This paper identifies a clear tradeoff between tracking error — performance differences relative to a targeted asset allocation — and turnover—a proxy for rebalancing costs — that can help guide investors’ rebalancing choices. We find that calendar-based approaches, while convenient, tend to lead to less efficient rebalancing tradeoffs than rebalancing with tolerance bands. Further improvements can be gained with tiered approaches that apply different tolerance bands across and within asset classes. We do not find evidence that rebalancing choices can reliably increase expected returns. Finally, our study evaluates how rebalancing choices relate to asset allocation and how they may impact a portfolio’s maximum drawdowns and shorter-term return differences to the target allocation.
{"title":"Portfolio Rebalancing: Tradeoffs and Decisions","authors":"Xing Hong, Philipp Meyer-Brauns","doi":"10.2139/ssrn.3858951","DOIUrl":"https://doi.org/10.2139/ssrn.3858951","url":null,"abstract":"This paper identifies a clear tradeoff between tracking error — performance differences relative to a targeted asset allocation — and turnover—a proxy for rebalancing costs — that can help guide investors’ rebalancing choices. We find that calendar-based approaches, while convenient, tend to lead to less efficient rebalancing tradeoffs than rebalancing with tolerance bands. Further improvements can be gained with tiered approaches that apply different tolerance bands across and within asset classes. We do not find evidence that rebalancing choices can reliably increase expected returns. Finally, our study evaluates how rebalancing choices relate to asset allocation and how they may impact a portfolio’s maximum drawdowns and shorter-term return differences to the target allocation.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90267177","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 purpose of this research is to determine the practicality of a prospective reform of the Moroccan money market's interbank rate within the context of the worldwide shift of reference indices. By analyzing 351 days of quotations, we were able to acquire an optimistic result using the chosen approach, which includes regulated variations that keep the compound rate relatively stable in comparison to other rates. The findings can be used as a benchmark for future maturities. It is worth noting, however, that the compounding strategy does have certain drawbacks. This is the most often used strategy among market participants due to its simplicity in terms of theoretical foundations and openness. The primary shortcoming of the suggested model is its lack of predicting. The methodology is based on previous day's data, with an eye toward the past, which complicates the changeover given IBOR rates' future-oriented methodology. This research project is designed to act as a starting point for future revisions to the ideas made in the body of this research.
{"title":"The Reform of Money Market Benchmarks Worldwide: Construction of a Forward Rate Model for the Moroccan Interbank Market","authors":"Youssef Louraoui","doi":"10.2139/ssrn.3854204","DOIUrl":"https://doi.org/10.2139/ssrn.3854204","url":null,"abstract":"The purpose of this research is to determine the practicality of a prospective reform of the Moroccan money market's interbank rate within the context of the worldwide shift of reference indices. By analyzing 351 days of quotations, we were able to acquire an optimistic result using the chosen approach, which includes regulated variations that keep the compound rate relatively stable in comparison to other rates. The findings can be used as a benchmark for future maturities. It is worth noting, however, that the compounding strategy does have certain drawbacks. This is the most often used strategy among market participants due to its simplicity in terms of theoretical foundations and openness. The primary shortcoming of the suggested model is its lack of predicting. The methodology is based on previous day's data, with an eye toward the past, which complicates the changeover given IBOR rates' future-oriented methodology. This research project is designed to act as a starting point for future revisions to the ideas made in the body of this research.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72751037","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}
Credit management is the process of granting credit, terms and conditions definition, compliance with credit policy, and then payment on the due date. The core business for financial institutions is to improve revenues and profit by facilitating sales and reducing loss and financial risks. This research is to assess the effectiveness of credit management principles and their impact on loan performance for a specific type of loan “microcredit”. The case study is microcredit in East Africa especially provided by commercial banks in partnership with mobile network operators. The purpose of the research will be mainly to assess the applicability of credit management principles to achieve better performance in microlending. This research's target sample is East Africa commercial banks in conjunction with mobile operators providing online microcredit to mobile money subscribers and commercial banks ‘customers.
