Commercial Mortgage-Backed Securities: Prepayment and Default

One of the major developments in real estate finance during the 1990s was the emergence of a viable market for commercial mortgage backed securities. The growth in this market has spurred greater interest in empirical and theoretical research on commercial mortgage default and prepayment. We employ a competing risks model to examine the default and prepayment behavior of commercial loans underlying CMBS deals. We find that changes in the yield curve have a direct impact on the probability of mortgage termination. Furthermore, we do not find any statistical relationship between LTV and prepayment or default.     

Valuation of Residential Mortgage-Backed Securities with Default Risk Using an Intensity-Based Approach

This paper develops a valuation model for fixed-rate mortgages, mortgage pools, and residential mortgage-backed securities (RMBS's) using an intensity-based approach. This model incorporates full prepayment, partial prepayment, and default in valuing a mortgage. Full prepayment is further classified into “refinancing” and “sale of a house” depending on the reason. The time of occurrence of each of these three types of prepayment and default is modeled as the first jump time of a Cox process. Under these conditions, the valuation formula for a mortgage as well as a partial differential equation (PDE) that the mortgage value satisfies is provided. As for implementation of the model, the short-term riskless interest rate and the house price are adopted as state variables. Each intensity process is specified in a manner that allows a jump in intensity depending on the state variables and the borrower's incentive for prepayment or default. Through such specifications, it is shown that our model has characteristics similar to some structural models in previous literature. As for the numerical method for valuation, we propose a simple backward induction technique on a tree instead of the commonly used Monte Carlo method. Additionally, the method for estimating the model is discussed, and the results of numerical simulations are reported.This paper represents the view of the author and does note necessarily the views of the Mitsubishi UFJ Securities Co., Ltd. or members of its staff.     

Valuation of Mortgage-Backed Securities Based upon a Structural Approach

This paper studies the valuation of mortgage-backed securities (MBS) based upon a structural approach of several risks involving the prepayment and/or default behavior of mortgagors. For the Kariya and Kobayashi (1999) model using a time-consuming Monte-Carlosimulation, we provide an alternative semi-analytic valuation methodology closely related to solving the (Volterra type) integral equation with respectto the first hitting time density for a curved/flat boundary; consequently that enables us to calculate the MBS price faster and more precisely. Next, to capture the path-dependent prepayment behavior of the interest ratemovements we give some prepayment models based upon a two-dimensional Markov process of the interest rate and its long-run average rate. Third, we study the simultaneous assessment issue of prepayment and defaultrisks, encountered in practice.Finally we discuss the calculation of the joint probability density ofmultiple first hitting times.     

Analyses of Mortgage-Backed Securities Based on Unobservable Prepayment Cost Processes

We propose a prepayment model of mortgage based on a structural approach in order to analyze prepayment risk of mortgage-backed securities (MBS). We introduce a continuous process named prepayment cost process. Specifically, each mortgager's prepayment time is defined by the first time when her or his prepayment cost process falls below zero, but prepayment cost processes are supposed to be unobservable in the market. We also introduce a risk unique to each loan pool of mortgages, called a loan pool risk (LPR), and we regard LPR as a systematic risk other than interest rate. Using the model, we discuss the conditional distribution of prepayment times and a risk-neutral valuation of pass-through MBS. It is shown that each mortgager's conditional non-prepayment probability and the posterior distribution of LPR play quite important roles in our study.This research is partially supported by Grant-in-Aid for Young Scientists (B) No. 16710108 from the Ministry of Education, Culture, Sports, Science and Technology.     

The prepayment option on mortgage securities: A random coefficient approach

Using the Swamy (1970) model for pooled data and a Hildreth and Houck (1968) model for individual securities, this article investigates whether the parameters describing the prepayment behavior of the fixed-rate debt underlying mortgage-backed securities are better estimated as a stochastic behavior. Empirical results indicate that differences between securities are random. The Hildreth and Houck model yields additional information on randomness over time. The use of the aggregate data to estimate prepayment of individual securities, as opposed to use of the prepayment history of the individual security, may yield more reliable results.     

