We introduce backtesting methods to assess Value-at-Risk (VaR) and Expected Shortfall (ES) that require no more than desktop VaR violations as inputs. Maintaining an integrated VaR perspective, our methodology relies on multiple testing to combine evidence on the frequency and dynamic evolution of violations, and to capture more information than a single threshold can provide about the magnitude of violations. Contributions include a formal finite sample analysis of the joint distribution of multi-threshold violations, and limiting results that unify discrete and continuous definitions of cumulative violations across thresholds. Simulation studies demonstrate the power advantages of the proposed tests, particularly with small samples and when underlying models are unavailable to assessors. Results also reinforce the usefulness of CaViaR approaches not just for VaR but also as ES backtests. Empirically, we assess desktop data by Bloomberg on exchange traded funds. We find that tail risk is not adequately reflected via a wide spectrum of models and available measures. Results provide useful prescriptions for empirical practice and, more generally, reinforce the recent arguments in favor of combined tests and forecasts in tail risk management.
{"title":"Multilevel and Tail Risk Management","authors":"Lynda Khalaf, A. Leccadito, G. Urga","doi":"10.1093/JJFINEC/NBAA044","DOIUrl":"https://doi.org/10.1093/JJFINEC/NBAA044","url":null,"abstract":"We introduce backtesting methods to assess Value-at-Risk (VaR) and Expected Shortfall (ES) that require no more than desktop VaR violations as inputs. Maintaining an integrated VaR perspective, our methodology relies on multiple testing to combine evidence on the frequency and dynamic evolution of violations, and to capture more information than a single threshold can provide about the magnitude of violations. Contributions include a formal finite sample analysis of the joint distribution of multi-threshold violations, and limiting results that unify discrete and continuous definitions of cumulative violations across thresholds. Simulation studies demonstrate the power advantages of the proposed tests, particularly with small samples and when underlying models are unavailable to assessors. Results also reinforce the usefulness of CaViaR approaches not just for VaR but also as ES backtests. Empirically, we assess desktop data by Bloomberg on exchange traded funds. We find that tail risk is not adequately reflected via a wide spectrum of models and available measures. Results provide useful prescriptions for empirical practice and, more generally, reinforce the recent arguments in favor of combined tests and forecasts in tail risk management.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991477","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 effects of limited liability on mortgage dynamics. While the literature has focused on default rates, renegotiation, or loan rates individually, we study them together as equilibrium outcomes of the strategic interaction between lenders and borrowers. We present a simple model of default and renegotiation where the degree of limited liability plays a key role in agents' strategies. We then use Fannie Mae loan performance data to test the predictions of the model. We focus on Metropolitan Statistical Areas that are crossed by a State border in order to exploit the discontinuity in regulation around the borders of States. As predicted by the model, we find that limited liability results in higher default rates and renegotiation rates. Regarding loan pricing, while the model predicts higher interest rates for limited liability loans, we find no such evidence in the Fannie Mae data. We further investigate this by using loan application data, which contains the interest rates on loans sold to private vs public investors. We find that private investors do price in the difference in ex-ante predictable default risk for limited liability loans.
{"title":"Limited Liability, Strategic Default and Bargaining Power","authors":"Mirco Balatti, Carolina López-Quiles","doi":"10.2139/ssrn.3682550","DOIUrl":"https://doi.org/10.2139/ssrn.3682550","url":null,"abstract":"In this paper we examine the effects of limited liability on mortgage dynamics. While the literature has focused on default rates, renegotiation, or loan rates individually, we study them together as equilibrium outcomes of the strategic interaction between lenders and borrowers. We present a simple model of default and renegotiation where the degree of limited liability plays a key role in agents' strategies. We then use Fannie Mae loan performance data to test the predictions of the model. We focus on Metropolitan Statistical Areas that are crossed by a State border in order to exploit the discontinuity in regulation around the borders of States. As predicted by the model, we find that limited liability results in higher default rates and renegotiation rates. Regarding loan pricing, while the model predicts higher interest rates for limited liability loans, we find no such evidence in the Fannie Mae data. We further investigate this by using loan application data, which contains the interest rates on loans sold to private vs public investors. We find that private investors do price in the difference in ex-ante predictable default risk for limited liability loans.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"874 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133846836","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}
Options can be dynamically replicated using model-free Greeks extracted from the volatility smile. However, smile-implied delta and delta-gamma hedging do not achieve minimum variance in the presence of price-volatility correlation, and these strategies have shown poor performance relative to the Black-Scholes benchmark. We propose a way to extend smile-implied option replication with volatility risk management. Large-scale evidence on S&P 500 index options indicates that smile-implied delta-gamma-vega hedging strategies outperform the Black-Scholes approach as well as more sophisticated option hedging frameworks including stochastic volatility and jumps.
