A Lattice Approach to the Valuation of Multi-variate Contingent Claims with Regime Switching

A Lattice Approach to the Valuation of Multi-variate Contingent Claims with Regime Switching

Author: Mohamed Wahab Mohamed Ismail

Publisher:

Published: 2006

Total Pages: 238

ISBN-13: 9780494219584

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Various investment and operational practices, such as investing in flexible manufacturing systems and writing contracts to hedge the future risks, increasingly require tools for the valuation of contingent claims whose values depend on multiple underlying stochastic variables. These contingent claims incorporate advanced features, such as the early exercise of options, intermediate decisions, optimal policies, and possible causes of the dynamic behavior of the economic and operational environments. It would be impractical to utilize single-regime models, which specify a given mean and volatility to represent the evolution of an underlying variable, to describe the uncertainties from those economic and operational environments. Therefore, regime-switching models, which allow changes in the mean and volatility of the underlying stochastic variables over time, emerge as an alternative approach. Since the current literature on the regime-switching models mainly focuses on modeling and valuing an option on a single stochastic variable, the existing regime-switching models can not be applied to value options on several financial and non-financial regime-switching variables. Those options are complicated and require the development of a lattice approach, which is a discrete representation of a continuous process. Thus, one of the primary goals of this research is to develop a lattice approach that can be applied to value options on multiple underlying stochastic processes with multiple regimes. In this thesis, the existing lattice approach is extended in two major directions: lattice for a single stochastic process with multiple regimes, and lattice for multiple stochastic processes with multiple regimes. We then present three applications for the proposed lattices. The first application prices swing options under price uncertainty. The second application incorporates the product life cycle in valuing the flexibility of a manufacturing system that has three capacity options: expansion, contraction, and switching. The third application prices European and American rainbow options on correlated multiple regime-switching stochastic processes. We show that when compared with the Monte Carlo simulation, the proposed lattice for multiple stochastic processes with multiple regimes is computationally efficient and converged to the actual value of the options within a smaller number of steps.


A Note on the Pricing of Multivariate Contingent Claims Under a Transformed-Gamma Distribution

A Note on the Pricing of Multivariate Contingent Claims Under a Transformed-Gamma Distribution

Author: Luiz Vitiello

Publisher:

Published: 2014

Total Pages: 18

ISBN-13:

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We develop a framework for pricing multivariate European-style contingent claims in a discrete-time economy based on a multivariate transformed-gamma distribution. In our model, each transformed-gamma distributed underlying asset depends on two terms: a idiosyncratic term and a systematic term, where the latter is the same for all underlying assets and has a direct impact on their correlation structure. Given our distributional assumptions and the existence of a representative agent with a standard utility function, we apply equilibrium arguments and provide sufficient conditions for obtaining preference-free contingent claim pricing equations. We illustrate the applicability of our framework by providing examples of preference-free contingent claim pricing models. Multivariate pricing models are of particular interest when payoffs depend on two or more underlying assets, such as crack and crush spread options, options to exchange one asset for another, and options with a stochastic strike price in general.


Semiparametric Pricing of Multivariate Contingent Claims

Semiparametric Pricing of Multivariate Contingent Claims

Author: Joshua V. Rosenberg

Publisher:

Published: 2009

Total Pages: 27

ISBN-13:

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This paper develops and implements a methodology for pricing multivariate contingent claims (MVCC s) based on semiparametric estimation of the multivariate risk-neutral density function.This methodology generates MVCC prices which are consistent with current market prices of univariate contingent claims.This method allows for completely general marginal risk-neutral densities and is compatible with all univariate risk-neutral density estimation techniques. The univariate risk-neutral densities are related by their risk-neutral correlation, which is estimated using time-series data on asset returns and an empirical pricing kernel (Rosenberg and Engle, 1999). This permits the multivariate risk-neutral density to be identified without requiring observation of multivariate contingent claims prices. The semiparametric MVCC pricing technique is used for valuation of one-month options on the better of two equity index returns. Option contracts with payoffs dependent on are four equity indexpairs are considered: Samp;P500 - CAC40, Samp;P500 - NK225, Samp;P500 - FTSE100, and Samp;P500 - DAX30. Five marginal risk-neutral densities (Samp;P500, CAC40, NK225, FTSE100, and DAX30) are estimated semiparametrically using a cross-section of contemporaneously measured equity index option prices in each market. A bivariate risk-neutral Plackett (1965) density is constructed using the given marginals and risk-neutral correlation derived using an empirical pricing kernel and the historical joint density of the index returns. Price differences from a lognormal pricing formulausing historical and risk-neutral return moments are found to be significant.


Pricing Multivariate Contingent Claims Using Estimated Risk-Neutral Density Functions

Pricing Multivariate Contingent Claims Using Estimated Risk-Neutral Density Functions

Author:

Publisher:

Published: 2008

Total Pages: 24

ISBN-13:

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Many asset price series exhibit time-varying volatility, jumps, and other features inconsistent with assumptions about the underlying price process made by standard multivariate contingent claims (MVCC) pricing models. This paper develops an interpolative technique for pricing MVCCs flexible NLS pricing that involves the estimation of a flexible multivariate risk-neutral density function implied by existing asset prices. As an application, the flexible NLS pricing technique is used to value several bivariate contingent claims dependent on foreign exchange rates in 1993 and 1994. The bivariate flexible risk-neutral density function more accurately prices existing options than the bivariate lognormal density implied by a multivariate geometric Brownian motion. In addition, the bivariate contingent claims analyzed have substantially different prices using the two density functions suggesting flexible NLS pricing may improve accuracy over standard methods.