{"title":"Effectiveness of Credit Management System on Micro Credit Performance: Case Study of East Africa Commercial Banks and Mobile Operators","authors":"Eveque Mutabaruka","doi":"10.2139/ssrn.3855367","DOIUrl":"https://doi.org/10.2139/ssrn.3855367","url":null,"abstract":"Credit management is the process of granting credit, terms and conditions definition, compliance with credit policy, and then payment on the due date. The core business for financial institutions is to improve revenues and profit by facilitating sales and reducing loss and financial risks. This research is to assess the effectiveness of credit management principles and their impact on loan performance for a specific type of loan “microcredit”. The case study is microcredit in East Africa especially provided by commercial banks in partnership with mobile network operators. The purpose of the research will be mainly to assess the applicability of credit management principles to achieve better performance in microlending. This research's target sample is East Africa commercial banks in conjunction with mobile operators providing online microcredit to mobile money subscribers and commercial banks ‘customers.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76908254","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 global financial crisis showed us that there is a need for appropriate identification and evaluation of implicit liquidity trading risks in investment portfolios. It is undeniable that many of the financial institution collapses, both in developed and emerging markets, as well as the subsequent financial turbulence, were, to a certain extent, caused by the impact of liquidity trading risk on structured stocks portfolios. Liquidity trading risk increases due to the incapability of financial institutions to liquidate their shares at a fair price during the settlement period. In the chapter “Liquidity risk management in emerging and Islamic markets” that I published as part of the Handbook of Empirical Research on Islam and Economic Life (Edward Elgar, 2017), edited by the renowned scholar Prof. M. Kabir Hassan, University of New Orleans, I empirically develop and test a strategy of measurement and exposure control of market/liquidity risks of investment portfolios that include illiquid capital shares in critical circumstances, proposing that there be a strategy for the establishment of maximum risk limits.
{"title":"Liquidity Risk Management in the Avoidance of Another Financial Crisis","authors":"Mazin A. M. Al Janabi","doi":"10.2139/ssrn.3840350","DOIUrl":"https://doi.org/10.2139/ssrn.3840350","url":null,"abstract":"The global financial crisis showed us that there is a need for appropriate identification and evaluation of implicit liquidity trading risks in investment portfolios. It is undeniable that many of the financial institution collapses, both in developed and emerging markets, as well as the subsequent financial turbulence, were, to a certain extent, caused by the impact of liquidity trading risk on structured stocks portfolios. Liquidity trading risk increases due to the incapability of financial institutions to liquidate their shares at a fair price during the settlement period. In the chapter “Liquidity risk management in emerging and Islamic markets” that I published as part of the Handbook of Empirical Research on Islam and Economic Life (Edward Elgar, 2017), edited by the renowned scholar Prof. M. Kabir Hassan, University of New Orleans, I empirically develop and test a strategy of measurement and exposure control of market/liquidity risks of investment portfolios that include illiquid capital shares in critical circumstances, proposing that there be a strategy for the establishment of maximum risk limits.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80172036","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}
Protection of creditors is a key objective of financial regulation. Where the protection needs are high, i.e., in banking and insurance, regulatory solvency requirements are an instrument to prevent that creditors incur losses on their claims. The current regulatory requirements based on Value at Risk and Average Value at Risk limit the probability of default of financial institutions, but fail to control the size of recovery on creditors' claims in the case of default. We resolve this failure by developing a novel risk measure, Recovery Value at Risk. Our conceptual approach can flexibly be extended and allows the construction of general recovery risk measures for various risk management purposes. By design, these risk measures control recovery on creditors' claims and integrate the protection needs of creditors into the incentive structure of the management. We provide detailed case studies and applications: We analyze how recovery risk measures react to the joint distributions of assets and liabilities on firms' balance sheets and compare the corresponding capital requirements with the current regulatory benchmarks based on Value at Risk and Average Value at Risk. We discuss how to calibrate recovery risk measures to historic regulatory standards. Finally, we show that recovery risk measures can be applied to performance-based management of business divisions of firms and that they allow for a tractable characterization of optimal tradeoffs between risk and return in the context of investment management.
