A model for pricing real estate derivatives with stochastic interest rates

The real estate derivatives market allows participants to manage risk and return from exposure to property, without buying or selling directly the underlying asset. Such market is growing very fast hence the need to rely on simple yet effective pricing models is very great. In order to take into account the real estate market sensitivity to the interest rate term structure in this paper is presented a two-factor model where the real estate asset value and the spot rate dynamics are jointly modeled. The pricing problem for both European and American options is then analyzed and since no closed-form solution can be found a bidimensional binomial lattice framework is adopted. The model proposed allows calibration to the interest rate and volatility term structures.

A model for pricing real estate derivatives with stochastic interest rates

The real estate derivatives market allows participants to manage risk and return from exposure to property, without buying or selling directly the underlying asset. Such market is growing very fast hence the need to rely on simple yet effective pricing models is very great. In order to take into account the real estate market sensitivity to the interest rate term structure in this paper is presented a two-factor model where the real estate asset value and the spot rate dynamics are jointly modeled. The pricing problem for both European and American options is then analyzed and since no closed-form solution can be found a bidimensional binomial lattice framework is adopted. The model proposed allows calibration to the interest rate and volatility term structures

An empirical comparison of convertible bond valuation models

This paper empirically compares three convertible bond valuation models. We use an innovative approach where all model parameters are estimated by the Marquardt algorithm using a subsample of convertible bond prices. The model parameters are then used for out-of-sample forecasts of convertible bond prices. The mean absolute deviation is 1.86% for the Ayache-Forsyth-Vetzal model, 1.94% for the Tsiveriotis-Fernandes model, and 3.73% for the Brennan-Schwartz model. For this and other measures of fit, the Ayache-Forsyth-Vetzal and Tsiveriotis-Fernandes models outperform the Brennan-Schwartz model

Real Option Pricing in Mixed-use Development Projects

The application of real options theory to commercial real estate has developed rapidly during the last 15 Years. In particular, several pricing models have been applied to value real options embedded in development projects. In this study we use a case study of a mixed use development scheme and identify the major implied and explicit real options available to the developer. We offer the perspective of a real market application by exploring different binomial models and the associated methods of estimating the crucial parameter of volatility. We include simple binomial lattices, quadranomial lattices and demonstrate the sensitivity of the results to the choice of inputs and method.

A Note on Embedded Lease Options

Buetow and Albert (1998) discuss options embedded in lease contracts. They present a pricing framework, calibrate it using data from the National Real Estate Index and apply it using a numerical method known as the finite difference method with absorbing boundaries. In this note the analysis is extended. Firstly, analytic solutions are presented. Secondly, some of the findings are discussed. Finally, the framework developed by Grenadier is used to compare indexed renewal options for different lease lengths.

The Pricing of Embedded Options in Real Estate Lease Contracts

Leases and rental agreements often have options attached or embedded in them. These options sometimes depend on a number of economic variables such as the consumer price index (CPI), a real estate index and/or the value of real estate underlying the agreement. The evaluation of these options often involves the solution or approximation to a partial differential equation (PDE). This study analyzes the appropriate PDEs which model the situation where the lessee is granted an option to either purchase the property or to renew the lease at a price (rent) indexed to the CPI or some other readily measured economic variable. The PDEs that result from the usual contingent claim asset-pricing framework are derived and numerically solved using the finite difference method with absorbing boundaries. The value of an embedded option to renew a five year lease on class A office space in each of the ternty-five markets for which the National Real Estate Index reports quarterly rental data is estimated. An evaluation of the model’s "Greeks" confirm that the model conforms to financial intuition which provides support for the accuracy of the estimates.

The History of the Quantitative Methods in Finance Conference Series. 1992-2007

This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.

Capturing UK Real Estate Volitility

Volatility, or the variability of the underlying asset, is one of the key fundamental components of property derivative pricing and in the application of real option models in development analysis. There has been relatively little work on volatility in real terms of its application to property derivatives and the real options analysis. Most research on volatility stems from investment performance (Nathakumaran & Newell (1995), Brown & Matysiak 2000, Booth & Matysiak 2001). Historic standard deviation is often used as a proxy for volatility and there has been a reliance on indices, which are subject to valuation smoothing effects. Transaction prices are considered to be more volatile than the traditional standard deviations of appraisal based indices. This could lead, arguably, to inefficiencies and mis-pricing, particularly if it is also accepted that changes evolve randomly over time and where future volatility and not an ex-post measure is the key (Sing 1998). If history does not repeat, or provides an unreliable measure, then estimating model based (implied) volatility is an alternative approach (Patel & Sing 2000). This paper is the first of two that employ alternative approaches to calculating and capturing volatility in UK real estate for the purposes of applying the measure to derivative pricing and real option models. It draws on a uniquely constructed IPD/Gerald Eve transactions database, containing over 21,000 properties over the period 1983-2005. In this first paper the magnitude of historic amplification associated with asset returns by sector and geographic spread is looked at. In the subsequent paper the focus will be upon model based (implied) volatility.Real Estate, Volatility

Systemic Risk and the Refinancing Ratchet Effect

The confluence of three trends in the U.S. residential housing market-rising home prices, declining interest rates, and near-frictionless refinancing opportunities-led to vastly increased systemic risk in the financial system. Individually, each of these trends is benign, but when they occur simultaneously, as they did over the past decade, they impose an unintentional synchronization of homeowner leverage. This synchronization, coupled with the indivisibility of residential real estate that prevents homeowners from deleveraging when property values decline and homeowner equity deteriorates, conspire to create a "ratchet" effect in which homeowner leverage is maintained during good times without the ability to decrease leverage during bad times. If refinancing-facilitated homeowner-equity extraction is sufficiently widespread-as it was during the years leading up to the peak of the U.S. residential real-estate market-the inadvertent coordination of leverage during a market rise implies higher correlation of defaults during a market drop. To measure the systemic impact of this ratchet effect, we simulate the U.S. housing market with and without equity extractions, and estimate the losses absorbed by mortgage lenders by valuing the embedded put-option in non-recourse mortgages. Our simulations generate loss estimates of $1.5 trillion from June 2006 to December 2008 under historical market conditions, compared to simulated losses of$280 billion in the absence of equity extractions.Risk; Financial Crisis; Household Finance; Real Estate; Subprime