Prepayment Rates Research Articles

A mortgage valuation model: a tale of two equations

ABSTRACT In the Journal of Financial Economics, Gerardi, Willen, and Zhang (2023) examine the relationship between prepayment rates, race, and monetary policy. In this article, we identify an anomaly in GWZ‘s valuation equation that relates to the effect of prepayment rates on the ratio of market price to initial loan balance. We then show the mathematical steps to correct this anomaly.

Survey on Mortgage-Backed Securities Prepayment Risk Using Machine Learning Models

Mortgages allow for partial or complete prepayment at any time prior to the loan's maturity date. A mortgage prepayment is risky for the lending institution because it eliminates the borrower's obligation to pay future interest and complicates the steps required for refinancing the mortgage loan. Prepayment risk is a threat to mortgage-backed securities (MBS) that arises when borrowers pay down their mortgage principal more quickly than expected. For MBS investors, this means lower cash flows. A negative impact on cash flows and exposure to extension risk could result from actual prepayment rates being higher or lower than expected.

An Application of Interest Rate Models to RMBS and SME Conditional Prepayment Rates and CPR Time Series Analysis

An Application of Interest Rate Models to RMBS and SME Conditional Prepayment Rates and CPR Time Series Analysis

Pricing quantitative model design of distribution network assets REITs products and ABS products

Abstract In recent years, the development of asset securitization in China has maintained a rapid growth pattern. The raised funds will be used to support enterprises in power grids or related industrial chains to obtain financial equivalent services. Reasonable pricing of distribution network assets REITs, ABS products and other financial products related to distribution network assets is an important auxiliary means to establish asset guarantee. The research of quantitative distribution network asset valuation model provides a good theoretical and working support for solving the reasonable pricing problem of distribution network assets. This paper will focus on the theoretical basis and related methods of quantitative model design for REITs products and ABS products from the perspective of distribution network assets. The results show that asset prices fluctuate at the 1% level for every 1% change in default rate when the prepayment rate is unchanged. The results show that the price of ABS products is more sensitive to the change of prepayment rate.

Irreversible investment with random delay and partial prepayment

Classical irreversible investment problem admits an optimal strategy of threshold type. But there is no consensus on how the investor should adjust the threshold, if there is an implementation delay. By formulating a general problem with random delay and partial prepayment, we find that the effect of delay can be opposite for different prepayment rates. Besides, although the constant delay model is commonly used, we argue that it is a reasonable approximation only if the discount rate is small.

Servicer Influence on Mortgage Prepayments

Investors in the mortgage-backed securities market have long tiered pools based on the servicer concentration in the pool. The tiering is largely due to observed prepayment differences among servicer, servicer type (bank versus non-bank), and origination channel (retail, correspondent, or broker). We examine the influence of the servicer on prepayment rates and differentiate between bank and non-bank servicers. Further, the origination channel also influences mortgage prepayment rates.

A prepayment-risk-neutral pricing model for mortgage-backed securities

In this paper, we investigate a pricing model for mortgage-backed securities (MBSs) of a pay-through type of collateral mortgage obligation (CMO), embedded call options, which can be exercised by the intermediary, and pass-through MBSs. We suggest a prepayment-risk-neutral pricing model, applying a reduced-form prepayment rate model, and then compute and investigate the appropriate prices and spreads in the coupon rates between CMOs and PT MBSs. We believe that this study contributes in that it provides a sophisticated pricing model for MBSs, especially to the financial markets which are not advanced enough to finance with a simple type of MBSs.

Research on Interest Rate Risk of Housing Mortgage Loan Based on Computer Simulation.

In recent years, with the rapid increase of the business volume of housing mortgage loans of commercial banks, the risk of prepayment is increasingly exposed. Prepayment will have a great impact on the duration and convexity of housing mortgage loans of commercial banks and then bring difficulties to the asset liability management of banks. Therefore, empirical research on the changes of duration and convexity of housing mortgage loans caused by prepayment when the market interest rate changes is of great significance for commercial banks to manage interest rate risk exposure. Based on the analysis of the option characteristics of prepayable housing mortgage loan, the CIR model with GARCH(1, 1) is selected to describe the interest rate change path, and the computer simulation method is used to calculate OAS and then calculate the effective duration and effective convexity of housing mortgage loan under different prepayment rates, so as to understand the interest rate risk of housing mortgage loan in the presence of embedded option.