{"title":"Capital Requirements and Claims Recovery: A New Perspective on Solvency Regulation","authors":"Cosimo Munari, Stefan Weber, Lutz Wilhelmy","doi":"10.2139/ssrn.3829179","DOIUrl":"https://doi.org/10.2139/ssrn.3829179","url":null,"abstract":"Protection of creditors is a key objective of financial regulation. Where the protection needs are high, i.e., in banking and insurance, regulatory solvency requirements are an instrument to prevent that creditors incur losses on their claims. The current regulatory requirements based on Value at Risk and Average Value at Risk limit the probability of default of financial institutions, but fail to control the size of recovery on creditors' claims in the case of default. We resolve this failure by developing a novel risk measure, Recovery Value at Risk. Our conceptual approach can flexibly be extended and allows the construction of general recovery risk measures for various risk management purposes. By design, these risk measures control recovery on creditors' claims and integrate the protection needs of creditors into the incentive structure of the management. We provide detailed case studies and applications: We analyze how recovery risk measures react to the joint distributions of assets and liabilities on firms' balance sheets and compare the corresponding capital requirements with the current regulatory benchmarks based on Value at Risk and Average Value at Risk. We discuss how to calibrate recovery risk measures to historic regulatory standards. Finally, we show that recovery risk measures can be applied to performance-based management of business divisions of firms and that they allow for a tractable characterization of optimal tradeoffs between risk and return in the context of investment management.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84555400","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 study proposes a portfolio-based forward premium regression to estimate its time-varying coefficients and to conduct simultaneous inference. To this end, we sort currency portfolios on forward premiums. The empirical results show much weaker evidence of Uncovered Interest Parity (UIP) breakdown for the currency portfolios than for individual currencies. The main implication is that the effects of two sources of heterogeneity—exposure to currency-specific risk and exposure to common risk—on the forward premium anomaly diminish with diversification through portfolio construction. The study also illustrates that the U.S. fundamentals have persistent predictive power for the risk premium of each portfolio.
{"title":"New Insights on the Forward Premium Regression through a Portfolio-based Approach","authors":"Jinyong Kim, Kun-Ho Kim, Taejin Kim","doi":"10.2139/ssrn.3812224","DOIUrl":"https://doi.org/10.2139/ssrn.3812224","url":null,"abstract":"This study proposes a portfolio-based forward premium regression to estimate its time-varying coefficients and to conduct simultaneous inference. To this end, we sort currency portfolios on forward premiums. The empirical results show much weaker evidence of Uncovered Interest Parity (UIP) breakdown for the currency portfolios than for individual currencies. The main implication is that the effects of two sources of heterogeneity—exposure to currency-specific risk and exposure to common risk—on the forward premium anomaly diminish with diversification through portfolio construction. The study also illustrates that the U.S. fundamentals have persistent predictive power for the risk premium of each portfolio.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90535818","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 Financial Risk Meter (FRM) is an established quantitative tool that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of expectiles, thus indicating not only the tail probability but rather the actual tail loss given a stress situation in the network. The expectile variant of the FRM enjoys several advantages: Firstly, the multivariate tail risk indicator conditional expectile-based VaR (CoEVaR) can be derived, which is sensitive to the magnitude of extreme losses. Next, FRM index is not restricted to an index compared to the quantile based FRM mechanisms, but can be expanded to a set of systemic tail risk indicators, which provide investors with numerous tools in terms of diverse risk preferences. The power of FRM also lies in displaying the FRM distribution across various entities every day. Two distinct patterns can be discovered under high stress and during stable periods from the empirical results in the United States stock market. Furthermore, the framework is able to identify individual risk characteristics and to capture spillover effects in a network.
