While the 2008 shifted the attention from individual trades to netting-set counterparty risk, the evolving 2020 storyline is driven by liquidity risk at the funding-set level. The COVID turmoil brings General Wrong Way Risk (GWWR) to the fore while the impending IBOR transition amplifies portfolio-wide liquidity risk by nominally decoupling fixing rates from funding costs. This confluence of circumstances reopens the never quite abated debate on the “black art of FVA”.
{"title":"Liquidity in the Time of COVID","authors":"C. Albanese, Stefano Iabichino, Paolo Mammola","doi":"10.2139/ssrn.3840967","DOIUrl":"https://doi.org/10.2139/ssrn.3840967","url":null,"abstract":"While the 2008 shifted the attention from individual trades to netting-set counterparty risk, the evolving 2020 storyline is driven by liquidity risk at the funding-set level. The COVID turmoil brings General Wrong Way Risk (GWWR) to the fore while the impending IBOR transition amplifies portfolio-wide liquidity risk by nominally decoupling fixing rates from funding costs. This confluence of circumstances reopens the never quite abated debate on the “black art of FVA”.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81039059","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 work introduces the concept of a new risk measure VaR in a square (VaR(2)) and displays the formula for calculating it. It turns out that to calculate the VaR (2), it is sufficient to calculate a normal measure of risk VaR , with a certain changed confidence probability.
The ratio of risk estimates by risk measures VaR(2) and ES was investigated.
{"title":"New Risk Measure VAR Squared (VAR (2)) and its Calculation Part II: Case of the General Law of Allocation of Damages. Comparison of VAR (2) and ES","authors":"V. B. Minasyan","doi":"10.2139/ssrn.3612643","DOIUrl":"https://doi.org/10.2139/ssrn.3612643","url":null,"abstract":"The work introduces the concept of a new risk measure VaR in a square (VaR(2)) and displays the formula for calculating it. It turns out that to calculate the VaR (2), it is sufficient to calculate a normal measure of risk VaR , with a certain changed confidence probability.<br><br>The ratio of risk estimates by risk measures VaR(2) and ES was investigated.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83987415","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 considers some univariate and multivariate operational risk models, in which the loss severities are modelled by some weakly tail dependent and heavy-tailed positive random variables, and the loss frequency processes are some general counting processes. In such models, we derive some limit behaviors for the Value-at-Risk and Conditional Tail Expectation of aggregate operational risks. The methodology is based on capital approximation within the framework of the Basel II/III regulatory capital accords, which is the so-called Loss Distribution Approach. We also conduct some simulation studies to check the accuracy of our obtained approximations and the (in)sensitivity due to different dependence structures or the heavy-tailedness of the severities.
{"title":"Measuring Tail Operational Risk in Univariate and Multivariate Models under Extreme Losses","authors":"Yang Yang, Yishan Gong, Jiajun Liu","doi":"10.2139/ssrn.3607639","DOIUrl":"https://doi.org/10.2139/ssrn.3607639","url":null,"abstract":"This paper considers some univariate and multivariate operational risk models, in which the loss severities are modelled by some weakly tail dependent and heavy-tailed positive random variables, and the loss frequency processes are some general counting processes. In such models, we derive some limit behaviors for the Value-at-Risk and Conditional Tail Expectation of aggregate operational risks. The methodology is based on capital approximation within the framework of the Basel II/III regulatory capital accords, which is the so-called Loss Distribution Approach. We also conduct some simulation studies to check the accuracy of our obtained approximations and the (in)sensitivity due to different dependence structures or the heavy-tailedness of the severities.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79486621","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}
Economic theory predicts that bond insurance lowers issuers’ financing costs by resolving asymmetric information and mitigating credit risk. With comprehensive data over the last 36 years, we find increasingly diminished empirical support for these models. The value of insurance in resolving asymmetric information beyond that resolved by credit ratings and other observable bond characteristics is economically minimal. The average gross value of insurance ranges from 4 to 14 bps when bond insurers offer Aaa-rated coverage. However, this gross value becomes insignificant after 2008 when Aaa-rated insurance no longer exists. Evidence suggests that the lack of insurance benefit in the postcrisis period is attributable to the deteriorated creditworthiness of insurance companies. Examining noninterest saving explanations for the continued use of insurance in the no-Aaa insurance market, we find evidence that issuers purchase insurance out of habit (with insurance value most diminished for habitual purchasers with low governance quality) and for the convenience it affords in default, but no evidence that insurance improves secondary market liquidity. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4813 .