{"title":"Smile-Implied Hedging with Volatility Risk","authors":"Pascal François, Lars Stentoft","doi":"10.2139/ssrn.3681662","DOIUrl":"https://doi.org/10.2139/ssrn.3681662","url":null,"abstract":"Options can be dynamically replicated using model-free Greeks extracted from the volatility smile. However, smile-implied delta and delta-gamma hedging do not achieve minimum variance in the presence of price-volatility correlation, and these strategies have shown poor performance relative to the Black-Scholes benchmark. We propose a way to extend smile-implied option replication with volatility risk management. Large-scale evidence on S&P 500 index options indicates that smile-implied delta-gamma-vega hedging strategies outperform the Black-Scholes approach as well as more sophisticated option hedging frameworks including stochastic volatility and jumps.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130048255","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 research is to develop a fast and robust variant of the evolutionary heuristic Bionomic algorithm and assess its contribution to solving complex parametric estimation problems, in conjunction with other traditional optimization techniques. We introduce a modified version of the Bionomic Algorithm (MB), designed to efficiently compute the MLE of self-exciting exponential Hawkes processes with increasing dimensionality of the solution space. Performance tests, performed on simulated and historical S&P 500 financial data, show that the MB algorithm, with its solutions locally improved by either the standard Nelder Mead (NM) or Expectation Maximization (EM) algorithm, converges significantly faster and more frequently to a near-global solution than the NM or EM algorithms operating alone. These test results illustrate the robustness and computational efficiency of the MB algorithm, combined with traditional optimization methods, in the optimization of complex objective functions of high dimensionality.
{"title":"Calibration of exponential Hawkes processes using a Modified Bionomic Algorithm","authors":"Jing Chen, S. Pierre","doi":"10.2139/ssrn.3672195","DOIUrl":"https://doi.org/10.2139/ssrn.3672195","url":null,"abstract":"The aim of this research is to develop a fast and robust variant of the evolutionary heuristic Bionomic algorithm and assess its contribution to solving complex parametric estimation problems, in conjunction with other traditional optimization techniques. We introduce a modified version of the Bionomic Algorithm (MB), designed to efficiently compute the MLE of self-exciting exponential Hawkes processes with increasing dimensionality of the solution space. Performance tests, performed on simulated and historical S&P 500 financial data, show that the MB algorithm, with its solutions locally improved by either the standard Nelder Mead (NM) or Expectation Maximization (EM) algorithm, converges significantly faster and more frequently to a near-global solution than the NM or EM algorithms operating alone. These test results illustrate the robustness and computational efficiency of the MB algorithm, combined with traditional optimization methods, in the optimization of complex objective functions of high dimensionality.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122532426","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 notion of "relativistic finance" became ingrained in public imagination and has been asserted in many mass-media reports. Yet, despite an observed drive of the most reputable Wall Street firms to establish their servers ever closer to the trading hubs, there is surprisingly little "hard" information related to relativistic delay of the trading orders. In this paper, the author uses modified M/M/G queue theory to describe propagation of the trading signal with finite velocity.
{"title":"Transmission of Market Orders Through Communication Line With Relativistic Delay","authors":"Peter B. Lerner","doi":"10.2139/ssrn.3672625","DOIUrl":"https://doi.org/10.2139/ssrn.3672625","url":null,"abstract":"The notion of \"relativistic finance\" became ingrained in public imagination and has been asserted in many mass-media reports. Yet, despite an observed drive of the most reputable Wall Street firms to establish their servers ever closer to the trading hubs, there is surprisingly little \"hard\" information related to relativistic delay of the trading orders. In this paper, the author uses modified M/M/G queue theory to describe propagation of the trading signal with finite velocity.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134442002","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 comment letter opposes the adoption of a proposed rule published by the Office of the Comptroller of the Currency (“OCC”) on July 22, 2020. 85 Fed. Reg. 44223 (2020). The proposed rule would determine whether a national bank or federal savings association “makes a loan and is the ‘true lender’ in the context of a partnership between a bank and a third party, such as a marketplace lender.” Id. The proposed rule – to be codified at 12 C.F.R. 7.1031 – would provide that a national bank or federal savings association is deemed to “make” a loan if the institution, “as of the date of origination: (a) Is named as the lender in the loan agreement; or (b) Funds the loan.” Id. at 44228. The proposed rule is designed to operate in combination with the OCC’s recently-adopted “Madden-fix rule.” 85 Fed. Reg. 33530 (2020). Under the Madden-fix rule, a loan that is “made” by a national bank or federal savings association will retain its preemptive immunity from state usury laws under 12 U.S.C. 85 or 1463(g) if the loan is “subsequently sold, assigned, or otherwise transferred” to a nonbank. The proposed rule – in tandem with the Madden-fix rule – would allow a national bank or federal savings association to form “partnerships” with nonbank lenders, including payday lenders and auto title lenders. The two rules would allow a national bank or federal savings association to be treated as the “lender” under 12 U.S.C. 85 or 1463(g) for loans that are originated in its name or that it funds, even if it sells those loans to a nonbank “partner” one day after the loans are originated. 