Pub Date : 2021-10-31DOI: 10.3905/jsf.2021.27.3.047
Mark H. Adelson
Credit ratings from the major rating agencies failed to signal the true risk content of residential mortgage-backed securities (RMBS), collateralized debt obligations (CDOs), and commercial mortgage-backed securities (CMBS) issued from 2005 through 2007. This article compares the failures across rating agencies and asset classes, using data filed by the rating agencies with the Securities and Exchange Commission (SEC). The data confirm the terrible performance of RMBS ratings. The likely causes include a combination of the breakdown of mortgage industry lending practices and the concurrent deterioration of rating agency practices. The data show that CDO ratings perform somewhat better than RMBS ratings. That result is perhaps surprising and likely reflects the confounding effects of the SEC’s definitions of its reporting categories. The data also show bad performance for CMBS ratings although the underlying causes differ from those driving the results for RMBS and CDOs. Moreover, the data show high levels of rating withdrawals across all asset classes, raising the question of possible underreporting of defaults. Key Findings ▪ Rating agency data reported to the SEC confirm the terrible performance of RMBS ratings, with triple-A-rated RMBS displaying 10-year default rates of 30% to 35% as of year-end 2017. The likely causes include a combination of the breakdown of mortgage industry lending and securitization practices and the concurrent deterioration of rating agency practices. ▪ The data show that CDO ratings performed better than RMBS ratings, likely because the data include ratings for many synthetic corporate CDOs. Other studies indicate that performance is significantly worse for CDOs backed by structured finance assets. ▪ CMBS ratings also performed poorly. Although CMBS rated triple-A displayed 10-year default rates of only 2% to 3%, those rated double-A had default rates of 12% to 19% while single-A-rated CMBS default rates were 23% to 32%. ▪ The data document high levels of unexplained rating withdrawals on structured finance securities. The effect of such withdrawals may be to artificially depress the reported default rates.
{"title":"Commentary: Credit Rating Failures in the Aftermath of the Mortgage Meltdown","authors":"Mark H. Adelson","doi":"10.3905/jsf.2021.27.3.047","DOIUrl":"https://doi.org/10.3905/jsf.2021.27.3.047","url":null,"abstract":"Credit ratings from the major rating agencies failed to signal the true risk content of residential mortgage-backed securities (RMBS), collateralized debt obligations (CDOs), and commercial mortgage-backed securities (CMBS) issued from 2005 through 2007. This article compares the failures across rating agencies and asset classes, using data filed by the rating agencies with the Securities and Exchange Commission (SEC). The data confirm the terrible performance of RMBS ratings. The likely causes include a combination of the breakdown of mortgage industry lending practices and the concurrent deterioration of rating agency practices. The data show that CDO ratings perform somewhat better than RMBS ratings. That result is perhaps surprising and likely reflects the confounding effects of the SEC’s definitions of its reporting categories. The data also show bad performance for CMBS ratings although the underlying causes differ from those driving the results for RMBS and CDOs. Moreover, the data show high levels of rating withdrawals across all asset classes, raising the question of possible underreporting of defaults. Key Findings ▪ Rating agency data reported to the SEC confirm the terrible performance of RMBS ratings, with triple-A-rated RMBS displaying 10-year default rates of 30% to 35% as of year-end 2017. The likely causes include a combination of the breakdown of mortgage industry lending and securitization practices and the concurrent deterioration of rating agency practices. ▪ The data show that CDO ratings performed better than RMBS ratings, likely because the data include ratings for many synthetic corporate CDOs. Other studies indicate that performance is significantly worse for CDOs backed by structured finance assets. ▪ CMBS ratings also performed poorly. Although CMBS rated triple-A displayed 10-year default rates of only 2% to 3%, those rated double-A had default rates of 12% to 19% while single-A-rated CMBS default rates were 23% to 32%. ▪ The data document high levels of unexplained rating withdrawals on structured finance securities. The effect of such withdrawals may be to artificially depress the reported default rates.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"47 - 70"},"PeriodicalIF":0.4,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45087207","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}
Reed D. Auerbach, Susan F. DiCicco, David I. Monteiro
The true lender rule issued by the Office of the Comptroller of the Currency (OCC) briefly provided a uniform standard that could be applied to determine when a national bank is acting as a lender when it partners with other service providers. The rule was lauded for its objective standard that respected the form of legal documentation. The fintech marketplace lending platforms and banks that have been doing business for years under a bank partnership model viewed the rule as a welcome sign that the OCC did not support state efforts to recast the marketplace lending platforms as the true lender as a way to impose state law usury rules against national banks. Then Congress invalidated the rule under the Congressional Review Act (CRA) within six months of its effective date. Did the bank partnership model take one step forward and two steps back? In this article, we explore “true lender” issues, existing litigation and regulatory developments, and the implications following the invalidation of the rule.