{"title":"The Price of Safety: The Evolution of Municipal Bond Insurance Value","authors":"Kimberly J. Cornaggia, John E. Hund, Giang Nguyen","doi":"10.2139/ssrn.3266890","DOIUrl":"https://doi.org/10.2139/ssrn.3266890","url":null,"abstract":"Economic theory predicts that bond insurance lowers issuers’ financing costs by resolving asymmetric information and mitigating credit risk. With comprehensive data over the last 36 years, we find increasingly diminished empirical support for these models. The value of insurance in resolving asymmetric information beyond that resolved by credit ratings and other observable bond characteristics is economically minimal. The average gross value of insurance ranges from 4 to 14 bps when bond insurers offer Aaa-rated coverage. However, this gross value becomes insignificant after 2008 when Aaa-rated insurance no longer exists. Evidence suggests that the lack of insurance benefit in the postcrisis period is attributable to the deteriorated creditworthiness of insurance companies. Examining noninterest saving explanations for the continued use of insurance in the no-Aaa insurance market, we find evidence that issuers purchase insurance out of habit (with insurance value most diminished for habitual purchasers with low governance quality) and for the convenience it affords in default, but no evidence that insurance improves secondary market liquidity. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4813 .","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74302450","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 consider a network of banks that optimally choose a strategy of asset liquidations and borrowing in order to cover short term obligations. The borrowing is done in the form of collateralized repurchase agreements, the haircut level of which depends on the total liquidations of all the banks. Similarly the fire-sale price of the asset obtained by each of the banks depends on the amount of assets liquidated by the bank itself and by other banks. By nature of this setup, banks' behavior is considered as a Nash equilibrium. This paper provides two forms for market clearing to occur: through a common closing price and through an application of the limit order book. The main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels).
{"title":"A Repo Model of Fire Sales with VWAP and LOB Pricing Mechanisms","authors":"Maxim Bichuch, Zachary Feinstein","doi":"10.2139/ssrn.3701847","DOIUrl":"https://doi.org/10.2139/ssrn.3701847","url":null,"abstract":"We consider a network of banks that optimally choose a strategy of asset liquidations and borrowing in order to cover short term obligations. The borrowing is done in the form of collateralized repurchase agreements, the haircut level of which depends on the total liquidations of all the banks. Similarly the fire-sale price of the asset obtained by each of the banks depends on the amount of assets liquidated by the bank itself and by other banks. By nature of this setup, banks' behavior is considered as a Nash equilibrium. This paper provides two forms for market clearing to occur: through a common closing price and through an application of the limit order book. The main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels).","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86138931","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}
Kyriakos Chousakos, Gary B. Gorton, Guillermo Ordoñez
A financial crisis is an event of sudden information acquisition about the collateral backing short-term debt in credit markets. When investors see a financial crisis coming, however, they react by more intensively acquiring information about firms in stock markets, revealing those that are weaker, which as a consequence end up cut off from credit. This cleansing effect of stock markets’ information on credit markets’ composition discourage information acquisition about the collateral of the firms remaining in credit markets, slowing down credit growth and potentially preventing a crisis. Production of information in stock markets, then, acts as a macroprudential tool in the economy.
