Fundamental credit analysis, widely performed by fixed-income analysts and financial institutions, has yet to develop a method that computes, directly from a company’s financial statements, the default probability, recovery rate upon default, and the fundamental valuation of a company’s credit risk in terms of the prices of its debts. This article introduces a computationally scalable approach to achieve these goals by modeling the dynamics of the multidimensional balance sheet, in which default is defined as the negative level of cash. Using six to eight years of annual financial statements up till 2020 as inputs, the method is applied to several Chinese real estate developers to forecast by simulation their future financials, including default scenarios, and to derive their fundamental credit spreads. The results both agreed and disagreed with the market-traded credit spreads at the time of the forecasts. The model priced the China Evergrande Group’s debt in deep distress-levels more than six months before the company’s actual default.
{"title":"Fundamental Credit Analysis through Dynamical Modeling and Simulation of the Balance Sheet: Case Study of Chinese Real Estate Developers","authors":"J. W. Xu","doi":"10.3905/jsf.2022.1.137","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.137","url":null,"abstract":"Fundamental credit analysis, widely performed by fixed-income analysts and financial institutions, has yet to develop a method that computes, directly from a company’s financial statements, the default probability, recovery rate upon default, and the fundamental valuation of a company’s credit risk in terms of the prices of its debts. This article introduces a computationally scalable approach to achieve these goals by modeling the dynamics of the multidimensional balance sheet, in which default is defined as the negative level of cash. Using six to eight years of annual financial statements up till 2020 as inputs, the method is applied to several Chinese real estate developers to forecast by simulation their future financials, including default scenarios, and to derive their fundamental credit spreads. The results both agreed and disagreed with the market-traded credit spreads at the time of the forecasts. The model priced the China Evergrande Group’s debt in deep distress-levels more than six months before the company’s actual default.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"10 - 24"},"PeriodicalIF":0.4,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41466809","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}
Financial policy, which is an integral part of economic policy, is subdivided into financial strategy and tactics. This article examines the priorities of the latest credit and financial tactics and strategies of the Republic of Azerbaijan and shows how the country is solving the problem of acquiring financial resources, both for current needs and the economic and social development of society. The authors analyze the dependence of the resulting indicators of Azerbaijan’s economic growth on credit investments. Using a vector error correction model and Granger causality analysis based on monthly data from 2005–2019, they perform correlation and regression analysis to build econometric models that characterize the investigated dependence and provide a selection of significant econometric models, as well as an assessment of the results. The influence of financial progress on monetary development has frequently been a major worry. When financial crises arise, the relationship between financial business areas, financial crises, and monetary activity becomes paramount. The primary reason for this research is to identify the relationship between financial development and monetary advancement in the Azerbaijani economy.
{"title":"Impact of Issued Loans on the Economic Growth of Azerbaijan","authors":"N. Akbulaev, Nigar Huseynli, Tabriz Aliyev","doi":"10.3905/jsf.2022.1.136","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.136","url":null,"abstract":"Financial policy, which is an integral part of economic policy, is subdivided into financial strategy and tactics. This article examines the priorities of the latest credit and financial tactics and strategies of the Republic of Azerbaijan and shows how the country is solving the problem of acquiring financial resources, both for current needs and the economic and social development of society. The authors analyze the dependence of the resulting indicators of Azerbaijan’s economic growth on credit investments. Using a vector error correction model and Granger causality analysis based on monthly data from 2005–2019, they perform correlation and regression analysis to build econometric models that characterize the investigated dependence and provide a selection of significant econometric models, as well as an assessment of the results. The influence of financial progress on monetary development has frequently been a major worry. When financial crises arise, the relationship between financial business areas, financial crises, and monetary activity becomes paramount. The primary reason for this research is to identify the relationship between financial development and monetary advancement in the Azerbaijani economy.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"58 - 73"},"PeriodicalIF":0.4,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41679555","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 : 2022-04-30DOI: 10.3905/jsf.2022.28.1.066
{"title":"Highlights from the Structured Finance Association (SFA)","authors":"","doi":"10.3905/jsf.2022.28.1.066","DOIUrl":"https://doi.org/10.3905/jsf.2022.28.1.066","url":null,"abstract":"","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"66 - 75"},"PeriodicalIF":0.4,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45861080","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 : 2022-04-30DOI: 10.3905/jsf.2022.28.1.058
Jennifer Kang
{"title":"Highlights from Global Capital","authors":"Jennifer Kang","doi":"10.3905/jsf.2022.28.1.058","DOIUrl":"https://doi.org/10.3905/jsf.2022.28.1.058","url":null,"abstract":"","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"58 - 65"},"PeriodicalIF":0.4,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43345322","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}
An unexpected result of the COVID-19 pandemic was the resurgence of private-label securitization (PLS) in 2021. This article reviews the effect of the two-year pandemic on single-family mortgage volume and performance with a focus on PLS and a view into some of the lasting impacts. PLS issuance in 2021 was the largest since 2007, with four-fifths backed by prime jumbo and Alt-A non-QM product. Fast-rising home prices expanding the jumbo loan population and record low mortgage rates triggering a refinance boom and pay-off acceleration supported new issuance. Although borrower financial distress precipitated a spike in delinquency rates, delinquencies at the end of 2021 were generally below levels two years earlier except for long-term delinquency (more than fifteen months past due). PLS delinquency varies substantially across the nation, with states hit particularly hard by the pandemic, recession, and natural hazards having serious delinquency rates of more than 25% above the national level.
