This study quantifies the contributions of risk and mispricing to a comprehensive set of anomalies identified in the literature. Overall, risk and mispricing contribute equally to these anomalies; however, there is a wide variation across different categories. Mispricing is solely responsible for momentum anomalies, whereas risk is solely responsible for anomalies associated with accounting-to-market ratios. Profitability and investment anomalies are due to both risk and mispricing, while other anomalies based on information from financial statements and the stock market are mainly due to mispricing. The study highlights the importance of considering risk and mispricing together in asset-pricing research, especially when the two causes are likely to have opposite effects, as in the case of anomalies relating to financial distress and constraints.
{"title":"How Do Risk and Mispricing Contribute to Anomalies?","authors":"Yuan Li","doi":"10.2139/ssrn.3642792","DOIUrl":"https://doi.org/10.2139/ssrn.3642792","url":null,"abstract":"This study quantifies the contributions of risk and mispricing to a comprehensive set of anomalies identified in the literature. Overall, risk and mispricing contribute equally to these anomalies; however, there is a wide variation across different categories. Mispricing is solely responsible for momentum anomalies, whereas risk is solely responsible for anomalies associated with accounting-to-market ratios. Profitability and investment anomalies are due to both risk and mispricing, while other anomalies based on information from financial statements and the stock market are mainly due to mispricing. The study highlights the importance of considering risk and mispricing together in asset-pricing research, especially when the two causes are likely to have opposite effects, as in the case of anomalies relating to financial distress and constraints.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90409547","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}
Crash risk has been a hot dispute since financial crisis (2008) and the Chinese stock market crash (2015). Many literature including features of managers have been discussed to connect them with crash risk. However, fewer literatures focus on the channel between innovation and crash risk. In this paper, two different channels of innovation input and output have been constructed to explain the crash risk. Innovation input, R&D activities under earnings management, increase the information asymmetry and crash risk, while innovation output, patent quality for its public availability for datum, decrease the information asymmetry, and crash risk. Sample selection for innovative firms and non-innovative firms have been examined to be robust. The financial crisis has also been tested to verify the crash risk. We hope to build two mechanisms for conduction between innovation and crash risk in China.
{"title":"Corporate Innovation and Crash Risk: Output and Input Channel","authors":"Guanglei Zhou, Feng Guo","doi":"10.2139/ssrn.3632771","DOIUrl":"https://doi.org/10.2139/ssrn.3632771","url":null,"abstract":"Crash risk has been a hot dispute since financial crisis (2008) and the Chinese stock market crash (2015). Many literature including features of managers have been discussed to connect them with crash risk. However, fewer literatures focus on the channel between innovation and crash risk. In this paper, two different channels of innovation input and output have been constructed to explain the crash risk. Innovation input, R&D activities under earnings management, increase the information asymmetry and crash risk, while innovation output, patent quality for its public availability for datum, decrease the information asymmetry, and crash risk. Sample selection for innovative firms and non-innovative firms have been examined to be robust. The financial crisis has also been tested to verify the crash risk. We hope to build two mechanisms for conduction between innovation and crash risk in China.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84908927","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 develop a measure of how information events impact investors' perceptions of firms' riskiness. We derive this measure from an option-pricing model where investors anticipate an announcement containing information on the mean and variance of firms' future prices. We apply the measure to firms' earnings announcements and show it has many desirable properties: it predicts firms' return volatilities, risk-factor exposures, implied costs of capital, the timing of heightened volatility, and deterioration in fundamental performance, and outperforms textual-based proxies. Together, our study offers an approach for studying risk information conveyed by information events that is simple to implement and broadly applicable.
{"title":"Measuring Risk Information","authors":"Kevin C. Smith, Eric C. So","doi":"10.2139/ssrn.3519543","DOIUrl":"https://doi.org/10.2139/ssrn.3519543","url":null,"abstract":"We develop a measure of how information events impact investors' perceptions of firms' riskiness. We derive this measure from an option-pricing model where investors anticipate an announcement containing information on the mean and variance of firms' future prices. We apply the measure to firms' earnings announcements and show it has many desirable properties: it predicts firms' return volatilities, risk-factor exposures, implied costs of capital, the timing of heightened volatility, and deterioration in fundamental performance, and outperforms textual-based proxies. Together, our study offers an approach for studying risk information conveyed by information events that is simple to implement and broadly applicable.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91503720","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}
How can risk of a company be allocated to its divisions and attributed to risk factors? The Euler principle allows for an economically justified allocation of risk to different divisions. We introduce a method that generalizes the Euler principle to attribute risk to its driving factors when these factors affect losses in a nonlinear way. The method splits loss contributions over time and is straightforward to implement. We show in an example how this risk decomposition can be applied in the context of credit risk.
