The standard way to summarize the yield curve is to use the first three principal components of the yield curve, resulting in level, slope and curvature factors. Yields, however, are non-stationary. We analyze the first three principal components of yield changes, which correspond to changes in level, slope and curvature. The new factors based on changes in yields have strong predictive power for bond risk premia, in contrast to the factors based on yield levels. We also provide insights into the impact this has on the added value of macro data for bond risk premia predictions and the recent conclusion that machine learning provides better forecasts than linear regression.
{"title":"Forecasting Bond Risk Premia using Stationary Yield Factors","authors":"T. Hoogteijling, M. Martens, Michel van der Wel","doi":"10.2139/ssrn.3824896","DOIUrl":"https://doi.org/10.2139/ssrn.3824896","url":null,"abstract":"The standard way to summarize the yield curve is to use the first three principal components of the yield curve, resulting in level, slope and curvature factors. Yields, however, are non-stationary. We analyze the first three principal components of yield changes, which correspond to changes in level, slope and curvature. The new factors based on changes in yields have strong predictive power for bond risk premia, in contrast to the factors based on yield levels. We also provide insights into the impact this has on the added value of macro data for bond risk premia predictions and the recent conclusion that machine learning provides better forecasts than linear regression.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114846552","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 this paper new semiparametric GARCH models with long memory are introduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market risk in the banks' trading books (Basel Committee on Banking Supervision, 2013), the semi- parametric GARCH models are applied to obtain rolling one-step ahead forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk assets. In addition, standard regulatory traffic light tests (Basel Committee on Banking Supervision, 1996) and a newly introduced traffic light test for the ES are carried out for all models. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long memory GARCH models are an attractive alternative to their conventional, parametric counterparts.
本文介绍了一种新的具有长记忆的半参数GARCH模型。非参数尺度函数的估计是由SEMIFAR算法的改编版本进行的(Beran et al.， 2002)。根据巴塞尔委员会在银行交易账簿中衡量市场风险的修订建议(巴塞尔银行监管委员会，2013年)，半参数GARCH模型被应用于获得市场风险资产的风险价值(VaR)和预期缺口(ES)的滚动一步预测。此外，对所有模型都进行了标准监管红绿灯测试(巴塞尔银行监管委员会，1996年)和新引入的ES红绿灯测试。一项比较研究证明了我们建议的实际意义。我们的研究结果表明，半参数长记忆GARCH模型是传统参数模型的一个有吸引力的替代方案。
{"title":"Semiparametric GARCH Models with Long Memory Applied to Value at Risk and Expected Shortfall","authors":"Sebastian Letmathe, Yuanhua Feng, André Uhde","doi":"10.2139/ssrn.3823895","DOIUrl":"https://doi.org/10.2139/ssrn.3823895","url":null,"abstract":"In this paper new semiparametric GARCH models with long memory are introduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market risk in the banks' trading books (Basel Committee on Banking Supervision, 2013), the semi- parametric GARCH models are applied to obtain rolling one-step ahead forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk assets. In addition, standard regulatory traffic light tests (Basel Committee on Banking Supervision, 1996) and a newly introduced traffic light test for the ES are carried out for all models. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long memory GARCH models are an attractive alternative to their conventional, parametric counterparts.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124980061","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 study the real effects of resolving distressed banks using quasi-experimental variation in resolutions introduced by a threshold-based rule of the FDIC Improvement Act. Our fuzzy regression discontinuity estimates indicate that resolutions lead to reductions in employment and establishments growth of up to six percentage points. These effects are concentrated in small, less urban counties, and translate to large declines in SME lending and increases in corporate bankruptcies. These results imply that large acquiring banks restrict lending to the small business borrowers of distressed target banks. Overall, current bank resolution policy may have costly externalities for local economic activity.