{"title":"Aftershock: The Effect of the Pandemic on Mortgage Securitization","authors":"Frank E. Nothaft, Patrick H. Kiser, Molly Boesel","doi":"10.3905/jsf.2022.1.135","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.135","url":null,"abstract":"An unexpected result of the COVID-19 pandemic was the resurgence of private-label securitization (PLS) in 2021. This article reviews the effect of the two-year pandemic on single-family mortgage volume and performance with a focus on PLS and a view into some of the lasting impacts. PLS issuance in 2021 was the largest since 2007, with four-fifths backed by prime jumbo and Alt-A non-QM product. Fast-rising home prices expanding the jumbo loan population and record low mortgage rates triggering a refinance boom and pay-off acceleration supported new issuance. Although borrower financial distress precipitated a spike in delinquency rates, delinquencies at the end of 2021 were generally below levels two years earlier except for long-term delinquency (more than fifteen months past due). PLS delinquency varies substantially across the nation, with states hit particularly hard by the pandemic, recession, and natural hazards having serious delinquency rates of more than 25% above the national level.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"27 - 37"},"PeriodicalIF":0.4,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45646529","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}
Adoption of fully electronic mortgages (eMortgages) jumped over the past few years. This study examines the reasons why adoption of eMortgages had lagged and why the market may currently be at a tipping point, moving toward a period of more rapid adoption. The study also examines industry-level productivity statistics to determine the extent to which this adoption has led—and could in the future lead—to faster processing speeds and thereby lower costs for lenders and borrowers. In prior research regarding technology adoption in financial services, there is a theme that cost advantage isn’t enough to promote adoption: It takes time to overcome institutional constraints, central counterparties need to adopt and accept the technology, and sometimes an external shock is needed to move things along. The COVID-19 pandemic has been such a shock for the mortgage industry, accelerating adoption of a number of digital processes.
{"title":"eMortgage Adoption: Acceleration through the Pandemic","authors":"Mike Fratantoni","doi":"10.3905/jsf.2022.1.134","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.134","url":null,"abstract":"Adoption of fully electronic mortgages (eMortgages) jumped over the past few years. This study examines the reasons why adoption of eMortgages had lagged and why the market may currently be at a tipping point, moving toward a period of more rapid adoption. The study also examines industry-level productivity statistics to determine the extent to which this adoption has led—and could in the future lead—to faster processing speeds and thereby lower costs for lenders and borrowers. In prior research regarding technology adoption in financial services, there is a theme that cost advantage isn’t enough to promote adoption: It takes time to overcome institutional constraints, central counterparties need to adopt and accept the technology, and sometimes an external shock is needed to move things along. The COVID-19 pandemic has been such a shock for the mortgage industry, accelerating adoption of a number of digital processes.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"12 - 26"},"PeriodicalIF":0.4,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44566091","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}
Historically, US house prices track key housing and economic factors such as housing starts, housing inventory, employment, interest rates, and consumer price indices, to name a few. During the past two years, the US economy has gyrated through myriad distortions resulting from the government’s various attempts to control the pandemic. Most recently, the administration has adopted policies that have further disrupted the economy, leading to increases in consumer prices and shortages of goods. We study the potential change in the connection between US house prices and key drivers before and after the onset of the pandemic. We take several approaches to this question, including studying cross-correlations of the multivariate time series, estimating a seasonal ARIMA model, and fitting seemingly unrelated regressions. Finally, we model house prices as a univariate time series. We find some evidence of a change in the association between house prices and other economic measures from before to after the covid response.