85 Fed. Reg. at 44225. The proposed rule would preempt state “true lender” laws, under which courts apply a substance-over-form analysis and consider several fact-specific issues in determining whether a loan is “made” by a bank as opposed to its nonbank “partner.” The two rules would permit a nonbank “partner” of a national bank or federal savings association to claim preemptive immunity from state usury laws under 12 U.S.C. 85 or 1463(g). The national bank or federal thrift could act as a mere conduit by quickly transferring loans to the nonbank “partner,” which could assume all of the economic risks and control the terms and enforcement of the loans. Such “partnerships” would amount to “rent-a-charter” schemes, which the OCC has barred national banks from entering since the early 2000s. In addition, the proposed rule evidently seeks to preempt a wide range of other state laws – including state licensing, examination, and consumer protection laws – that would otherwise apply to nonbank lenders that establish “partnerships” with national banks or federal savings associations. Thus, the proposed rule’s scope of preemption is not limited to state usury laws and potentially affects a far broader range of state laws. This comment letter argues that the OCC’s proposed rule is unlawful, invalid, and contrary to the public interest for the followin
{"title":"Comment Letter In Opposition to the OCC's Proposed \"True Lender\" Rule","authors":"Arthur E. Wilmarth","doi":"10.2139/ssrn.3673421","DOIUrl":"https://doi.org/10.2139/ssrn.3673421","url":null,"abstract":"This comment letter opposes the adoption of a proposed rule published by the Office of \u0000the Comptroller of the Currency (“OCC”) on July 22, 2020. 85 Fed. Reg. 44223 (2020). The \u0000proposed rule would determine whether a national bank or federal savings association “makes a \u0000loan and is the ‘true lender’ in the context of a partnership between a bank and a third party, such \u0000as a marketplace lender.” Id. The proposed rule – to be codified at 12 C.F.R. 7.1031 – would \u0000provide that a national bank or federal savings association is deemed to “make” a loan if the \u0000institution, “as of the date of origination: (a) Is named as the lender in the loan agreement; or (b) \u0000Funds the loan.” Id. at 44228. \u0000 \u0000The proposed rule is designed to operate in combination with the OCC’s recently-adopted \u0000“Madden-fix rule.” 85 Fed. Reg. 33530 (2020). Under the Madden-fix rule, a loan that is \u0000“made” by a national bank or federal savings association will retain its preemptive immunity \u0000from state usury laws under 12 U.S.C. 85 or 1463(g) if the loan is “subsequently sold, assigned, \u0000or otherwise transferred” to a nonbank. \u0000 \u0000The proposed rule – in tandem with the Madden-fix rule – would allow a national bank or \u0000federal savings association to form “partnerships” with nonbank lenders, including payday \u0000lenders and auto title lenders. The two rules would allow a national bank or federal savings \u0000association to be treated as the “lender” under 12 U.S.C. 85 or 1463(g) for loans that are \u0000originated in its name or that it funds, even if it sells those loans to a nonbank “partner” one day \u0000after the loans are originated. 85 Fed. Reg. at 44225. The proposed rule would preempt state \u0000“true lender” laws, under which courts apply a substance-over-form analysis and consider \u0000several fact-specific issues in determining whether a loan is “made” by a bank as opposed to its \u0000nonbank “partner.” \u0000 \u0000The two rules would permit a nonbank “partner” of a national bank or federal savings \u0000association to claim preemptive immunity from state usury laws under 12 U.S.C. 85 or 1463(g). \u0000The national bank or federal thrift could act as a mere conduit by quickly transferring loans to \u0000the nonbank “partner,” which could assume all of the economic risks and control the terms and \u0000enforcement of the loans. Such “partnerships” would amount to “rent-a-charter” schemes, which \u0000the OCC has barred national banks from entering since the early 2000s. \u0000 \u0000In addition, the proposed rule evidently seeks to preempt a wide range of other state laws \u0000– including state licensing, examination, and consumer protection laws – that would otherwise \u0000apply to nonbank lenders that establish “partnerships” with national banks or federal savings \u0000associations. Thus, the proposed rule’s scope of preemption is not limited to state usury laws \u0000and potentially affects a far broader range of state laws. \u0000 \u0000This comment letter argues that the OCC’s proposed rule is unlawful, invalid, and \u0000contrary to the public interest for the followin","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122064772","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}
Abstract The relationships between contingent convertible (CoCo) bonds and their underlying equities, credit default swap spreads (CDS), interest rates, implied volatilities and foreign exchange rates are studied. Starting with the dynamic correlation of the DCC-GARCH method, it is found that CoCo bonds are most highly correlated to CDS. By constructing the minimum spanning tree of the resulting correlations, the primary link to CDS is confirmed. Implied volatility is found to be a secondary to tertiary link, alternating in importance with equities. Interest rates and FX have little impact.
