Stochastic Volatility And Jumps Driven By Continous Time Markov Chains PDF Download
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| Author | : Kyriakos Chourdakis |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 2003 |
| Genre | : |
| ISBN | : |
Download Stochastic Volatility and Jumps Driven by Continuous Time Markov Chains Book in PDF, ePub and Kindle
This paper considers a model where there is a single state variable that drives the state of the world and therefore the asset price behavior. This variable evolves according to a multi-state continuous time Markov chain, as the continuous time counterpart of (Hamilton 1989) model. It derives the moment generating function of the asset log-price difference under very general assumptions about its stochastic process, incorporating volatility and jumps that can follow virtually any distribution, both of them being driven by the same state variable. For an illustration, the extreme value distribution is used as the jump distribution. The paper shows how GMM and conditional ML estimators can be constructed, generalizing Hamilton's filter for the continuous time case. The risk neutral process is constructed and contingent claim prices under this specification are derived, in the lines of (Bakshi and Madan 2000). Finally, an empirical example is set up, to illustrate the potential benefits of the model.
| Author | : Kyriakos M. Chourdakis |
| Publisher | : |
| Total Pages | : 45 |
| Release | : 2000 |
| Genre | : Economics |
| ISBN | : |
Download Stochastic Volatility and Jumps Driven by Continuous Time Markov Chains Book in PDF, ePub and Kindle
| Author | : William J. Anderson |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 367 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461230381 |
Download Continuous-Time Markov Chains Book in PDF, ePub and Kindle
Continuous time parameter Markov chains have been useful for modeling various random phenomena occurring in queueing theory, genetics, demography, epidemiology, and competing populations. This is the first book about those aspects of the theory of continuous time Markov chains which are useful in applications to such areas. It studies continuous time Markov chains through the transition function and corresponding q-matrix, rather than sample paths. An extensive discussion of birth and death processes, including the Stieltjes moment problem, and the Karlin-McGregor method of solution of the birth and death processes and multidimensional population processes is included, and there is an extensive bibliography. Virtually all of this material is appearing in book form for the first time.
| Author | : Pierre Bremaud |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 456 |
| Release | : 2013-03-09 |
| Genre | : Mathematics |
| ISBN | : 1475731248 |
Download Markov Chains Book in PDF, ePub and Kindle
Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.
| Author | : Kyriakos M. Chourdakis |
| Publisher | : |
| Total Pages | : 45 |
| Release | : 2000 |
| Genre | : |
| ISBN | : |
Download Stochastic Volatility and Jumps Driven by Continous Time Markov Chains Book in PDF, ePub and Kindle
| Author | : Sean P. Meyn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 559 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 144713267X |
Download Markov Chains and Stochastic Stability Book in PDF, ePub and Kindle
Markov Chains and Stochastic Stability is part of the Communications and Control Engineering Series (CCES) edited by Professors B.W. Dickinson, E.D. Sontag, M. Thoma, A. Fettweis, J.L. Massey and J.W. Modestino. The area of Markov chain theory and application has matured over the past 20 years into something more accessible and complete. It is of increasing interest and importance. This publication deals with the action of Markov chains on general state spaces. It discusses the theories and the use to be gained, concentrating on the areas of engineering, operations research and control theory. Throughout, the theme of stochastic stability and the search for practical methods of verifying such stability, provide a new and powerful technique. This does not only affect applications but also the development of the theory itself. The impact of the theory on specific models is discussed in detail, in order to provide examples as well as to demonstrate the importance of these models. Markov Chains and Stochastic Stability can be used as a textbook on applied Markov chain theory, provided that one concentrates on the main aspects only. It is also of benefit to graduate students with a standard background in countable space stochastic models. Finally, the book can serve as a research resource and active tool for practitioners.