{"title":"Financial Risk Meter based on Expectiles","authors":"Rui Ren, Meng-Jou Lu, Yingxing Li, W. Härdle","doi":"10.2139/ssrn.3809329","DOIUrl":"https://doi.org/10.2139/ssrn.3809329","url":null,"abstract":"The Financial Risk Meter (FRM) is an established quantitative tool that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of expectiles, thus indicating not only the tail probability but rather the actual tail loss given a stress situation in the network. The expectile variant of the FRM enjoys several advantages: Firstly, the multivariate tail risk indicator conditional expectile-based VaR (CoEVaR) can be derived, which is sensitive to the magnitude of extreme losses. Next, FRM index is not restricted to an index compared to the quantile based FRM mechanisms, but can be expanded to a set of systemic tail risk indicators, which provide investors with numerous tools in terms of diverse risk preferences. The power of FRM also lies in displaying the FRM distribution across various entities every day. Two distinct patterns can be discovered under high stress and during stable periods from the empirical results in the United States stock market. Furthermore, the framework is able to identify individual risk characteristics and to capture spillover effects in a network.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86501482","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 examines the effect of Environmental-, Social- and Governance- (ESG) rating events on returns and risks of stocks based on a large sample of US firms and their MSCI ESG ratings. Using event study methodology, we find that markets react with significant negative abnormal returns to downgrades in environmental and in social scores. ESG rating changes thus seem to provide new value-relevant information to market participants. Further, applying a difference-in-differences approach, we assess whether and how changes in ESG rating impact the risks associated with stocks by examining downside, systematic and total risk. Our findings suggest that rating changes already materialize shortly after the rating event. Upgrades in environmental scores significantly moderate downside risk, whereas upgrades in governance scores seem to mitigate systematic risk. Therefore, by improving the firm’s ESG profile, managers can mitigate value-relevant risks of their firms in short-term.
{"title":"ESG Rating Events and Stock Market Reactions","authors":"M. Glück, Benjamin Hübel, H. Scholz","doi":"10.2139/ssrn.3803254","DOIUrl":"https://doi.org/10.2139/ssrn.3803254","url":null,"abstract":"This paper examines the effect of Environmental-, Social- and Governance- (ESG) rating events on returns and risks of stocks based on a large sample of US firms and their MSCI ESG ratings. Using event study methodology, we find that markets react with significant negative abnormal returns to downgrades in environmental and in social scores. ESG rating changes thus seem to provide new value-relevant information to market participants. Further, applying a difference-in-differences approach, we assess whether and how changes in ESG rating impact the risks associated with stocks by examining downside, systematic and total risk. Our findings suggest that rating changes already materialize shortly after the rating event. Upgrades in environmental scores significantly moderate downside risk, whereas upgrades in governance scores seem to mitigate systematic risk. Therefore, by improving the firm’s ESG profile, managers can mitigate value-relevant risks of their firms in short-term.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85443683","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}
As financial development progresses, the maturity structure of bond yields plays a rising role not only in the financial system but also as a key transmission channel of monetary policy. China is likely to be no exception. However, specific characteristics in China’s bond markets raise two major questions. First do China’s Treasury bonds offer the benchmark term structure of yields, or is this role fulfilled by the young but fast expanding corporate bond market? In other words, where does price discovery take place in the Chinese bond market in terms of the different components of the yield curve?
We identify both dynamic and long-run relationships between each of the level, slope and curvature factors of the Treasury and corporate bond markets yield curve in China. We aim at determining which market plays a leading role in the discovery of each factor of the yield curve.
We obtain three main results. First, we document for the first time the presence of a long-run relationship between the corporate and Treasury bond markets in China both for the level and the slope of their yield curve. Second, such a long-run relationship appears to be stable between the slopes over the full sample 2006-2017, but shows a break for the level factor in 2012. Third, the source market for price discovery varies with the parameters of the yield curve. While the corporate bond market is the source of price discovery for the level factor, this function is fulfilled by the government bond market for the slope parameter.
