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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.

This paper aims to identify factors that affect agricultural mortgage default and prepayment.

Using a sample of farm credit system loans, prepayment and default are modeled as competing risks with potentially non‐stationary covariates using a statistical/econometric technique called survival snalysis (SA).

The analysis suggests that the primary drivers of prepayment and default are the rate of interest charged by the lender at origination and the borrower's current ratio at origination. Tests of the existence of a geographic effect indicate that despite bank management belief to the contrary, branches may not be homogeneous.

This analysis would be improved if more data were available in an easily obtainable manner to control for unobserved heterogeneity. Unobserved heterogeneity or incomplete specification within a model can be problematic. Inferences among regression coefficients can be problematic in that the estimates have inflated variances and unreliable test statistics. In addition, more frequent measures of the time‐varying covariates could be obtained to improve upon the SA models presented above. Future analyses could also incorporate other sections of the agricultural credit association portfolio, as well as a comparison to variable rate notes. One other logical next step would be to obtain loan collateral values to obtain estimates of the exposure at default, and the loss given default, or the estimates needed for the advanced internal ratings based approach described in the Basel Accords.

This paper provides a method for lenders to measure and model mortgage termination, an important consideration for risk managers when determining capital adequacy described in the Basel Accords.

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.

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.

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 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.

Interest only strips are created by stripping the interest portion of cash flows generated in mortgage‐backed securities or simply by servicing portfolios of mortgages. A number of financial institutions have significant amounts of mortgage‐servicing rights (MSR) which need to be delta (dynamic) hedged. Because MSR have a positive duration when prepayment effect is stronger than discount effect, it is possible to delta hedge a portfolio of MSR with other fixed income securities such that the value of the portfolio is not affected by increases or decreases in market rates. The purpose of this paper is to address this issue.

The paper develops the delta‐hedge‐ratio of MSR within a dynamic approach, using three different securities. To lower the cost of the delta hedge, the authors compare three hedge ratios dynamically, in order to obtain the portfolio that needs the least delta hedge.

The model enables the reduction of the amount of portfolio rebalancing and therefore reduces the cost of MSR portfolio hedging.

The paper develops the gamma‐hedge‐ratio function for each of the three securities. The lowest gamma corresponds to the hedged portfolio that needs the least re‐balancing.

This paper is innovative with the introduction of a delta‐hedge‐ratio function of interest and prepayment rates.

This paper aims to propose an Islamic compliant approach that deals with the prepayment rebate on debts resulting from cost-plus sales and their accompanied sale-based financing contracts. The proposed approach uses the time value of money concept without charging excessive fees from the debtor in the early settlement of debts.

The paper uses a qualitative analysis via analyzing and reviewing relevant literature. A quantitative analysis is subsequently used with a proposed computation that addresses prepayment rebate accompanied by debts resulting from cost-plus sales.

The proposed approach results in a rebate amount for the debtor greater than those rebate amounts resulting from either conventional finance techniques or current Islamic finance practices.

The application of the descending rebate proposed computation in this paper is restricted to cost-plus sale and their accompanied sale-based financing contracts only. The computation does not address any agreement or deal that may involve a rebate without a selling transaction.

The paper criticizes the prevailing practices for computing rebates in the case of debt prepayment, whether those nominated by conventional finance or others currently employed by most Islamic financial institutions. The paper also introduces a new rebate computation aimed to comply with Islamic finance's real context.

The purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This is done both for fixed-rate and floating rate loans under different assumptions on LGD modeling, prepayment, and discount rates.

This study provides exact formulas for lifetime expected credit loss derived analytically together with the mathematical proofs of each expression.

This articles shows that the formula most commonly applied in the literature for calculating lifetime expected credit loss is inconsistent with measuring expected loss based on expected discounted cash flows. Formulas based on discounted cash flows always lead to more conservative numbers.

For banks reporting under IFRS 9, the implication of this research is a better understanding of the different approaches used for computing lifetime expected loss, how they are connected, and what assumptions are underlying each approach. This may lead to corrections in existing frameworks to make applications of risk management systems more consistent.

While there is a lot of literature explaining IFRS 9 and evaluating its impact, none of the existing research has systematically analyzed the calculation of lifetime expected credit loss for this purpose and how the formula changes under different modeling assumptions. This gap is filled by this study.