{"title":"True Lender Issues: One Step Forward, Two Steps Back?","authors":"Reed D. Auerbach, Susan F. DiCicco, David I. Monteiro","doi":"10.3905/jsf.2021.1.126","DOIUrl":"https://doi.org/10.3905/jsf.2021.1.126","url":null,"abstract":"The true lender rule issued by the Office of the Comptroller of the Currency (OCC) briefly provided a uniform standard that could be applied to determine when a national bank is acting as a lender when it partners with other service providers. The rule was lauded for its objective standard that respected the form of legal documentation. The fintech marketplace lending platforms and banks that have been doing business for years under a bank partnership model viewed the rule as a welcome sign that the OCC did not support state efforts to recast the marketplace lending platforms as the true lender as a way to impose state law usury rules against national banks. Then Congress invalidated the rule under the Congressional Review Act (CRA) within six months of its effective date. Did the bank partnership model take one step forward and two steps back? In this article, we explore “true lender” issues, existing litigation and regulatory developments, and the implications following the invalidation of the rule.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"43 - 53"},"PeriodicalIF":0.4,"publicationDate":"2021-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44301370","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 : 2021-07-31DOI: 10.3905/jsf.2021.27.2.073
APRIL 28, 2021 SFA Research Corner: Serving the Underserved This week’s Research Corner analyzes Community Development Financial Institutions, which are private financial institutions whose primary mission is to support community development by providing financing to low-income, low-wealth individuals—a population that has been historically underserved by traditional lenders. According to the complaint bulletin, there were more than 3,400 complaints in March 2021, the greatest monthly mortgage complaint volume since April 2018. MAY 17, 2021 GSE Regulatory Caps Expected to Push Investor Home Loans to Private Market In January 2021, the US Treasury and the Federal Housing Finance Agency (FHFA) announced changes to Fannie Mae and Freddie Mac’s preferred stock purchase agreements (PSPAs) that will limit the share of non-owner occupied properties purchased by government sponsored enterprises (GSEs) to 7% per year. MAY 20, 2021 SFA Blog: How New Regulatory Caps on GSEs Will Impact Homeowners In January 2021, the Federal Housing Finance Agency (FHFA) and the US Department of the Treasury announced amendments to Fannie Mae and Freddie Mac’s Preferred Stock Purchase Agreements (PSPAs).