The finding that the Treasury bond market is not fully dominant in level bond-pricing may not come as a surprise. Although China’s corporate bond market has developed rapidly in the past fifteen years, there were few default cases during that period. It is believed investors treat the default risk of corporate bonds as similar to that of Treasury bonds, and benefit from the high corporate spread. Our results for the slope parameter imply that market-oriented reform has progressed enough for the Treasury bond market to already provide a benchmark slope for the yield curve of corporate bonds. When the reform progresses further, we would expect corporate bonds to be priced according to their risk profile which should make the Treasury market lead in price discovery also for the level of the yield curve.
{"title":"Price Discovery in China’s Corporate and Treasury Yield Curves","authors":"E. Girardin, Sandrine Lunven, Hongyi Chen","doi":"10.2139/ssrn.3803121","DOIUrl":"https://doi.org/10.2139/ssrn.3803121","url":null,"abstract":"As financial development progresses, the maturity structure of bond yields plays a rising role not only in the financial system but also as a key transmission channel of monetary policy. China is likely to be no exception. However, specific characteristics in China’s bond markets raise two major questions. First do China’s Treasury bonds offer the benchmark term structure of yields, or is this role fulfilled by the young but fast expanding corporate bond market? In other words, where does price discovery take place in the Chinese bond market in terms of the different components of the yield curve?<br><br>We identify both dynamic and long-run relationships between each of the level, slope and curvature factors of the Treasury and corporate bond markets yield curve in China. We aim at determining which market plays a leading role in the discovery of each factor of the yield curve.<br><br>We obtain three main results. First, we document for the first time the presence of a long-run relationship between the corporate and Treasury bond markets in China both for the level and the slope of their yield curve. Second, such a long-run relationship appears to be stable between the slopes over the full sample 2006-2017, but shows a break for the level factor in 2012. Third, the source market for price discovery varies with the parameters of the yield curve. While the corporate bond market is the source of price discovery for the level factor, this function is fulfilled by the government bond market for the slope parameter.<br><br>The finding that the Treasury bond market is not fully dominant in level bond-pricing may not come as a surprise. Although China’s corporate bond market has developed rapidly in the past fifteen years, there were few default cases during that period. It is believed investors treat the default risk of corporate bonds as similar to that of Treasury bonds, and benefit from the high corporate spread. Our results for the slope parameter imply that market-oriented reform has progressed enough for the Treasury bond market to already provide a benchmark slope for the yield curve of corporate bonds. When the reform progresses further, we would expect corporate bonds to be priced according to their risk profile which should make the Treasury market lead in price discovery also for the level of the yield curve.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74313155","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 emergence of algorithmic high-frequency trading in the market for credit risk affords accurate inference of new risk measures. When combined with machine learning predictive methods, these measures forecast substantial future changes in firms' credit and equity risk premiums in out-of-sample. Parallel measures estimated from firms' stocks fail to predict risk premiums, indicating that credit-market-based risk measures contain valuable information for forecasting firms' risk premia in both markets. The innovative high-volume high-frequency trading has not alleviated short-horizon pricing deviations across firms' equity and credit markets, an epitome of latent arbitrage in the market for credit risk.
{"title":"Machine Learning Predictions of Credit and Equity Risk Premia","authors":"Arben Kita","doi":"10.2139/ssrn.3800205","DOIUrl":"https://doi.org/10.2139/ssrn.3800205","url":null,"abstract":"The emergence of algorithmic high-frequency trading in the market for credit risk affords accurate inference of new risk measures. When combined with machine learning predictive methods, these measures forecast substantial future changes in firms' credit and equity risk premiums in out-of-sample. Parallel measures estimated from firms' stocks fail to predict risk premiums, indicating that credit-market-based risk measures contain valuable information for forecasting firms' risk premia in both markets. The innovative high-volume high-frequency trading has not alleviated short-horizon pricing deviations across firms' equity and credit markets, an epitome of latent arbitrage in the market for credit risk.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79918875","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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