{"title":"A New Approach to Risk Attribution and its Application in Credit Risk Analysis","authors":"C. Frei","doi":"10.3390/risks8020065","DOIUrl":"https://doi.org/10.3390/risks8020065","url":null,"abstract":"How can risk of a company be allocated to its divisions and attributed to risk factors? The Euler principle allows for an economically justified allocation of risk to different divisions. We introduce a method that generalizes the Euler principle to attribute risk to its driving factors when these factors affect losses in a nonlinear way. The method splits loss contributions over time and is straightforward to implement. We show in an example how this risk decomposition can be applied in the context of credit risk.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86468522","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 analyse the impact of the COVID-19 pandemic on spillover between conventional and Islamic stock and bond markets. We further analyse comparatively whether gold, oil, and Bitcoin prices, VIX and EPU index affect the relationships between these markets during the COVID-19 pandemic. The results show that the Islamic bonds (Sukuk) demonstrate safe haven properties during this pandemic, while the spillovers between conventional and Islamic stock markets become stronger during the pandemic. COVID-19, Oil and gold are strong predictors of conventional-Islamic markets spillovers, while Bitcoin is not a significant determinant of these relationships.
{"title":"Searching for Safe Havens during the COVID-19 Pandemic: Determinants of Spillovers between Islamic and Conventional Financial Markets","authors":"L. Yarovaya, Ahmed H. Elsayed, S. Hammoudeh","doi":"10.2139/ssrn.3634114","DOIUrl":"https://doi.org/10.2139/ssrn.3634114","url":null,"abstract":"We analyse the impact of the COVID-19 pandemic on spillover between conventional and Islamic stock and bond markets. We further analyse comparatively whether gold, oil, and Bitcoin prices, VIX and EPU index affect the relationships between these markets during the COVID-19 pandemic. The results show that the Islamic bonds (Sukuk) demonstrate safe haven properties during this pandemic, while the spillovers between conventional and Islamic stock markets become stronger during the pandemic. COVID-19, Oil and gold are strong predictors of conventional-Islamic markets spillovers, while Bitcoin is not a significant determinant of these relationships.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88094724","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}
During the COVID-19 pandemic (Jan 2020 - Mar 2020) all of the Fama and French (2018) factors except momentum lost money. Negative payoffs in a bad state would appear to justify the positive premia generated by these risk factors. But this is atypical – historically the value, profitability, investment and momentum factors are all more profitable in bear markets. The five non-market factors exhibit their own bull and bear market phases, but these do not correlate with the economic cycle. Factor profitability in bear markets arise primarily from the short side. Biased expectations corrected around earnings announcement offer only a partial explanation.
{"title":"Where Is the Risk in Risk Factors? Evidence from the Vietnam War to the COVID-19 Pandemic.","authors":"P. Geertsema, Helen Lu","doi":"10.2139/ssrn.3620691","DOIUrl":"https://doi.org/10.2139/ssrn.3620691","url":null,"abstract":"During the COVID-19 pandemic (Jan 2020 - Mar 2020) all of the Fama and French (2018) factors except momentum lost money. Negative payoffs in a bad state would appear to justify the positive premia generated by these risk factors. But this is atypical – historically the value, profitability, investment and momentum factors are all more profitable in bear markets. The five non-market factors exhibit their own bull and bear market phases, but these do not correlate with the economic cycle. Factor profitability in bear markets arise primarily from the short side. Biased expectations corrected around earnings announcement offer only a partial explanation.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82027106","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}
Recent Basel Committee on Banking Supervision standards on interest rate risk in the banking book require the consideration of macroeconomic variables for modeling client behaviors, while no macroeconomic risk scenarios are prescribed by regulators or are generally agreed in the industry. Since macroeconomic variables and interest rates are correlated, projecting macroeconomic variables for interest rate risk measurement poses the challenge of maintaining consistency with regulator-prescribed interest rate scenarios. This paper proposes an approach to integrate macroeconomic variables with interest rate scenarios. The conditional expectation of macroeconomic variables on interest rate variables is used to capture their interdependence. Based on the mathematical properties of conditional expectation, we derive its nonparametric estimator. The resulting projections of macroeconomic variables are fully consistent with the given interest rate scenarios and are convenient for implementation in practice. An empirical application to Canadian fixed-term deposits is conducted to illustrate the proposed approach.