{"title":"Highlights from Structured Finance Association (SFA)","authors":"","doi":"10.3905/jsf.2021.27.2.073","DOIUrl":"https://doi.org/10.3905/jsf.2021.27.2.073","url":null,"abstract":"APRIL 28, 2021 SFA Research Corner: Serving the Underserved This week’s Research Corner analyzes Community Development Financial Institutions, which are private financial institutions whose primary mission is to support community development by providing financing to low-income, low-wealth individuals—a population that has been historically underserved by traditional lenders. According to the complaint bulletin, there were more than 3,400 complaints in March 2021, the greatest monthly mortgage complaint volume since April 2018. MAY 17, 2021 GSE Regulatory Caps Expected to Push Investor Home Loans to Private Market In January 2021, the US Treasury and the Federal Housing Finance Agency (FHFA) announced changes to Fannie Mae and Freddie Mac’s preferred stock purchase agreements (PSPAs) that will limit the share of non-owner occupied properties purchased by government sponsored enterprises (GSEs) to 7% per year. MAY 20, 2021 SFA Blog: How New Regulatory Caps on GSEs Will Impact Homeowners In January 2021, the Federal Housing Finance Agency (FHFA) and the US Department of the Treasury announced amendments to Fannie Mae and Freddie Mac’s Preferred Stock Purchase Agreements (PSPAs).","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"73 - 83"},"PeriodicalIF":0.4,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45228044","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 : 2021-07-31DOI: 10.3905/jsf.2021.27.2.063
Jennifer Kang
Fintechs to rely heavily on ABS despite switch to banking By Jennifer Kang 07 Jan 2021 Online lenders have sought ways to transform themselves into banks to gain regulatory clarity and forge long term customer relationships [ ]of the status change, the securitization market will remain a vital funding source to the challenger banks, sources say “Fintechs are still going to see what type of private capital markets funding is needed, and I would anticipate that even chartered institutions are going to have a mix of different funding sources to ensure growth and find a sweet spot in deal flow ” [ ]regulators have shown they are still hesitant about granting money to fintechs given their short track record, making it even more necessary for these soon-to-be-banks to keep a steady stream of securitizations According to Deutsche Bank, 2020 issued deals eligible to refi and reset account for $40bn
金融科技公司尽管转向银行业，但仍严重依赖ABS作者：Jennifer Kang 2021年1月7日在线贷款人已寻求将自己转变为银行的方法，以获得监管的明确性并建立长期客户关系，消息人士表示，“金融科技公司仍将考虑需要哪种类型的私人资本市场融资，我预计，即使是特许机构也会有不同的资金来源，以确保增长并在交易流中找到最佳点”[]监管机构已经表明，鉴于金融科技公司的短期业绩，他们仍对向其提供资金犹豫不决，这使得这些即将成为银行的银行更有必要保持稳定的证券化。根据德意志银行的数据，2020年发行的交易有资格重新融资和重置400亿美元的账户
{"title":"Highlights from Global Capital","authors":"Jennifer Kang","doi":"10.3905/jsf.2021.27.2.063","DOIUrl":"https://doi.org/10.3905/jsf.2021.27.2.063","url":null,"abstract":"Fintechs to rely heavily on ABS despite switch to banking By Jennifer Kang 07 Jan 2021 Online lenders have sought ways to transform themselves into banks to gain regulatory clarity and forge long term customer relationships [ ]of the status change, the securitization market will remain a vital funding source to the challenger banks, sources say “Fintechs are still going to see what type of private capital markets funding is needed, and I would anticipate that even chartered institutions are going to have a mix of different funding sources to ensure growth and find a sweet spot in deal flow ” [ ]regulators have shown they are still hesitant about granting money to fintechs given their short track record, making it even more necessary for these soon-to-be-banks to keep a steady stream of securitizations According to Deutsche Bank, 2020 issued deals eligible to refi and reset account for $40bn","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"63 - 72"},"PeriodicalIF":0.4,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48643727","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 recent Jumbo Mortgage Loan Virtual Symposium was a virtual event on April 29, 2021. It attracted 488 registered attendees, including more than 100 investors. Speakers expressed strongly positive views about the outlook for jumbo mortgage loans and jumbo MBS. The report contains summaries of seven session from the event, including separate panels of jumbo loan originators and buyers, as well as sessions about home prices and the US economy. Sessions Covered Launching/Re-Launching Your New Jumbo Product Economic Overview Originator “C-Suite” Panel What Is Your Retention & Exit Decision Tree? Securitization Strategy? Buyers Panel Home Values & Valuation Marketing and Sourcing Jumbo Clients
