V. Carlos Slawson

Valuing Prepayment and Default in a Fixed‐Rate Mortgage: A Bivariate Binomial Options Pricing Technique

This paper uses a bivariate binomial options pricing technique to value the prepayment and default options in a fixed-rate mortgage. The American style options are dependent on two stochastic variables: (1) house price, (2) one year spot rate. The paper uses the standard lognormal process for house price and the CIR square-root process for interest rates. By forcing the two underlying state variables to undergo transformations, two new uncorrelated variables with constant volatilities are established. With constant volatilities, a computationally simple bivariate binomial tree is formed which greatly reduces the complexity of working with two state variables and is pedagogicallyuseful. Using this procedure, the price of any real estate contingent claim whose value is dependent on the one year spot rate and house price can be determined. Results are compared with those from a finite difference model.

A Housing Price Model with Endogenous Externality Location: A Study of Mobile Home Parks

This research explores the impact of mobile home parks on the value of single-family homes. This is the first study that empirically analyzes the effect of mobile home parks on property values. The empirical methodology used attempts to address the potential identification problem that exists within this study; it is possible that mobile home parks are located in areas of relatively lower land values or next to other land uses that impact property values. To address this identification problem, mobile home park locations are treated as endogenous within the model and the mobile home parks are identified as being located in residential or non-residential areas. The results suggest a negative effect on the selling price of single-family dwellings in close proximity to mobile home parks located in residential areas.

The Changing Asymmetric Information Component of REIT Spreads: A Study of Anticipated Announcements

This study examines the risk-compensating behavior of REIT market makers. The bid-ask spread is hypothesized to compensate market makers for three costs: asymmetric information, order processing, and inventory. As the market makers perceived likelihood of transacting with a better-informed individual increases (decreases), the percentage of the spread that is attributed to asymmetric information will increase (decrease). This study examines the asymmetric information component of the bid-ask spread immediately prior to and following REIT dividend announcements and REIT funds from operations announcements during 1995 and 1996. The asymmetric information component increases the day before and then declines subsequent to dividend announcements of small and equity REITs. Asymmetric information costs increase following funds from operations announcements.

Subprime Mortgage Default

This paper constructs a reduced-form credit risk model of mortgage default. The data used is of privately-securitized subprime ARMs (adjustable rate mortgages), originated between 1997 and 2008, and observed between 2000 and 2009. The period studied thus encompasses the beginning of the subprime crisis. Given the estimated model, contractual properties of the loans are then used to infer the market price of default risk for the various quarters of origination. It is empirically determined that a change in the inherent nature of borrowers led to a deterioration in their default performance, a change which can be first detected in late 2004. On the other hand, the evidence also indicates that the secondary mortgage market became aware of this change at about this same time. The large rise in defaults in 2007 cannot, therefore, be attributed to any surprise other than the unexpectedly large fall in housing prices.

Time-Varying Mortgage Prepayment Penalties

Recent empirical findings reveal that prepayment decisions of commercial property owners are slower than predicted by the pure options-pricing model (OPM). Borrower decisions appearing slow, however, may be quite rational when prepayment penalties of a time-varying nature are incorporated into the OPM. This article uses a competing risks OPM, adjusted for each of four different categories of prepayment penalties, to analyze borrower prepayment behavior. We find the value of delaying prepayment is often higher for mortgages with declining-rate penalties than for mortgages with static-rate penalties, frequently requiring a substantially higher interest rate spread to trigger a refinance. Multifamily loan prepayment records reveal the type of prepayment pattern that the adjusted OPM indicate should occur, reducing the gap between empirical findings and theoretical predictions. The results have implications for the specification of regressions fit to historical data, for the pricing of newly originated commercial mortgages, and for pricing in the single-family market where prepayment penalties are reemerging.

Frictions, Heterogeneity, and Optimality in Mortgage Modeling

The purpose of this article is to provide a unified framework for incorporating frictions into a theoretical options-pricing model (OPM) for mortgages. This article presents formulation for a frictions-adjustable mortgage model that integrates borrower heterogeneity while simultaneously preserving prepayment and default financial decisions. Our model demonstrates the flexibility of the OPM by simulating separate and concurrent effects of three categories of frictions on the mortgage and mortgage components. Researchers can use our example formulation to determine the effects of specific borrower characteristics on mortgage values without destroying the options theoretic framework.

Automated Valuation Models

Traditional fee appraisers have welcomed the computer technology of databases, spreadsheets, and word processing. Even further, they have welcomed appraisal software which has reduced the clerical element of writing appraisal reports. However, the basic methods they follow in estimating value have not changed much in some time. In contrast, over the same period, assessors have quietly yet radically changed their valuation technology through application of computer aided mass assessment (CAMA) techniques. These techniques have improved the accuracy of mass appraisals while reducing their cost. As the price of computer power and automated data collection spirals downwards, could the application of CAMA techniques supplant traditional appraisal in other settings?1

REIT excess dividend and information asymmetry: evidence with taxable income

Purpose – US real estate investment trusts (REITs) typically distribute more dividends than required by tax regulations. This paper aims to focus on discretionary dividends, and examines the impact of information asymmetry on this excess component of dividends.Design/methodology/approach – This paper considers a set of US REITs with reported taxable income figures over the 2000‐2007 period, and employs regression analysis to examine the influence of information asymmetry on the excess component of dividends. The explained variable is specified as excess dividends scaled by total assets. Excess dividends are dividends paid over the mandatory dividend payments calculated with taxable income, instead before‐tax net income. Following the REIT studies of Hardin and Hill and Han, this study employs Tobin Q as the proxy for asymmetric information.Findings – Contrary to Hardin and Hills conclusion, but consistent with dividend signaling theory as well as agency cost explanations, the results indicate that REITs ...

Are Appraisers Statisticians

Traditional hedonic pricing models, based upon an impressive corpus of statistical and economic theory, often exhibit prediction errors with a standard deviation in the range of 28–50%.1 In contrast, statistically challenged appraisers following ad hoc procedures often exhibit prediction errors with a standard deviation around 10%.2 The juxtaposition of these purported facts suggests the fruitfulness of examining elements of appraisal practice from a statistical perspective. In this vein Pace and Gilley (1998) showed the grid adjustment estimator employed by appraisers is a restricted version of the simultaneous autoregressive (SAR) estimator from spatial statistics. They suggest spatial statistics provides a unifying intellectual framework for reconciling appraisal practices with statistical theory.3