{"title":"Integrating Macroeconomic Variables into Behavioral Models for interest Rate Risk Measurement in the Banking Book","authors":"Zhongfang He","doi":"10.21314/jor.2020.436","DOIUrl":"https://doi.org/10.21314/jor.2020.436","url":null,"abstract":"Recent Basel Committee on Banking Supervision standards on interest rate risk in the banking book require the consideration of macroeconomic variables for modeling client behaviors, while no macroeconomic risk scenarios are prescribed by regulators or are generally agreed in the industry. Since macroeconomic variables and interest rates are correlated, projecting macroeconomic variables for interest rate risk measurement poses the challenge of maintaining consistency with regulator-prescribed interest rate scenarios. This paper proposes an approach to integrate macroeconomic variables with interest rate scenarios. The conditional expectation of macroeconomic variables on interest rate variables is used to capture their interdependence. Based on the mathematical properties of conditional expectation, we derive its nonparametric estimator. The resulting projections of macroeconomic variables are fully consistent with the given interest rate scenarios and are convenient for implementation in practice. An empirical application to Canadian fixed-term deposits is conducted to illustrate the proposed approach.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85776791","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 analyze the risk-return trade-off in the US Treasury market using a term-structure model that features volatility-in-mean effects of multiple sources, and yet preserves tractable bond prices. We find a strong positive relation between risks and risk premia over the 1966-2018 period. While interest-rate risk is the main driver of such positive relation, macro risk plays a non-trivial role, and its omission leads to unstable estimates of the trade-off. Notably, macro risk contributes to the surge and consequent fall of risk premia around the 1980s, whereas it moves inversely with risk premia during the recent `low yield' period.
{"title":"Risks and Risk Premia in the US Treasury Market","authors":"Junye Li, Lucio Sarno, Gabriele Zinna","doi":"10.2139/ssrn.3640341","DOIUrl":"https://doi.org/10.2139/ssrn.3640341","url":null,"abstract":"We analyze the risk-return trade-off in the US Treasury market using a term-structure model that features volatility-in-mean effects of multiple sources, and yet preserves tractable bond prices. We find a strong positive relation between risks and risk premia over the 1966-2018 period. While interest-rate risk is the main driver of such positive relation, macro risk plays a non-trivial role, and its omission leads to unstable estimates of the trade-off. Notably, macro risk contributes to the surge and consequent fall of risk premia around the 1980s, whereas it moves inversely with risk premia during the recent `low yield' period.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81897401","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 studies the impact of information processing and rational learning about economic fundamentals on the level and timing of risk premium in the cross-section of firms. Learning helps explain the level of the value premium, and why the term structure of risk premium is increasing for value firms and decreasing for growth firms. Moreover, learning yields an upward-sloping term structure of interest rates and a downward-sloping term structure of market risk premium, whereas the full information economy predicts the opposite shapes. Therefore, rational learning helps understand the level and timing of expected returns observed in the cross-section of risky and risk-free assets.
{"title":"The Term Structures of Value and Growth Risk Premia","authors":"M. Hasler, Mariana Khapko, Roberto Marfè","doi":"10.2139/ssrn.3616087","DOIUrl":"https://doi.org/10.2139/ssrn.3616087","url":null,"abstract":"This paper studies the impact of information processing and rational learning about economic fundamentals on the level and timing of risk premium in the cross-section of firms. Learning helps explain the level of the value premium, and why the term structure of risk premium is increasing for value firms and decreasing for growth firms. Moreover, learning yields an upward-sloping term structure of interest rates and a downward-sloping term structure of market risk premium, whereas the full information economy predicts the opposite shapes. Therefore, rational learning helps understand the level and timing of expected returns observed in the cross-section of risky and risk-free assets.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75832544","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 develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a statistically significant negative downgrade risk premium in excess returns, suggesting that stocks at higher risk of failure tend to deliver lower returns. The performance of the model remains robust across several estimation methods. Panel Granger causality test results indicate that there indeed is a Granger-causal relationship from credit rating transition probabilities to excess returns. Our paper thus provides a new methodology to generate firm-level downgrade probabilities and the basis for further empirical validation and development of Fama-French-type models under financial distress.
{"title":"Credit Rating Downgrade Risk on Equity Returns","authors":"Periklis Brakatsoulas, J. Kukacka","doi":"10.2139/ssrn.3617559","DOIUrl":"https://doi.org/10.2139/ssrn.3617559","url":null,"abstract":"We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a statistically significant negative downgrade risk premium in excess returns, suggesting that stocks at higher risk of failure tend to deliver lower returns. The performance of the model remains robust across several estimation methods. Panel Granger causality test results indicate that there indeed is a Granger-causal relationship from credit rating transition probabilities to excess returns. Our paper thus provides a new methodology to generate firm-level downgrade probabilities and the basis for further empirical validation and development of Fama-French-type models under financial distress.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83597311","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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