{"title":"Fighting Failure: The Persistent Real Effects of Resolving Distressed Banks","authors":"Ivan T. Ivanov, S. Karolyi","doi":"10.2139/ssrn.3822591","DOIUrl":"https://doi.org/10.2139/ssrn.3822591","url":null,"abstract":"We study the real effects of resolving distressed banks using quasi-experimental variation in resolutions introduced by a threshold-based rule of the FDIC Improvement Act. Our fuzzy regression discontinuity estimates indicate that resolutions lead to reductions in employment and establishments growth of up to six percentage points. These effects are concentrated in small, less urban counties, and translate to large declines in SME lending and increases in corporate bankruptcies. These results imply that large acquiring banks restrict lending to the small business borrowers of distressed target banks. Overall, current bank resolution policy may have costly externalities for local economic activity.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115867254","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}
PurposeThe purpose of this paper is to contribute to the existing stock return predictability and idiosyncratic risk literature by examining the relationship between stock returns and components derived from the decomposition of stock returns variance at the portfolio and firm levels.Design/methodology/approachA theoretical model is used to decompose the variance of stock returns into two volatility and two covariance terms by using a conditional Fama-French three-factor model. This study adopts portfolio analysis and Fama-MacBeth cross-sectional regression to examine the relationship between components of idiosyncratic risk and expected stock returns.FindingsThe portfolio analysis results show that volatility terms are negatively related to expected stock returns, and alpha risk has the most significant relationship with stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. Furthermore, the results of the Fama-MacBeth cross-sectional regression show that only alpha risk can explain variations in stock returns at the firm level. Another finding is that when volatility and covariance terms are excluded from idiosyncratic volatility, the relation between idiosyncratic volatility and stock returns becomes weak at the portfolio level and disappears at the firm level.Originality/valueThis is the first study that examines the relations between all the components of idiosyncratic risk and expected stock returns in equal-weighted and value-weighted portfolios. This research also suggests covariance terms of idiosyncratic volatility as new predictors of stock returns at the portfolio level. Moreover, this paper contributes to the idiosyncratic risk literature by examining whether all the four additional components explain all the systematic patterns included in the unconditional idiosyncratic risk.
{"title":"The Cross-section of Expected Stock Returns and Components of Idiosyncratic Volatility","authors":"Seyed Reza Tabatabaei Poudeh, Chengbo Fu","doi":"10.2139/ssrn.3817871","DOIUrl":"https://doi.org/10.2139/ssrn.3817871","url":null,"abstract":"PurposeThe purpose of this paper is to contribute to the existing stock return predictability and idiosyncratic risk literature by examining the relationship between stock returns and components derived from the decomposition of stock returns variance at the portfolio and firm levels.Design/methodology/approachA theoretical model is used to decompose the variance of stock returns into two volatility and two covariance terms by using a conditional Fama-French three-factor model. This study adopts portfolio analysis and Fama-MacBeth cross-sectional regression to examine the relationship between components of idiosyncratic risk and expected stock returns.FindingsThe portfolio analysis results show that volatility terms are negatively related to expected stock returns, and alpha risk has the most significant relationship with stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. Furthermore, the results of the Fama-MacBeth cross-sectional regression show that only alpha risk can explain variations in stock returns at the firm level. Another finding is that when volatility and covariance terms are excluded from idiosyncratic volatility, the relation between idiosyncratic volatility and stock returns becomes weak at the portfolio level and disappears at the firm level.Originality/valueThis is the first study that examines the relations between all the components of idiosyncratic risk and expected stock returns in equal-weighted and value-weighted portfolios. This research also suggests covariance terms of idiosyncratic volatility as new predictors of stock returns at the portfolio level. Moreover, this paper contributes to the idiosyncratic risk literature by examining whether all the four additional components explain all the systematic patterns included in the unconditional idiosyncratic risk.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123488639","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}
FRTB proposes Indirect Approach (IA) to address data challenges during period of stress for calculating stress Expected Shortfall (ES) under Internal Model Method (IMM). Unlike other topics like Non-Modellable Risk Factors (NMRF) and Profit and Loss Attribution Test (PLAT), Indirect Approach gets little attention and discussion in literatures, ISDA Forums and Basel Quantitative Impact Study (QIS) due to its contingency on data readiness and complexity of operating. This paper investigates if Indirect Approach is well defined and robust to give certain and stable results and identifies some weaknesses by testing the impact of portfolio structures, underlying parameters (correlations, volatilities and means) as well as scaling factor floor on the performance of the approach through several simplified representative examples, and proposes several alternative approaches and calls for further investigation and testing to improve the approach and avoid diminishing the incentive for institutions to implement and use the Internal Model Method.