| Author | : David Freedman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 395 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461255007 |
Download Markov Chains Book in PDF, ePub and Kindle
A long time ago I started writing a book about Markov chains, Brownian motion, and diffusion. I soon had two hundred pages of manuscript and my publisher was enthusiastic. Some years and several drafts later, I had a thousand pages of manuscript, and my publisher was less enthusiastic. So we made it a trilogy: Markov Chains Brownian Motion and Diffusion Approximating Countable Markov Chains familiarly - MC, B & D, and ACM. I wrote the first two books for beginning graduate students with some knowledge of probability; if you can follow Sections 10.4 to 10.9 of Markov Chains you're in. The first two books are quite independent of one another, and completely independent of the third. This last book is a monograph which explains one way to think about chains with instantaneous states. The results in it are supposed to be new, except where there are specific disclaim ers; it's written in the framework of Markov Chains. Most of the proofs in the trilogy are new, and I tried hard to make them explicit. The old ones were often elegant, but I seldom saw what made them go. With my own, I can sometimes show you why things work. And, as I will VB1 PREFACE argue in a minute, my demonstrations are easier technically. If I wrote them down well enough, you may come to agree.
| Author | : Sean Meyn |
| Publisher | : Cambridge University Press |
| Total Pages | : 595 |
| Release | : 2009-04-02 |
| Genre | : Mathematics |
| ISBN | : 1139477978 |
Download Markov Chains and Stochastic Stability Book in PDF, ePub and Kindle
Meyn and Tweedie is back! The bible on Markov chains in general state spaces has been brought up to date to reflect developments in the field since 1996 - many of them sparked by publication of the first edition. The pursuit of more efficient simulation algorithms for complex Markovian models, or algorithms for computation of optimal policies for controlled Markov models, has opened new directions for research on Markov chains. As a result, new applications have emerged across a wide range of topics including optimisation, statistics, and economics. New commentary and an epilogue by Sean Meyn summarise recent developments and references have been fully updated. This second edition reflects the same discipline and style that marked out the original and helped it to become a classic: proofs are rigorous and concise, the range of applications is broad and knowledgeable, and key ideas are accessible to practitioners with limited mathematical background.
| Author | : Masaaki Kijima |
| Publisher | : Springer |
| Total Pages | : 345 |
| Release | : 2013-12-19 |
| Genre | : Mathematics |
| ISBN | : 1489931325 |
Download Markov Processes for Stochastic Modeling Book in PDF, ePub and Kindle
This book presents an algebraic development of the theory of countable state space Markov chains with discrete- and continuous-time parameters. A Markov chain is a stochastic process characterized by the Markov prop erty that the distribution of future depends only on the current state, not on the whole history. Despite its simple form of dependency, the Markov property has enabled us to develop a rich system of concepts and theorems and to derive many results that are useful in applications. In fact, the areas that can be modeled, with varying degrees of success, by Markov chains are vast and are still expanding. The aim of this book is a discussion of the time-dependent behavior, called the transient behavior, of Markov chains. From the practical point of view, when modeling a stochastic system by a Markov chain, there are many instances in which time-limiting results such as stationary distributions have no meaning. Or, even when the stationary distribution is of some importance, it is often dangerous to use the stationary result alone without knowing the transient behavior of the Markov chain. Not many books have paid much attention to this topic, despite its obvious importance.
| Author | : R. Syski |
| Publisher | : IOS Press |
| Total Pages | : 564 |
| Release | : 1992 |
| Genre | : Computers |
| ISBN | : 9789051990607 |
Download Passage Times for Markov Chains Book in PDF, ePub and Kindle
This book is a survey of work on passage times in stable Markov chains with a discrete state space and a continuous time. Passage times have been investigated since early days of probability theory and its applications. The best known example is the first entrance time to a set, which embraces waiting times, busy periods, absorption problems, extinction phenomena, etc. Another example of great interest is the last exit time from a set. The book presents a unifying treatment of passage times, written in a systematic manner and based on modern developments. The appropriate unifying framework is provided by probabilistic potential theory, and the results presented in the text are interpreted from this point of view. In particular, the crucial role of the Dirichlet problem and the Poisson equation is stressed. The work is addressed to applied probalilists, and to those who are interested in applications of probabilistic methods in their own areas of interest. The level of presentation is that of a graduate text in applied stochastic processes. Hence, clarity of presentation takes precedence over secondary mathematical details whenever no serious harm may be expected. Advanced concepts described in the text gain nowadays growing acceptance in applied fields, and it is hoped that this work will serve as an useful introduction. Abstracted by Mathematical Reviews, issue 94c