Impact of government budget on health prepayment levels: evidence from OECD countries.

Health prepayment, a key indicator under the Sustainable Development Goals monitoring framework, is strongly associated with household financial protection; however, the impact of government health budget on the level of prepayment has rarely been discussed. To address the following research questions. (1) Does a higher government health budget translate into higher prepayment rates in the healthcare financing system? (2) What are the effects of government health budget on public prepayment and private prepaid plans? (3) What are the heterogeneities between groups of countries with different income levels and public health prepayment systems? Analysis of panel co-integration, impulse response function, and variance decomposition were conducted in 34 Organisation for Economic Co-operation and Development (OECD) members for the period 1995-2016. Government health budget has a long-running equilibrium relationship with the level of public and total prepayment. However, a stable relationship could not be confirmed with private prepaid plans. Moreover, government health budget played a significant positive role in explaining the fluctuations in the total and public prepayments over a long time, that is, 51 and 37 periods, respectively. Considering differences between groups of countries, the impacts are greater for those with higher income levels and more public-dominated health-financing systems. Government health budget has a long-time relationship with the levels of both total prepaid expenditure and public prepayment. By contrast, it does not systematically crowd out private prepaid plans.

A Neural Network Approach for the Estimation of Mortgage Prepayment Rates

A Neural Network Approach for the Estimation of Mortgage Prepayment Rates

Flood Damage and Mortgage Credit Risk: A Case Study of Hurricane Harvey

Using a unique, loan-level database that combines post-disaster home inspection data, flood zone designations, and loan performance measures in the area impacted by Hurricane Harvey, we examine the link between property damage, flood insurance, and mortgage credit risk. We find that compared with homes with no damage, loans on moderately to severely damaged homes are more likely to become 90 days delinquent shortly after Harvey. However, longer-term loan performance depends on whether the property is located in areas where borrowers are required to have flood insurance. Where flood insurance is required, loan prepayment rate rises with property damage. In areas where flood insurance is not required, and very few borrowers have flood insurance, we find that as property damage increases, the likelihood of needing a loan modification increases, as does the likelihood of a loan being 180 or more days delinquent or in default during the two years following Hurricane Harvey. Thus, our findings provide direct evidence that flood insurance protects homeowners and mortgage creditors against credit risk arising from flood events.

머신러닝 알고리즘을 이용한 MBS 조기상환율 예측

머신러닝 알고리즘을 이용한 MBS 조기상환율 예측

주택담보대출 중도상환수수료가 MBS 조기상환율에 미치는 영향

본 연구는 국내 주택금융시장을 대상으로 주택담보대출에 부과하는 중도상환수수료가 차입자의 조기상환 행태에 미치는 영향을 분석하였다. 주택담보대출 차입자는 일정기간 이내에 대출금을 상환하는 경우 중도상환수수료를 부담하여야 하므로, 중도상환에 따른 패널티는 차입자의 조기상환결정에 영향을 미칠 수 있다. 즉, 중도상환수수료는 주택담보대출의 조기상환과 일련의 관련성이 존재할 가능성이 있다.BR한국주택금융공사에서 2004년 6월부터 2018년 6월까지 발행한 MBS를 대상으로 월별 조기상환율 자료를 이용한 주요 분석결과를 요약하면 다음과 같다. 첫째, 향후의 시장금리 하락에 따른 이자비용 절감효과가 중도상환수수료를 보전하기에 충분한 효익이 존재하는 경우 차입자의 조기상환은 증가하였다. 둘째, 정책모기지의 중도상환수수료 부과체계가 전면적으로 개편된 2012년 10월 이후에 발행한 MBS의 경우에는 조기상환이 유의적으로 높게 나타났다. 셋째, 중도상환수수료 수준이 높은 기간일수록 차입자의 조기상환율은 감소하는데 이는 특히 2012년 규정변경 이후에 발행한 MBS 에서 강건한 결과를 보였다.BR전체적으로 중도상환수수료 수준 또는 수수료 부과체계는 주택담보대출 차입자의 조기상환에 일련의 영향을 미치는 것으로 판단된다. MBS 가격결정에 있어 조기상환율 예측은 중요한 요인으로 작용한다. 따라서 향후 중도상환수수료 규정을 변경한다면 해당 특성도 고려하여 조기상환율을 추정할 필요성이 있는 것으로 판단된다.