{"title":"Is Indirect Approach for Stress Expected Shortfall of FRTB Internal Model Method Well Defined?","authors":"J. Zhan","doi":"10.2139/ssrn.3814984","DOIUrl":"https://doi.org/10.2139/ssrn.3814984","url":null,"abstract":"FRTB proposes Indirect Approach (IA) to address data challenges during period of stress for calculating stress Expected Shortfall (ES) under Internal Model Method (IMM). Unlike other topics like Non-Modellable Risk Factors (NMRF) and Profit and Loss Attribution Test (PLAT), Indirect Approach gets little attention and discussion in literatures, ISDA Forums and Basel Quantitative Impact Study (QIS) due to its contingency on data readiness and complexity of operating. This paper investigates if Indirect Approach is well defined and robust to give certain and stable results and identifies some weaknesses by testing the impact of portfolio structures, underlying parameters (correlations, volatilities and means) as well as scaling factor floor on the performance of the approach through several simplified representative examples, and proposes several alternative approaches and calls for further investigation and testing to improve the approach and avoid diminishing the incentive for institutions to implement and use the Internal Model Method.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114261930","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 aim of this article is to share the key learning experiences from the challenges presented by COVID-19 that Risk Managers have had to accept and live through.
本文的目的是分享风险管理者必须接受和度过的2019冠状病毒病带来的挑战的关键学习经验。
{"title":"A Risk Manager's Journal of the Plague Year","authors":"Elisabeth Wilson, Sunil Kansal","doi":"10.2139/SSRN.3807286","DOIUrl":"https://doi.org/10.2139/SSRN.3807286","url":null,"abstract":"The aim of this article is to share the key learning experiences from the challenges presented by COVID-19 that Risk Managers have had to accept and live through.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114170188","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}
Pub Date : 2021-03-11DOI: 10.29013/EJEMS-21-1-23-28
Mario Strassberger
Financial institutes have to be in a position to describe and to analyze the networks of obligors in their credit portfolios. If one obligor defaults who is numerously connected with other obligors in the portfolio there can be effects of credit contagion. We suggest a graph-based modeling of micro-structural relationships of obligors in credit portfolios. Analyzing the graph topology, we identify the most important obligors and the weightiest relations. In addition, information is provided on possible credit contagion and risk concentration. This may help to examine potential implications of defaults on the rest of the portfolio.
{"title":"Graph-based Representations of Credit Portfolios and Their Analysis","authors":"Mario Strassberger","doi":"10.29013/EJEMS-21-1-23-28","DOIUrl":"https://doi.org/10.29013/EJEMS-21-1-23-28","url":null,"abstract":"Financial institutes have to be in a position to describe and to analyze the networks of obligors in their credit portfolios. If one obligor defaults who is numerously connected with other obligors in the portfolio there can be effects of credit contagion. We suggest a graph-based modeling of micro-structural relationships of obligors in credit portfolios. Analyzing the graph topology, we identify the most important obligors and the weightiest relations. In addition, information is provided on possible credit contagion and risk concentration. This may help to examine potential implications of defaults on the rest of the portfolio.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127086573","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 this paper, we address risk aggregation and capital allocation problems in the presence of dependence between risks. The dependence structure is defined by a mixed Bernstein copula which represents a generalization of the well-known Archimedean copulas. Using this new copula, the probability density function and the cumulative distribution function of the aggregate risk are obtained. Then, closed-form expressions for basic risk measures, such as tail value-at risk (TVaR) and TVaR-based allocations, are derived.