{"title":"The Macroprudential Role of Stock Markets","authors":"Kyriakos Chousakos, Gary B. Gorton, Guillermo Ordoñez","doi":"10.2139/ssrn.3586560","DOIUrl":"https://doi.org/10.2139/ssrn.3586560","url":null,"abstract":"A financial crisis is an event of sudden information acquisition about the collateral backing short-term debt in credit markets. When investors see a financial crisis coming, however, they react by more intensively acquiring information about firms in stock markets, revealing those that are weaker, which as a consequence end up cut off from credit. This cleansing effect of stock markets’ information on credit markets’ composition discourage information acquisition about the collateral of the firms remaining in credit markets, slowing down credit growth and potentially preventing a crisis. Production of information in stock markets, then, acts as a macroprudential tool in the economy.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83035728","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 examine the stock markets’ response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 to 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.
{"title":"Stock Markets’ Reaction to Covid-19: Cases or Fatalities","authors":"Badar Nadeem Ashraf","doi":"10.2139/ssrn.3585789","DOIUrl":"https://doi.org/10.2139/ssrn.3585789","url":null,"abstract":"In this paper, we examine the stock markets’ response to the COVID-19 pandemic. Using daily COVID-19 confirmed cases and deaths and stock market returns data from 64 countries over the period January 22, 2020 to April 17, 2020, we find that stock markets responded negatively to the growth in COVID-19 confirmed cases. That is, stock market returns declined as the number of confirmed cases increased. We further find that stock markets reacted more proactively to the growth in number of confirmed cases as compared to the growth in number of deaths. Our analysis also suggests negative market reaction was strong during early days of confirmed cases and then between 40 to 60 days after the initial confirmed cases. Overall, our results suggest that stock markets quickly respond to COVID-19 pandemic and this response varies over time depending on the stage of outbreak.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82442935","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 set of indicators relevant for the risk characteristics of covered bonds, as based on granular publicly available transparency data. The indicators capture various aspects of cash flow risks related to the issuer, the cover pool and the payment structure. They offer unified risk metrics for the European covered bond universe, which ensures comparability across covered bonds issued by different issuers and rated by different credit rating agencies. The availability of granular risk indicators adds to the overall transparency of the market in the context of risk monitoring.
{"title":"Risk Characteristics of Covered Bonds: Monitoring Beyond Ratings","authors":"Magdalena Grothe, Jana Zeyer","doi":"10.2139/ssrn.3578541","DOIUrl":"https://doi.org/10.2139/ssrn.3578541","url":null,"abstract":"This paper proposes a set of indicators relevant for the risk characteristics of covered bonds, as based on granular publicly available transparency data. The indicators capture various aspects of cash flow risks related to the issuer, the cover pool and the payment structure. They offer unified risk metrics for the European covered bond universe, which ensures comparability across covered bonds issued by different issuers and rated by different credit rating agencies. The availability of granular risk indicators adds to the overall transparency of the market in the context of risk monitoring.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76588201","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 has two objectives. It first assesses the output and inflation effects of systemic risk-taking in the euro area banking sector using a factor-augmented vector autoregressive model that exploits a 519 time-series rich dataset, including coherent measures of systemic risk in all its forms and its time dimension. Then, it evaluates whether the systemic risk measures can be used as early warning signals of severe negative nominal growth outcomes using the Receiver Operating Characteristic approach. The main findings are that, overall, real GDP growth and inflation react negatively to a one-standard deviation shock to systemic risk measures of the euro area banking industry. Inflation depicts a more pronounced response than GDP. There is heterogeneity in the strength of the responses across diverse forms of systemic risk and their time dimension. Specifically, short-term systemic risk measures tend to portray stronger effects on output and inflation than their conditional forward counterparts. In particular, systemic risk in the form of banking sector vulnerability associated with interconnectedness and contagion plays a considerable role in depressing economic activity in the euro area. Finally, all but one systemic risk measure predict with high accuracy the extreme macro-financial instability in the euro area that followed Lehman Brothers’ collapse. The systemic risk measures are potentially good candidates to be included in a macroprudential-policy toolkit for calibrating instruments at thresholds that reflect policymakers’ risk preferences.
