Search results

In the USA, a substantial literature has emerged to investigate the prepayment behaviour of mortgage borrowers, using loan level data to identify the effects of borrower characteristics. This paper supplements the existing literature in three ways. First, the study looks for the first time at the prepayment behaviour of German mortgage borrowers. Second, it uses a unique Bauspar‐Loan data set consisting of over 55,000 Bauspar‐Loans paid off or prepaid between January 1998 and September 2000. Third, based on the special characteristics of the Bauspar‐Loan, it is possible to identify a portfolio optimizing behaviour as the driving force for prepayment.

The purpose of this paper is to generalize the one‐factor mortgage‐backed securities (MBS)‐pricing model proposed by Kariya and Kobayashi to a three‐factor model. The authors describe prepayment behavior due to refinancing and rising housing prices by discrete‐time, no‐arbitrage pricing theory, making an association between prepayment behavior and cash flow patterns.

The structure, rationality and potential for practical use of our model is demonstrated by valuing an MBS via Monte Carlo simulation and then conducting a comparative static analysis.

The proposed model is found to be effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

While the one‐factor valuation model Kariya and Kobayashi treated is a basic framework, the generalized model presented in this paper is much more effective for analysing MBS cash flow patterns, making a decision for bond investments and risk management due to prepayment.

A distinctive feature of mortgages as assets is the existence of prepayment risk, typically viewed as a borrower’s call option to pay the outstanding mortgage balance at any time during the term. While previous research identified important causes for prepayment, these studies are mostly based on fixed‐rate mortgages, with little work on variable‐rate or floating‐rate mortgages and even less work on prepayment in countries other than the USA. This paper presents an analysis of prepayment based on the historical aggregate pre‐payment experience of a sample of variable rate mortgages in Hong Kong, which func‐tions under a Currency Board Mechanism that determines exogenously the level and term structure of interest rates. With variable rate mortgages, it is expected that there will not be a prepayment incentive with decreases in interest rates, unlike the case with fixed‐rate mortgages. However, we argue that observed interest rate movements remain a key factor that affects prepayment decisions, because current interest changes influence expected future interest rates. Furthermore, drawing on quasi‐rational and behavioral economics concepts, we expect the effect on prepayment of expected upward movement in interest rates to be stronger than that of expected downward movements. Empirical evidence from the adjustable rate residential mortgage sample from Hong Kong supports these expected relationships.

There exists a large volume of literature evaluating the mortgage prepayment risk based on the USA's and other developed countries' experiences. With access to detailed loan‐level data provided by a national mortgage lender in China, the purpose of this paper is to revisit the empirical question of the determinants of mortgage prepayment probability.

The paper utilizes unique loan‐level data from a large national residential mortgage lender in China to provide insights into borrowers' prepayment behavior in China under recent market conditions, focusing on the customers' behavior and the segmentation analysis of the prepayment risk.

The results from a logit model indicate that housing appreciation rate and the stock market performance are important considerations for Chinese borrowers. It was also found that borrowers show the heterogeneous prepayment behavior in different groups. For instance, households who purchase new houses are less sensitive to the LTV ratio. These findings provide empirical support for the risk management in the rapid growing mortgage market in China as well as those in other transitional economies.

Because of the lack of the literature in the immature mortgage markets, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further using their own datasets.

The paper includes implications for policy makers to further strategic decision making using a quantitative framework which has not been fully developed in most of the state‐owned banks in China.

This paper has contributed to the analysis of Chinese mortgage prepayment pattern using a large recent micro‐loan level data set. As mortgage borrowers' behavior can be country specific due to the differences in housing policies and housing market structure, this paper sheds new light on the driver factors determining mortgage prepayment in China's mortgage market.

Unlike most residential mortgage‐backed securities, Farmer Mac agricultural mortgage‐backed securities (AMBS) have prepayment penalties. To quantify the impact of prepayment penalties on the cost of funding loans, prepayment behavior, and AMBS value, an analytic AMBS model is developed and numerically solved using pathwise simulation and dynamic programming. The results suggest prepayment penalties currently being used by Farmer Mac reduce AMBS yields considerably relative to not charging prepayment penalties. Presumably, lower yielding AMBS imply more competitive loan pricing. Even with prepayment penalties in place, however, it can be advantageous for profit‐maximizing mortgagors to optimally prepay or even default on agricultural mortgages. The model is used to quantify prepayment and credit risk by valuing the embedded options in mortgages, namely, the right of the mortgagor to prepay and to default.

This research analyzes borrowers' credit utilization through prepayment behavior in peer-to-peer (P2P) lending. The authors investigate factors influencing the decision to prepay and assess the role of P2P lending as an alternative source of consumer credits.