Impact of Early Repayment Risk on Domestic MBS Basic Assets

It is important to reconfirm the existing relationship between previously studied economic variables and early repayment rates and to identify additional variables that increase the explanatory power of the model. The purpose of this study is to investigate the relationship between premature repayment rate and influence variables, and then analyze the dynamic relationship between prepayment rate and influence variables by constructing a Vector Auto Regression (VAR) model. The variables analyzed to affect prepayment rates in this study were construction and positive macroeconomic events, especially inflation. As a result of the analysis of variance analysis, mortgage interst rate was the most influential variable for early repayment rate. This suggests that interest rate policy should be effective in the short-term, and in the mid- to long-term, if the MBS price or market is abnormal, it should be responded to by changing the policy related to the construction industry.

Mortgage Prepayment, Race, and Monetary Policy

This paper documents large differences in mortgage prepayment behavior across racial and ethnic groups in the United States, which have significant implications for monetary policy, inequality, and pricing. Using a novel data set that combines administrative data on mortgage performance with information on race and ethnicity, we show that Black and Hispanic white borrowers have significantly lower prepayment rates compared with Non-Hispanic white borrowers, holding income, credit score, and equity constant. This gap is on the order of 50 percent and largely reflects different sensitivities to movements in market interest rates, and was particularly pronounced during QE1. Differences in prepayment speeds result in large disparities between white and minority borrowers in the distribution of rates paid on outstanding mortgages, which widens during periods of low mortgage rates and high refinance volumes. From 2010 to 2014, Black borrowers were paying 30 to 45 basis points more on average than Non-Hispanic whites despite only a small gap of about 5 basis points between the groups at the time of mortgage origination. The large differences in prepayment behavior have important pricing implications, as they suggest that minority borrowers are overpaying for their prepayment option. Our results show that inequality in mortgage markets is larger than previously realized and is exacerbated by expansionary monetary policy.

On the Comprehensive Balance Sheet Stress Testing and Net Interest Income P/L Attribution

The joint stress testing of net interest income interest rate risk and profit and loss from behavioral risks on a multi-horizon scenario path poses great challenges in enterprise stress testing and earnings risk attributions. We propose a framework for granular level stressed net interest income calculation and P/L attribution. The proposed framework can accommodate net interest income impact from interest rate risk, profit and losses from behavioral risks e.g. prepayments and credit defaults as well as facility and deposit contingent drawdowns at each horizon on a given scenario path. Our net interest income framework uses the matched maturity asset and liability concept to synthetically separate the loan origination risks and the Treasury strategic funding risks. It considerably simplifies the joint market and credit risk stress testing by focusing on the asset versus maturity matched liability net interest income on the asset side and the maturity matched asset versus actual liabilities cash flows on the Treasury side. In this framework there is no need for exact cash flow generation on the asset side. The focus is on the loan net interest income process which requires only the outstanding balance. The loan net interest income process is a stochastic process with behavioral events. At the time of the events, the net interest income process regime-switches to capture the event impact e.g., credit loss or prepayment with associated interest rate impact. The event based net interest income process is suitable for loan-level behavioral state path simulation models with competing risk. We also consider the corresponding net interest income process with conditional default and prepayment rate models. The obtained net interest income process can be applied to both loan-level models as well as pools of homogenous loans. We illustrate the framework with competing hazards and state transition models.

Refinance Incidence and Information Loss in Predicting Prepayment Risk

This paper uses loan-level data to investigate heterogeneity in loan prepayment incidence, and argues that refinancing is affected by a mortgage pricing convention that underestimates co-borrowers' actual creditworthiness. Specifically, we find a substantial difference in prepayment incidence between sole borrowers and co-borrowers. We also find this difference to vary across sub-sets of co-borrowers in a predictable manner. To address endogeneity concerns, we exploit the variation across time in mortgage rates to confirm that the difference in prepayment incidence exists only during a period of declining mortgage rates. At an aggregate level, we find that geographic areas with higher concentration of co-borrowers are having a higher prepayment rate. These results are directly relevant to the valuation of mortgage-backed securities by offering an additional explanation for the observed variation in refinancing decisions that is related to institutional aspects of the loan process.

