating leverage strategy generates positive and significant risk-adjusted return. Finally, the impact of regulatory operating leverage on returns is due to the (systematic) risk contribution of fixed regulatory costs. (JEL G12, G18, G28)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"67 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139460765","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 provide evidence that equity investors are slow to process information about how current oil price changes affect future earnings announcements. Stock prices respond to lagged quarterly oil price changes when firms start announcing earnings in the next quarter. A cross-sectional equity trading strategy that exploits this predictability yields an annualized Sharpe ratio of 0.50. Our oil-response forecast strategy earns especially high returns after large absolute oil price changes, in recessions or bear markets, and during peak earnings season. The predictability we document is consistent with limited attention, is not driven by risk factor exposure, and survives several robustness tests.
{"title":"Oil Price Exposure and the Cross-Section of Stock Returns","authors":"Jordan Moore, Mihail Velikov","doi":"10.1093/rapstu/raad016","DOIUrl":"https://doi.org/10.1093/rapstu/raad016","url":null,"abstract":"We provide evidence that equity investors are slow to process information about how current oil price changes affect future earnings announcements. Stock prices respond to lagged quarterly oil price changes when firms start announcing earnings in the next quarter. A cross-sectional equity trading strategy that exploits this predictability yields an annualized Sharpe ratio of 0.50. Our oil-response forecast strategy earns especially high returns after large absolute oil price changes, in recessions or bear markets, and during peak earnings season. The predictability we document is consistent with limited attention, is not driven by risk factor exposure, and survives several robustness tests.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"16 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138824651","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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