The authors use individual loan-level data from the LendingClub, one of the largest P2P platforms in the USA. The authors use a Logit model and a sample selection model estimated by the two-stage Heckman method. The empirical analysis considers borrower-specific and loan-specific characteristics as well as macroeconomic factors.

The authors present a number of significant findings that can enhance understanding consumers' financing decisions. The authors offer evidence that borrowers are able to take advantage of cheaper loans offered by P2P lending to better manage credit card balance and consolidate debt. The authors find that borrowers tend to prepay P2P loans quickly when the aggregate cost of borrowing is low, suggesting that P2P lending offers an efficient alternative to obtain credit. This is particularly true for creditworthy borrowers that are able to take advantage of competing sources of finance. The authors' results provide evidence that P2P lending can improve consumers' optimal credit utilization.

P2P lending has grown exponentially and has become a significant credit supplier to consumers and small businesses. While the existing literature mostly focuses on default risks, prepayment has received much less attention. This research fills in the gap and investigates borrowers' prepayment behavior in P2P loans and the role of P2P lending as an alternative source of consumer credits.

The purpose of this paper is to identify effects of prepayment risk on performance of commercial banks in the USA. Understanding how various risks impact banks' performance can help to improve performance of financial institutions and better estimate risk premia charged by banks on the loans they extend to their customers.

The paper measures the prepayment risk premium and aims to gauge its effect on various ratios that measure bank performance. Since, risk management is an important goal of financial management, it is important to learn how prepayment risk pertains to bank performance.

The results of this paper suggest that prepayment risk may significantly impact return on loans, return on equity and real estate loans to total loans ratios of various commercial banks. The impacts, in terms of strength and direction, vary between the periods of pre‐ and post‐passage of the Financial Institutions Reform and Recovery Act. The results indicate that the addition of prepayment risk variable to regression models can generally increase their ability to explain bank performance metrics.

To the authors' knowledge, there is no existing literature that gauges the impact of prepayment risk on various components of bank performance. There is existing literature that shows that bank stocks move in response to prepayment risk.

Prepayment risk is a key concern in securitized real estate. Using repeat sales in transaction data to proxy for holding period and prepayment, this paper provides the first rigorous analysis of residential mortgage prepayment in Singapore. The prepayment rate for new condominiums is increasing in the holding period and exhibits spikes in the fourth and sixth years. The likelihood of observing a subsequent sale and the prepayment rate increases in floor level, sentiment and other investment return, but decreases in floor area and mortgage rate hikes. Appreciation in the property price also tends to increase the probability and rate of prepayment. In contrast, owners of larger property units and HDB upgraders are less likely to resell their properties. The evidence also suggests that the likelihood of prepayment is lowered after the anti‐speculation measures were introduced in May 1996.

This paper examines how the macroeconomic environment affects the determinants of prepayment of mortgage loans from October 2004 to February 2020. For more accurate analysis, the authors define the timing of prepayment not only before the loan maturity but also at the time when 50% or more of the loan principal is repaid. The results show that, during the global financial crisis as well as the recent period of low interest rates, macroeconomic variables such as interest rate spreads and housing prices have a different effect compared to the normal situation. Also, significant explanatory variables, such as debt to income (DTI) ratio, loan amount ratio and poor credit score, have different effects depending on the macroenvironment. On the other hand, in all periods, the possibility of prepayment increases as comprehensive loan to value (CLTV) increases, and the younger the age, the shorter the loan maturity. The results suggest that, in the case of ultralong (40 years) mortgage loans recently introduced to support young people purchasing houses, the prepayment risk can be, at least partially, migrated by offsetting the increase in prepayment by young people and the decrease in prepayment due to long loan maturity. In addition, this study confirms that the accelerated time failure model compared to the logit model and COX proportional risk model has the potential to be more appropriate as a prepayment model for individual borrower analysis in terms of the explanatory power.

As financial markets move toward increased globalization, it becomes worth considering whether inherent differences in financial markets across different countries will diminish. For two countries more similar than different in terms of geography, location, government and culture, Canada and the USA remain strikingly different in terms of housing finance. Public policy objectives toward housing followed quite different paths over the past 70 years and fundamental differences in banking practices have led to considerably different outcomes in terms of mortgage finance instruments in the two countries. Examines some of the differences in policy and in competitive practices between Canada and the USA in an attempt to illuminate why differences in rates and terms across the two countries still exist. While a part of the difference remains due to legal constraints concerning the finance of the domestic housing sector, focuses on the economics and public policy choices that have led to the observed differences rather than on an analysis of the legal structure.