Nonparametric Smoothing of Yield Curves

This paper proposes a new nonparametric approach to the problem of inferring term structure estimates using coupon bond prices. The nonparametric estimator is defined on the basis of a penalized least squares criterion. The solution is a natural cubic spline, and the paper presents an iterative procedure for solving the non-linear first-order conditions. Besides smoothness, there are no a priori restrictions on the yield curve, and the position of the knots and the optimal smoothness can be determined from data. For these reasons the smoothing procedure is said to be completely data driven. The paper also demonstrates that smoothing a simple transformation of the yield curve greatly improves the stability of longer-term yield curve estimates.     

Anatomy of a Fair Lending Exam: The Uses and Limitations of Statistics*

In this paper, we examine how statistical analysis is used to help conduct fair lending compliance examinations. We present a case study of an actual fair lending examination of a large mortgage lender, illustrating how statistical techniques are used to focus examiner efforts. Our case also highlights the limitations inherent in statistical analysis of discrimination. The study suggests that statistical analysis and the more-traditional comparative file reviews complement one another in the overall examination process, offsetting some of the limitations inherent in each.     

Estimating Outage Costs in China: A Modified Tobit Model

The electric power shortages in China the period from 2002 to 2007 had pervasive effects. How to measure the economic costs of power shortages becomes one of the central questions of interest to regulators, industrial users, and investors. The current study estimates the objective outage costs to industrial users using an adjusted Tobit model and survey data on 812 firms in six provinces in China during 2002–5. Empirical results show that objective outage costs are higher than the willingness to pay to avoid outages, but are lower than the willingness to accept to accept outages, implying that firms are loss averse.     

中国期货市场与股票市场量价关系比较——基于分位回归法的研究

运用分位回归方法分别对连豆期货与上证指数各自的量价关系进行准确刻画,并检验了各自量价关系的对称性。实证结果表明,连豆期货具有关于零收益率对称的"V"型量价关系,上证股指具有关于零收益率非对称的"V"型量价关系。缺乏做空机制是导致量价关系非对称的原因。中国股市含有一定的非理性成份,建议引入做空机制。     

Mortgage Choice in the Euro Area: Macroeconomic Determinants and the Effect of Monetary Policy on Debt Burdens

This paper provides novel evidence on the role of the macroeconomic environment for households’ choice between fixed‐interest‐rate and adjustable‐interest‐rate mortgages (ARMs) in the euro area. We find that relatively more ARMs are taken out when economic growth is strong, the interest rate spread is high, or unemployment shows low volatility. A simulation exercise shows that a reduction in mortgage rates as witnessed during the monetary easing in the course of the global financial crisis produces a substantial decline in debt burdens among mortgage‐holding households, especially in countries where households have higher debt burdens and a larger share of ARMs.     

基于分位数回归模型的经济因素影响传媒产业发展研究

依据灰色关联分析技术,运用分位数回归模型,考量中国传媒产业发展处于不同分位水平时经济因素对其发展的影响。结果表明,市场化程度与中国传媒产业发展的关联度最大,科技进步贡献率与中国传媒产业发展的关联度较低;在中国传媒产业发展水平不断提升过程中,市场化程度贡献率呈U型态势,文体广播财政支出贡献率以及科技进步贡献率呈持续上升态势;而GDP的增加与传媒产业发展水平的增长呈负相关关系,中国传媒产业发展水平增长速度滞后于区域GDP增长速度。     

中国城镇正规就业与非正规就业的工资差异演变研究——基于非条件分位数回归的分解方法

基于CHNS历次调查的数据资料,利用非条件分位数回归与分解方法,实证研究1989-2011年三个时期中国城镇正规就业与非正规就业的工资差异问题.研究表明:(1)两个就业群体间的工资差距在不断扩大,正规就业的个体禀赋优势在工资决定中发挥了关键作用;(2)正规就业与非正规就业的工资差距存在不对称性现象,且在工资分布的末端表现明显,符合"黏地板效应",而造成这一现象的主要原因在于低收入群体存在较为严重的市场分割和就业歧视;(3)由个体禀赋所解释的特征差异呈现上升趋势,而由非市场因素解释的参数差异则在不断下降,反映出我国劳动力市场在整体上趋于公平和完善,工资的决定机制更加以市场为导向.     