The Three-Factor Hedging Strategy for Mortgage Pass-Through Securities: Empirical Evidence

The mortgage pass-through securities sector of the investment-grade bond market is attractive to institutional investors seeking to outperform a bond index without taking a view on credit risk. Market participants view this sector as being less price efficient than the other investment-grade bonds sectors, offering opportunities within the sector to take contrary positions relative to prevailing prices, particularly with respect to future prepayments. In executing a relative value strategy to enhance returns in this sector, portfolio managers must be able to remove interest rate risk. Unlike hedging interest rate risk in the other sectors of the investment-grade bond market, the cash flow structure of mortgage pass-throughs is such that there is interest rate exposure, via prepayment rates, due to a change in the term structure of interest rate. Both academics and practitioners have proposed several strategies for hedging interest rate risk. In this article, the authors evaluate a three-factor hedging strategy for agency pass-throughs, comparing the performance of this strategy to both the single-factor and two-factor hedging strategies. Their analysis finds that under certain conditions the three-factor hedging strategy outperforms both the one- or two-factor hedging strategy.

Assessing determinants of health care prepayment in China: Economic growth or government willingness? New evidence from the continuous wavelet analysis.

Significant prepayment of health care is a crucial factor to ensure that all individuals have access to effective health services at affordable prices. The research questions we address here are as follows: What role does economic growth play in changing the level of health care prepayment? Does government's willingness to spend more on health mean higher prepayment rates in the health financing system? What are their dynamic relationships? These questions are addressed in China over the 1978 to 2014 period by employing the continuous wavelet analysis. We focus in particular on their correlations and lead-lag relationships across different frequency bands. Our findings clearly show that overall government willingness has a positive effect on health care prepayment level, while the impact of economic growth varies in the time-frequency domain. This variation could be demonstrated in 1980 to 1998, when the positive correlation between economic growth and health care prepayment level in the short term turned negative in the medium and long term, which indicated that China could not achieve mutual development of economic growth and social welfare within the market-oriented health system. Notably, the time-varying analysis indicates that China's new round of medical system reform since 2006 plays an important role in changing the correlations and lead-lag relationships. In particular, health care prepayment tended to lead government willingness during the 2006 to 2012 period since the increase of health subsidies and expenditures strengthened government responsibility over the health sector, and there existed a persistent mutual stimulation between economic growth and health care prepayment level across all frequency bands along with the reform.

A New Hedonic Method for Measuring Mortgage Default Risk

Measuring and monitoring the true level of mortgage delinquencies across an economy is essential for asset pricing and financial system stability. Yet public measures of mortgage default risk almost always use simple averages across pools of individual assets, including balance-sheet loans or indices tracking default risk across portfolios of residential mortgage-backed securities (RMBS). These approaches are, like median house price indices, afflicted by compositional biases that can lead to spurious inferences regarding the direction of default rates. Sources of bias include artificial changes in default rates attributable to: increases in the volume of new loans being written or (securitised RMBS added to indices); changes in the proportion of transactions with higher loan-to-value ratios (LVRs); the introduction of less seasoned RMBS transactions with a lower weighted-average loan age; and/or shifts in borrower characteristics that have higher probabilities of default (e.g. tilts towards investment borrowers). To address this problem, we have developed the first known hedonic regression-based indices of empirical mortgage default risk that explicitly control for compositional biases through the models’ characteristic-based independent variables. Whereas simple average measures of default rates across securitised loan portfolios have declined in recent years, which suggests that the risk of loss has been falling, our hedonic mortgage default index implies exactly the opposite: that is, compositionally-adjusted default rates have, in fact, been increasing sharply in recent times. In addition to delinquency rates, we apply similar hedonic regression techniques to create a compositionally-adjusted index for RMBS prepayment rates, which shows a sharp decline in prepayments from 2017 to late 2018.