{"title":"Jumbo Mortgage 2021 Conference Notes","authors":"Mark H. Adelson","doi":"10.3905/jsf.2021.1.125","DOIUrl":"https://doi.org/10.3905/jsf.2021.1.125","url":null,"abstract":"The recent Jumbo Mortgage Loan Virtual Symposium was a virtual event on April 29, 2021. It attracted 488 registered attendees, including more than 100 investors. Speakers expressed strongly positive views about the outlook for jumbo mortgage loans and jumbo MBS. The report contains summaries of seven session from the event, including separate panels of jumbo loan originators and buyers, as well as sessions about home prices and the US economy. Sessions Covered Launching/Re-Launching Your New Jumbo Product Economic Overview Originator “C-Suite” Panel What Is Your Retention & Exit Decision Tree? Securitization Strategy? Buyers Panel Home Values & Valuation Marketing and Sourcing Jumbo Clients","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"37 - 46"},"PeriodicalIF":0.4,"publicationDate":"2021-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48226117","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 aviation industry is undergoing a series of layered dynamic effects to the entire business model value chain including aviation finance, leasing, and associated structured products. COVID has caused an historical exogenous demand shock and global airlines have suffered greatly; recovery is varied and uneven. There is a divergence of what has occurred since COVID and outlook geographically among the airlines (end-users), their lessors, and all of the various stakeholders in financing structures, such as aircraft asset backed securities (ABS) and enhanced equipment trust certificates (EETCs) that make up the capital structure. Debt funding has been robust for airlines with access to the capital markets, but others are less fortunate and are finding it more difficult. Financing options are diverse but are restricted among the players, given the effects of COVID. Pricing and structuring characteristics are all affected by these conditions. Key Findings ▪ COVID has changed the structure of demand for aircraft, and it has impacted both financing of aircraft lessors and the airlines with different effects geographically. ▪ Airlines face a bifurcation of opportunity, between larger or state-supported airlines with access to the public debt capital markets or government subsidy and smaller airlines, which have had to fall back on private capital in a challenging environment. ▪ The aircraft ABS and EETC financing environments continue to have pressures from downward aircraft pricing and 2 EETC issuance winddown cases.
{"title":"Divergence of Aviation Finance Markets: Lulls before the Storm or Growth?","authors":"David Yu","doi":"10.3905/JSF.2021.1.124","DOIUrl":"https://doi.org/10.3905/JSF.2021.1.124","url":null,"abstract":"The aviation industry is undergoing a series of layered dynamic effects to the entire business model value chain including aviation finance, leasing, and associated structured products. COVID has caused an historical exogenous demand shock and global airlines have suffered greatly; recovery is varied and uneven. There is a divergence of what has occurred since COVID and outlook geographically among the airlines (end-users), their lessors, and all of the various stakeholders in financing structures, such as aircraft asset backed securities (ABS) and enhanced equipment trust certificates (EETCs) that make up the capital structure. Debt funding has been robust for airlines with access to the capital markets, but others are less fortunate and are finding it more difficult. Financing options are diverse but are restricted among the players, given the effects of COVID. Pricing and structuring characteristics are all affected by these conditions. Key Findings ▪ COVID has changed the structure of demand for aircraft, and it has impacted both financing of aircraft lessors and the airlines with different effects geographically. ▪ Airlines face a bifurcation of opportunity, between larger or state-supported airlines with access to the public debt capital markets or government subsidy and smaller airlines, which have had to fall back on private capital in a challenging environment. ▪ The aircraft ABS and EETC financing environments continue to have pressures from downward aircraft pricing and 2 EETC issuance winddown cases.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"9 - 17"},"PeriodicalIF":0.4,"publicationDate":"2021-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48717187","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 mortgage default modeling, many of the key variables, such as loan age, FICO score, Debt-to-Income ratio (DTI), and Loan-to-House-Value ratio (LTV), have nonlinear relationships with the target default rates. Experienced modelers generally apply a spline transformation with knots to the individual variables. In this article, we introduce the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features an automatic spline knot selection in a mortgage default model. QSC-MLE is an enhanced variant of SC-MLE (Chen and Samworth 2016) used in combination with a quantile-based knots set, to effectively process large datasets. QSC-MLE requires generic shape information of the inputs, for example, the monotonicity or convexity of the FICO score, DTI, and LTV, to capture any nonlinear effects. We show that the new default model considerably improves the accuracy of the out-of-sample prediction in comparison with the logistic regression and the Cox proportional hazards model. Moreover, the model conveniently generates component-wise spline functions, which facilitates the interpretation of the default rate response to the input variables. Key Findings ▪ A mortgage default model using the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features automatic spline knot selection. ▪ QSC-MLE constructs shape-constrained spline functions to capture nonlinear effects of model inputs. ▪ The new default model considerably improves the accuracy of the out-of-sample prediction.