中国产业结构优化升级引致的城镇化效应研究——一个省级面板分位数模型的实证检验

基于2000～2011年我国省级面板数据,采用面板分位数计量模型考察了产业结构引致的城镇化效应。研究发现,第三产业份额的估计参数显著为正,说明产业结构优化带来的城镇化效应是存在的。同时,这种效应对于处于不同分位数上的地区有较大差异:第三产业份额适中的省(市、自治区),城镇化效应最为明显;第三产业份额相对过高或过低的省(市、自治区),产业结构优化带来的城镇化效应较弱,估计参数呈现"两头小、中间大"的结果,显著、稳健为"倒U型"结构。     

Bank Liability Structure,FDIC Loss,and Time to Failure: A Quantile Regression Approach

Deposit insurers are particularly concerned about high-cost failures. When the factors driving such failures differ systematically from the determinants of low- and moderate-cost failures, a new estimation technique is required. Using a sample of more than 1,000 bank failures in the U.S. between 1984 and 2003, I present a quantile regression approach that illustrates the sensitivity of the dollar value of losses in different quantiles to my explanatory variables. These findings suggest that reliance on standard econometric techniques results in misleading inferences, and that losses are not homogeneously driven by the same factors across the quantiles. I also find that liability composition affects time to failure.

Effects of Firm Size,Financial Leverage and R&D Expenditures on Firm Earnings: An Analysis Using Quantile Regression Approach

As documented in the literature, the effects of firm size, financial leverage, and R&D expenditures on firm earnings are inclusive. Our hypothesis is that the inconsistent empirical results of such effects may be driven by the regression models implemented in data analysis. Using the quantile regression (QR) approach developed by Koenker and Basset (1978), this study analyses S&P 500 firms from 1996 to 2005. We find that the effects of firm size, financial leverage and R&D expenditures on firm earnings differ considerably across earnings quantiles. Comparing the results from the QR approach with those from the ordinary least squares (OLS) and least absolute deviation (LAD) methods, this study further explains the puzzling relationship between firm size, financial leverage, R&D expenditures and firm earnings.     

Terror attacks and stock-market fluctuations: evidence based on a nonparametric causality-in-quantiles test for the G7 countries

We use a novel nonparametric causality-in-quantiles test to study the effects of terror attacks on stock-market returns and volatility in G7 countries. We also use the novel test to study the international repercussions of terror attacks. Test results show that terror attacks often have significant effects on returns, whereas the effect on volatility is significant only for Japan and the UK for several quantiles above the median. The effects on returns in many cases become stronger in terms of significance for the upper and lower quantiles of the conditional distribution of stock-market returns. As for international repercussions, we find that terror attacks mainly affect the tails of the conditional distribution of stock-market returns. We find no evidence of a significant cross-border effects of terror attacks on stock-market volatility, where again Japan and the UK are exceptions as far as terror attacks on the US are concerned. Finally, our results continue to hold following various robustness checks involving model structure, lag-lengths and possible omitted variable bias.     

US Fiscal Sustainability and the Causality Relationship between Government Expenditures and Revenues: A New Approach Based on Quantile Cointegration

This paper first aims to reinvestigate the issue of US fiscal sustainability by using the quantile cointegration approach proposed by Xiao (2009 and 2012). Our empirical evidence indicates a quantile‐dependent cointegrating relationship between government expenditures and revenues. In addition, this paper examines the long‐run causality relationship between expenditures and revenues by using the vector error‐correction (VEC) model with coefficients based on the different quantiles. Findings from the long‐run Granger‐causality analyses support the spend‐and‐tax hypothesis. Our investigation suggests that the government should show more discretion in increasing expenditures in the long run. Moreover, budget deficit reduction can only be achieved through reductions in government expenditures.