{"title":"Effects on Growth and Inflation of the Unraveling of Systemic Risk in the Euro Area Banking Sector: Lessons from the Financial Crisis","authors":"A. Kabundi, Francisco Nadal De Simone","doi":"10.2139/ssrn.3565803","DOIUrl":"https://doi.org/10.2139/ssrn.3565803","url":null,"abstract":"This study has two objectives. It first assesses the output and inflation effects of systemic risk-taking in the euro area banking sector using a factor-augmented vector autoregressive model that exploits a 519 time-series rich dataset, including coherent measures of systemic risk in all its forms and its time dimension. Then, it evaluates whether the systemic risk measures can be used as early warning signals of severe negative nominal growth outcomes using the Receiver Operating Characteristic approach. The main findings are that, overall, real GDP growth and inflation react negatively to a one-standard deviation shock to systemic risk measures of the euro area banking industry. Inflation depicts a more pronounced response than GDP. There is heterogeneity in the strength of the responses across diverse forms of systemic risk and their time dimension. Specifically, short-term systemic risk measures tend to portray stronger effects on output and inflation than their conditional forward counterparts. In particular, systemic risk in the form of banking sector vulnerability associated with interconnectedness and contagion plays a considerable role in depressing economic activity in the euro area. Finally, all but one systemic risk measure predict with high accuracy the extreme macro-financial instability in the euro area that followed Lehman Brothers’ collapse. The systemic risk measures are potentially good candidates to be included in a macroprudential-policy toolkit for calibrating instruments at thresholds that reflect policymakers’ risk preferences.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83093939","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 authors estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic risk concerns arising from the high concentration of the economy in large business groups and a few export-oriented sectors, the authors perform three levels of estimation using individual stocks, business groups, and industry returns. The results show that the measures perform well over the study’s sample period by indicating heightened levels of commonality and interconnectedness during crisis periods. In out-of-sample tests, the measures can predict future losses in the stock market during the crises. The authors also provide the recent readings of their measures at the market, chaebol, and industry levels. Although the measures indicate systemic risk is not a major concern in Korea, as they tend to be at the lowest level since 1998, there is an increasing trend in commonality and connectedness since 2017. Samsung and SK exhibit increasing degrees of commonality and connectedness, perhaps because of their heavy dependence on a few major member firms. Commonality in the finance industry has not subsided since the financial crisis, suggesting that systemic risk is still a concern in the banking sector.
{"title":"Network-Based Measures of Systemic Risk in Korea","authors":"Jaewon Choi, Jieun Lee","doi":"10.2139/ssrn.3561359","DOIUrl":"https://doi.org/10.2139/ssrn.3561359","url":null,"abstract":"The authors estimate systemic risk in the Korean economy using the econometric measures of commonality and connectedness applied to stock returns. To assess potential systemic risk concerns arising from the high concentration of the economy in large business groups and a few export-oriented sectors, the authors perform three levels of estimation using individual stocks, business groups, and industry returns. The results show that the measures perform well over the study’s sample period by indicating heightened levels of commonality and interconnectedness during crisis periods. In out-of-sample tests, the measures can predict future losses in the stock market during the crises. The authors also provide the recent readings of their measures at the market, chaebol, and industry levels. Although the measures indicate systemic risk is not a major concern in Korea, as they tend to be at the lowest level since 1998, there is an increasing trend in commonality and connectedness since 2017. Samsung and SK exhibit increasing degrees of commonality and connectedness, perhaps because of their heavy dependence on a few major member firms. Commonality in the finance industry has not subsided since the financial crisis, suggesting that systemic risk is still a concern in the banking sector.","PeriodicalId":11410,"journal":{"name":"Econometric Modeling: Capital Markets - Risk eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74637019","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：