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.


An Analytic Valuation Method for Multivariate Contingent Claims with Regime-Switching Volatilities

An Analytic Valuation Method for Multivariate Contingent Claims with Regime-Switching Volatilities

Author: Bong-Gyu Jang

Publisher:

Published: 2011

Total Pages:

ISBN-13:

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In this paper, we provide an analytic valuation method for European-type contingent claims written on multiple assets in a stochastic market environment. We employ a two-state Markov regime-switching volatility in order to reflect the stochastically-changing market condition. The method is developed by exploiting the probability density of the occupation time for which the underlying asset processes are in a certain regime during a time period. In order to show its usefulness, we derive closed-form valuation formulas for quanto options and exchange options with two underlying assets, as examples. In addition, we develop an approximation formula for valuing a wide range of financial contingent claims written on more than two underlying assets.


American-Type Options

American-Type Options

Author: Dmitrii S. Silvestrov

Publisher: Walter de Gruyter

Published: 2013-11-27

Total Pages: 520

ISBN-13: 3110329824

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The book gives a systematical presentation of stochastic approximation methods for models of American-type options with general pay-off functions for discrete time Markov price processes. Advanced methods combining backward recurrence algorithms for computing of option rewards and general results on convergence of stochastic space skeleton and tree approximations for option rewards are applied to a variety of models of multivariate modulated Markov price processes. The principal novelty of presented results is based on consideration of multivariate modulated Markov price processes and general pay-off functions, which can depend not only on price but also an additional stochastic modulating index component, and use of minimal conditions of smoothness for transition probabilities and pay-off functions, compactness conditions for log-price processes and rate of growth conditions for pay-off functions. The book also contains an extended bibliography of works in the area. This book is the first volume of the comprehensive two volumes monograph. The second volume will present results on structural studies of optimal stopping domains, Monte Carlo based approximation reward algorithms, and convergence of American-type options for autoregressive and continuous time models, as well as results of the corresponding experimental studies.


Handbook of the Economics of Finance

Handbook of the Economics of Finance

Author: G. Constantinides

Publisher: Elsevier

Published: 2003-11-04

Total Pages: 698

ISBN-13: 0080495087

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Volume 1B covers the economics of financial markets: the saving and investment decisions; the valuation of equities, derivatives, and fixed income securities; and market microstructure.


Management Science

Management Science

Author:

Publisher:

Published: 2004

Total Pages: 656

ISBN-13:

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Issues for Feb. 1965-Aug. 1967 include Bulletin of the Institute of Management Sciences.


An Introduction to Applied Multivariate Analysis with R

An Introduction to Applied Multivariate Analysis with R

Author: Brian Everitt

Publisher: Springer Science & Business Media

Published: 2011-04-23

Total Pages: 284

ISBN-13: 1441996508

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The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.