{"title":"Shifting Drivers for US House Prices","authors":"Francis Parisi","doi":"10.3905/jsf.2022.1.133","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.133","url":null,"abstract":"Historically, US house prices track key housing and economic factors such as housing starts, housing inventory, employment, interest rates, and consumer price indices, to name a few. During the past two years, the US economy has gyrated through myriad distortions resulting from the government’s various attempts to control the pandemic. Most recently, the administration has adopted policies that have further disrupted the economy, leading to increases in consumer prices and shortages of goods. We study the potential change in the connection between US house prices and key drivers before and after the onset of the pandemic. We take several approaches to this question, including studying cross-correlations of the multivariate time series, estimating a seasonal ARIMA model, and fitting seemingly unrelated regressions. Finally, we model house prices as a univariate time series. We find some evidence of a change in the association between house prices and other economic measures from before to after the covid response.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"48 - 57"},"PeriodicalIF":0.4,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47771649","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 United States faces a shortage of housing supply, estimated to be millions of units. This shortage is especially acute in the affordable sector. Although the causes of the supply shortage are many, we focus on one major set of constraints: financing. In particular, we focus on how to improve financing for the three types of affordable single-family housing where we see the most potential: manufactured housing (MH), accessory dwelling units (ADUs), and housing preservation. We argue that these financing issues constrain production; improving financing will grow consumer demand for affordable housing and preservation and prompt builders and manufacturers to respond by increasing supply. Finally, we try to quantify the potential impact in each of these areas to increase housing supply. Overcoming these financing hurdles would remove a major roadblock facing MH, ADU, and housing preservation and allow for the addition of a significant number of units of affordable housing supply.
{"title":"Improvements in Financing Could Increase the Single-Family Affordable Housing Supply","authors":"L. Goodman, Karan Kaul, Michael Neal","doi":"10.3905/jsf.2022.1.132","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.132","url":null,"abstract":"The United States faces a shortage of housing supply, estimated to be millions of units. This shortage is especially acute in the affordable sector. Although the causes of the supply shortage are many, we focus on one major set of constraints: financing. In particular, we focus on how to improve financing for the three types of affordable single-family housing where we see the most potential: manufactured housing (MH), accessory dwelling units (ADUs), and housing preservation. We argue that these financing issues constrain production; improving financing will grow consumer demand for affordable housing and preservation and prompt builders and manufacturers to respond by increasing supply. Finally, we try to quantify the potential impact in each of these areas to increase housing supply. Overcoming these financing hurdles would remove a major roadblock facing MH, ADU, and housing preservation and allow for the addition of a significant number of units of affordable housing supply.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"38 - 47"},"PeriodicalIF":0.4,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44678458","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}
After displaying resilience during the initial phase of the pandemic (in 2Q20) and recording stellar performance since 3Q20, the collateralized loan obligation (CLO) market has gained significant credibility, crossing the USD1tn size mark and experiencing widespread participation. Corporate earnings rebounded strongly after 2Q20 and are expected to continue to grow in 2022. However, there are a number of macro and industry-specific headwinds to watch out for. The CLO market also faces its next major challenge of transitioning away from the London interbank offered rate (LIBOR) regime. Although the newly mandated base rates resolve the issues LIBOR regulators wanted to correct, they bring a whole new set of challenges for the market. This article explores the current CLO market landscape, outlook for 2022, key macro challenges facing the market, LIBOR transition problem, and role of each participant in ensuring a smooth LIBOR transition.
{"title":"CLOs in Hypergrowth Mode, but LIBOR Transition a Near-Term Challenge","authors":"Alankar Ranade","doi":"10.3905/jsf.2022.1.131","DOIUrl":"https://doi.org/10.3905/jsf.2022.1.131","url":null,"abstract":"After displaying resilience during the initial phase of the pandemic (in 2Q20) and recording stellar performance since 3Q20, the collateralized loan obligation (CLO) market has gained significant credibility, crossing the USD1tn size mark and experiencing widespread participation. Corporate earnings rebounded strongly after 2Q20 and are expected to continue to grow in 2022. However, there are a number of macro and industry-specific headwinds to watch out for. The CLO market also faces its next major challenge of transitioning away from the London interbank offered rate (LIBOR) regime. Although the newly mandated base rates resolve the issues LIBOR regulators wanted to correct, they bring a whole new set of challenges for the market. This article explores the current CLO market landscape, outlook for 2022, key macro challenges facing the market, LIBOR transition problem, and role of each participant in ensuring a smooth LIBOR transition.","PeriodicalId":51968,"journal":{"name":"Journal of Structured Finance","volume":"28 1","pages":"74 - 87"},"PeriodicalIF":0.4,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48801268","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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