Radu Tunaru

Property Derivatives for Managing European Real-Estate Risk

Although property markets represent a large proportion of total wealth in developed countries, the real-estate derivatives markets are still lagging behind in volume of trading and liquidity. Over the last few years there has been increased activity in developing derivative instruments that can be utilised by asset managers. In this paper, we discuss the problems encountered when using property derivatives for managing European real-estate risk. We also consider a special class of structured interest rate swaps that have embedded real-estate risk and propose a more efficient way to tailor these swaps.

Hedging Real Estate Risk

A number of real estate derivatives are available worldwide. The authors discuss the issues related to the pricing of these instruments and to the managing of hedging instruments over time. The property derivatives are classified by the type of real estate risk they hedge: 1) housing price risk, 2) commercial property price risk, and 3) mortgage loan portfolio amortizing risk. Given the special characteristics of the real estate asset class—an incomplete market, difficult to hedge, and reversion to a long-term trend—the authors emphasize the main points that should be taken into account when pricing property derivatives.

A Pricing Framework for Real Estate Derivatives

New methods are developed here for pricing the main real estate derivatives — futures and forward contracts, total return swaps, and options. Accounting for the incompleteness of this market, a suitable modelling framework is outlined that can produce exact formulae, assuming that the market price of risk is known. This framework can accommodate econometric properties of real estate indices such as predictability due to autocorrelations. The term structure of the market price of risk is calibrated from futures market prices on the Investment Property Databank index. The evolution of the market price of risk associated with all five futures curves during 2009 is discussed.

Estimating risk-neutral density with parametric models in interest rate markets

The departure in modelling terms from the log-normal distribution for option pricing has been largely driven by empirical observations on skewness. In recent years, the Weibull and generalized beta distributions have been used to fit the risk-neutral density from option prices. In this article, we also propose the use of the generalized gamma distribution for recovering the risk-neutral density. In terms of complexity, this distribution, having three parameters, falls between the Weibull and generalized beta distributions. New option pricing formulas for European call and put options are derived under the generalized gamma distribution. The empirical evidence based on a set of interest rate derivatives data indicates that this distribution is capable of producing the same type of performance as the Weibull, generalized beta, and Burr3 distributions. In addition, we analyze the effect of July 2005 bombings in London on interest rate markets under the best fitting distribution. Our results indicate that there was very little impact on the volatility of these markets.

Quantification of political risk with multiple dependent sources

In this paper, we develop a model using a conditional Poisson process for measuring the effect of a countable number of mutually dependant political risks on the outcome of foreign direct investment. We also apply a Bayesian updating process that makes it possible to re-estimate the models parameters as new information becomes available. We then show how the model can be operationalized and provide a comparative example related to foreign direct investment. (JEL G31, D81, F21).

On risk management problems related to a coherence property

Value at Risk has lost the battle against Expected Shortfall on theoretical grounds, the latter satisfying all coherence properties while the former may, on carefully constructed cases, lack the sub-additivity property that is in a sense, the most important property a risk measure ought to satisfy. While the superiority of Expected Shortfall is evident as a theoretical tool, little has been researched on the properties of estimators proposed in the literature. Since those estimators are the real tools for calculating bank capital reserves in practice, the natural question that one may ask is whether a given estimator of Expected Shortfall also satisfies the coherence properties. In this paper, we show that it is possible to have estimators of Expected Shortfall that do not satisfy the sub-additivity condition. This finding should motivate risk managers and quantitative asset managers to investigate further the properties of the estimators of the risk measures they are currently utilizing.

Commercial Real Estate Risk Management with Derivatives

Helping managers to gauge the interaction between commercial property prices and interest rates for commercial property and CMBS portfolios.

Portfolio selection under VaR constraints.

Abstract.In this paper we show that by assuming a constant variance/covariance matrix over the holding period, the VaR limits can often be exceeded within the relevant horizon period. To minimize this risk, we formulate the problem in terms of portfolio selection and propose an innovative methodology using conditional VaR that minimizes the VaR at each point of the holding period. We rewrite the optimisation problem by taking into consideration the variability of risk on all assets eligible to be included in the portfolio.

HERMITE BINOMIAL TREES: A NOVEL TECHNIQUE FOR DERIVATIVES PRICING

Edgeworth binomial trees were applied to price contingent claims when the underlying return distribution is skewed and leptokurtic, but with the limitation of working only for a limited set of skewness and kurtosis values. Recently, Johnson binomial trees were introduced to accommodate any skewness-kurtosis pair, but with the drawback of numerical convergence issues in some cases. Both techniques may suffer from non-exact matching of the moments of distribution of returns. A solution to this limitation is proposed here based on a new technique employing Hermite polynomials to match exactly the required moments. Several numerical examples illustrate the superior performance of the Hermite polynomials technique to price European and American options in the context of jump-diffusion and stochastic volatility frameworks and options with underlying asset given by the sum of two lognormally distributed random variables.

An improved method for pricing and hedging long dated American options

The majority of quasi-analytic pricing methods for American options are efficient near maturity but are prone to larger errors when time-to-maturity increases. We introduce a new methodology to increase the accuracy of almost any existing quasi-analytic approach in pricing long-maturity American options. The new methodology, called the “extension-method”, relies on an approximation of the optimal exercise price near the beginning of the contract combined with existing pricing approaches so that the maturity range for which small errors are attainable is extended. Our method retains the quasi-analytic nature of the methods it improves. Generic quasi-analytic formulae for the price of an American put as well as for its hedging parameter are derived. Our scenarios-based numerical study indicates that our method considerably improves both the pricing and the hedging performance of a number of established approaches for a wide range of maturities. The superiority of this approach is illustrated with real financial data by considering S&P 100TM LEAPS® options traded from January 2008 to May 2015.