{"title":"The Price Determinants of Contingent Convertible Bonds","authors":"Peter J. Zeitsch, Tom P. Davis","doi":"10.2139/ssrn.3668324","DOIUrl":"https://doi.org/10.2139/ssrn.3668324","url":null,"abstract":"Abstract The relationships between contingent convertible (CoCo) bonds and their underlying equities, credit default swap spreads (CDS), interest rates, implied volatilities and foreign exchange rates are studied. Starting with the dynamic correlation of the DCC-GARCH method, it is found that CoCo bonds are most highly correlated to CDS. By constructing the minimum spanning tree of the resulting correlations, the primary link to CDS is confirmed. Implied volatility is found to be a secondary to tertiary link, alternating in importance with equities. Interest rates and FX have little impact.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726703","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 illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID-19 pandemic—when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it vastly underestimates uncertainty.
{"title":"How to Estimate a VAR after March 2020","authors":"M. Lenza, Giorgio E. Primiceri","doi":"10.3386/w27771","DOIUrl":"https://doi.org/10.3386/w27771","url":null,"abstract":"This paper illustrates how to handle a sequence of extreme observations—such as those recorded during the COVID-19 pandemic—when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it vastly underestimates uncertainty.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131675709","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 scoring is a rapidly expanding analytical technique used by banks and other financial institutions. Academic studies on credit scoring provide a range of classification techniques used to differentiate between good and bad borrowers. The main contribution of this paper is to introduce a new method for credit scoring based on Gaussian Mixture Models. Our algorithm classifies consumers into groups which are labeled as positive or negative. Labels are estimated according to the probability associated with each class. We apply our model with real world databases from Australia, Japan, and Germany. Numerical results show that not only our model's performance is comparable to others, but also its flexibility avoids over-fitting even in the absence of standard cross validation techniques. The framework developed by this paper can provide a computationally efficient and powerful tool for assessment of consumer default risk in related financial institutions.
{"title":"A Novel Classification Approach for Credit Scoring based on Gaussian Mixture Models","authors":"H. Arian, Seyed Mohammad Sina Seyfi, A. Sharifi","doi":"10.2139/ssrn.3696216","DOIUrl":"https://doi.org/10.2139/ssrn.3696216","url":null,"abstract":"Credit scoring is a rapidly expanding analytical technique used by banks and other financial institutions. Academic studies on credit scoring provide a range of classification techniques used to differentiate between good and bad borrowers. The main contribution of this paper is to introduce a new method for credit scoring based on Gaussian Mixture Models. Our algorithm classifies consumers into groups which are labeled as positive or negative. Labels are estimated according to the probability associated with each class. We apply our model with real world databases from Australia, Japan, and Germany. Numerical results show that not only our model's performance is comparable to others, but also its flexibility avoids over-fitting even in the absence of standard cross validation techniques. The framework developed by this paper can provide a computationally efficient and powerful tool for assessment of consumer default risk in related financial institutions.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114820773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using contract-level supervisory data, we show that dollar forward sales by non-U.S. banks that are initiated at the end of a quarter and mature shortly after it concludes trade at higher prices and higher volumes. These effects are driven by banks with large net on-balance-sheet dollar assets that they can hedge around quarter ends by selling dollars forward (increasing off-balance-sheet short positions), which suggests regulatory arbitrage to reduce capital charges for open foreign exchange (FX) exposure. Our results indicate that demand effects related to banks’ management of FX exposure are an important driver of deviations from covered interest rate parity.
{"title":"Demand Effects in the FX Forward Market: Micro Evidence from Banks’ Dollar Hedging","authors":"Puriya Abbassi, Falk Bräuning","doi":"10.2139/ssrn.3117397","DOIUrl":"https://doi.org/10.2139/ssrn.3117397","url":null,"abstract":"\u0000 Using contract-level supervisory data, we show that dollar forward sales by non-U.S. banks that are initiated at the end of a quarter and mature shortly after it concludes trade at higher prices and higher volumes. These effects are driven by banks with large net on-balance-sheet dollar assets that they can hedge around quarter ends by selling dollars forward (increasing off-balance-sheet short positions), which suggests regulatory arbitrage to reduce capital charges for open foreign exchange (FX) exposure. Our results indicate that demand effects related to banks’ management of FX exposure are an important driver of deviations from covered interest rate parity.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130090662","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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