{"title":"Automatic Spline Knot Selection in Modeling Mortgage Loan Default Using Shape Constrained Regression","authors":"Guangning Xu, Geng Deng, Xindong Wang, Ken Fu","doi":"10.3905/JSF.2021.1.123","DOIUrl":"https://doi.org/10.3905/JSF.2021.1.123","url":null,"abstract":"In mortgage default modeling, many of the key variables, such as loan age, FICO score, Debt-to-Income ratio (DTI), and Loan-to-House-Value ratio (LTV), have nonlinear relationships with the target default rates. Experienced modelers generally apply a spline transformation with knots to the individual variables. In this article, we introduce the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features an automatic spline knot selection in a mortgage default model. QSC-MLE is an enhanced variant of SC-MLE (Chen and Samworth 2016) used in combination with a quantile-based knots set, to effectively process large datasets. QSC-MLE requires generic shape information of the inputs, for example, the monotonicity or convexity of the FICO score, DTI, and LTV, to capture any nonlinear effects. We show that the new default model considerably improves the accuracy of the out-of-sample prediction in comparison with the logistic regression and the Cox proportional hazards model. Moreover, the model conveniently generates component-wise spline functions, which facilitates the interpretation of the default rate response to the input variables. Key Findings ▪ A mortgage default model using the Quantile-based Shape Constrained Maximum Likelihood Estimator (QSC-MLE), which features automatic spline knot selection. ▪ QSC-MLE constructs shape-constrained spline functions to capture nonlinear effects of model inputs. ▪ The new default model considerably improves the accuracy of the out-of-sample prediction.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"18 - 36"},"PeriodicalIF":0.4,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46676306","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 : 2021-04-30DOI: 10.3905/jsf.2021.27.1.094
{"title":"Highlights from Structured Finance Association (SFA)","authors":"","doi":"10.3905/jsf.2021.27.1.094","DOIUrl":"https://doi.org/10.3905/jsf.2021.27.1.094","url":null,"abstract":"","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"94 - 103"},"PeriodicalIF":0.4,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46117521","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 : 2021-04-30DOI: 10.3905/jsf.2021.27.1.084
Jennifer Kang
{"title":"Highlights from Global Capital","authors":"Jennifer Kang","doi":"10.3905/jsf.2021.27.1.084","DOIUrl":"https://doi.org/10.3905/jsf.2021.27.1.084","url":null,"abstract":"","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"84 - 92"},"PeriodicalIF":0.4,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41335289","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}
It is human nature to be unprepared for rare catastrophic events. Human nature includes inclinations toward optimism, optimizing for best performance if nothing changes, linear thinking, innumeracy, inertia, greed, a desire to fit in with the crowd, and myopia. Thus, being prepared for an unknown future disaster of an unknown type requires going against human nature. TOPICS: Risk management, legal/regulatory/public policy, behavioral financial theory Key Findings • Human nature has not changed since modern humans evolved. • Myopic linear thinking, inertia, greed, and social pressure lead to optimizing for what would be the best results if conditions never changed. • Resiliency when conditions change requires actively preparing for events that may never happen, which is rarely part of human nature.
{"title":"Why We Tend to Be Unprepared for the Inevitable Next Disaster","authors":"Martin Goldberg","doi":"10.3905/jsf.2020.1.108","DOIUrl":"https://doi.org/10.3905/jsf.2020.1.108","url":null,"abstract":"It is human nature to be unprepared for rare catastrophic events. Human nature includes inclinations toward optimism, optimizing for best performance if nothing changes, linear thinking, innumeracy, inertia, greed, a desire to fit in with the crowd, and myopia. Thus, being prepared for an unknown future disaster of an unknown type requires going against human nature. TOPICS: Risk management, legal/regulatory/public policy, behavioral financial theory Key Findings • Human nature has not changed since modern humans evolved. • Myopic linear thinking, inertia, greed, and social pressure lead to optimizing for what would be the best results if conditions never changed. • Resiliency when conditions change requires actively preparing for events that may never happen, which is rarely part of human nature.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"27 1","pages":"10 - 16"},"PeriodicalIF":0.4,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44812966","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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