{"title":"Risk Aggregation and Capital Allocation Using a New Generalized Archimedean Copula","authors":"Fouad Marri, Khouzeima Moutanabbir","doi":"10.2139/ssrn.3802834","DOIUrl":"https://doi.org/10.2139/ssrn.3802834","url":null,"abstract":"In this paper, we address risk aggregation and capital allocation problems in the presence of dependence between risks. The dependence structure is defined by a mixed Bernstein copula which represents a generalization of the well-known Archimedean copulas. Using this new copula, the probability density function and the cumulative distribution function of the aggregate risk are obtained. Then, closed-form expressions for basic risk measures, such as tail value-at risk (TVaR) and TVaR-based allocations, are derived.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121653537","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}
By now climate change has a substantial impact on financial markets and risks related to it have to be analysed. Besides the physical risk imposed by extreme weather conditions, companies face transition risks as economies are rebuilding on a low-carbon basis. To assess the impact on individual companies reliable data are necessary. Currently, by far most-used data relate to the carbon emissions of firms. By analysing a large data set on company-level carbon emissions we identify several sources of data fault which have to be considered in any data-intensive analysis. We show that year-by-year analysis of company emission consistency is best to find data flaws. Also, we find that economic and carbon data are not perfectly synchronized. Our analysis indicates that the widespread use of winsorizing is not enough to remove data flaws. Also, alternative emission measures do not provide robustness of results as they tend to suffer from the same flaws. As providers update carbon data on an ad-hoc basis, the previous analysis may not be repeated unless the data set on which it was based is saved. Our findings serve as a warning for the reliability of (academic) analysis and highlight the possible impact of bad data quality on algorithmic approaches to company-level emission data.
{"title":"Handle with Care: Challenges and Opportunities of using Company-Level Emissions Data for Assessing Financial Risks from Climate Change","authors":"A. Bajić, Ruediger Kiesel, M. Hellmich","doi":"10.2139/ssrn.3789928","DOIUrl":"https://doi.org/10.2139/ssrn.3789928","url":null,"abstract":"By now climate change has a substantial impact on financial markets and risks related to it have to be analysed. Besides the physical risk imposed by extreme weather conditions, companies face transition risks as economies are rebuilding on a low-carbon basis. To assess the impact on individual companies reliable data are necessary. Currently, by far most-used data relate to the carbon emissions of firms. By analysing a large data set on company-level carbon emissions we identify several sources of data fault which have to be considered in any data-intensive analysis. We show that year-by-year analysis of company emission consistency is best to find data flaws. Also, we find that economic and carbon data are not perfectly synchronized. Our analysis indicates that the widespread use of winsorizing is not enough to remove data flaws. Also, alternative emission measures do not provide robustness of results as they tend to suffer from the same flaws. As providers update carbon data on an ad-hoc basis, the previous analysis may not be repeated unless the data set on which it was based is saved. Our findings serve as a warning for the reliability of (academic) analysis and highlight the possible impact of bad data quality on algorithmic approaches to company-level emission data.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127647973","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 evolution of firms is not necessarily uniform. Exploring how this affects credit risk models, we find that firm life cycle provides additional explanatory power not captured by age. Firm age has an ambiguous effect on default risk and its impact during periods of high volatility is insignificant. Unobserved firm heterogeneity is an important determinant of credit default swap spreads and, when accounted for, riskier growth firms command a lower spread compared to mature firms that commonly benefit from the lowest spreads. Firms that age well by maintaining a growth profile are rewarded with lower cost of capital.
{"title":"Firms That Age Well: Life Cycles and Default Risk","authors":"Attila Balogh, Jiri Svec, Danika Wright","doi":"10.2139/ssrn.3777702","DOIUrl":"https://doi.org/10.2139/ssrn.3777702","url":null,"abstract":"The evolution of firms is not necessarily uniform. Exploring how this affects credit risk models, we find that firm life cycle provides additional explanatory power not captured by age. Firm age has an ambiguous effect on default risk and its impact during periods of high volatility is insignificant. Unobserved firm heterogeneity is an important determinant of credit default swap spreads and, when accounted for, riskier growth firms command a lower spread compared to mature firms that commonly benefit from the lowest spreads. Firms that age well by maintaining a growth profile are rewarded with lower cost of capital.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126200459","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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