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Control theory --- Jump processes --- Linear systems --- Control theory --- Jump processes
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The text is concerned with a class of two-sided stochastic processes of the form X=W+A. Here W is a two-sided Brownian motion with random initial data at time zero and Aequiv A(W) is a function of W. Elements of the related stochastic calculus are introduced. In particular, the calculus is adjusted to the case when A is a jump process. Absolute continuity of (X,P) under time shift of trajectories is investigated. For example under various conditions on the initial density with respect to the Lebesgue measure, m, and on A with A_0=0 we verify frac{P(dX_{cdot -t})}{P(dX_cdot)}=frac{m(X_{-t})}{m(X_0)}cdot prod_ileft|abla_{d,W_0}X_{-t}ight|_i i.e. where the product is taken over all coordinates. Here sum_i left(abla_{d,W_0}X_{-t}ight)_i is the divergence of X_{-t} with respect to the initial position. Crucial for this is the temporal homogeneity of X in the sense that Xleft(W_{cdot +v}+A_v mathbf{1}ight)=X_{cdot+v}(W), vin {mathbb R}, where A_v mathbf{1} is the trajectory taking the constant value A_v(W). By means of such a density, partial integration relative to a generator type operator of the process X is established. Relative compactness of sequences of such processes is established.
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Stochastic processes with jumps and random measures are importance as drivers in applications like financial mathematics and signal processing. This 2002 text develops stochastic integration theory for both integrators (semimartingales) and random measures from a common point of view. Using some novel predictable controlling devices, the author furnishes the theory of stochastic differential equations driven by them, as well as their stability and numerical approximation theories. Highlights feature DCT and Egoroff's Theorem, as well as comprehensive analogs results from ordinary integration theory, for instance previsible envelopes and an algorithm computing stochastic integrals of càglàd integrands pathwise. Full proofs are given for all results, and motivation is stressed throughout. A large appendix contains most of the analysis that readers will need as a prerequisite. This will be an invaluable reference for graduate students and researchers in mathematics, physics, electrical engineering and finance who need to use stochastic differential equations.
Stochastic integrals. --- Jump processes. --- Integrals, Stochastic --- Stochastic analysis --- Processes, Jump --- Markov processes --- Jump processes
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Jump processes. --- Stochastic control theory. --- Control theory --- Stochastic processes --- Processes, Jump --- Markov processes
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During the last decade, financial models based on jump processes have acquired increasing popularity in risk management and option pricing. Much has been published on the subject, but the technical nature of most papers makes them difficult for nonspecialists to understand, and the mathematical tools required for applications can be intimidating. Potential users often get the impression that jump and Levy processes are beyond their reach. Financial Modelling with Jump Processes shows that this is not so. It provides a self-contained overview of the theoretical, numerical, and empirical aspects involved in using jump processes in financial modelling, and it does so in terms within the grasp of nonspecialists. The introduction of new mathematical tools is motivated by their use in the modelling process, and precise mathematical statements of results are accompanied by intuitive explanations.Topics covered in this book include: jump-diffusion models, Levy processes, stochastic calculus for jump processes, pricing and hedging in incomplete markets, implied volatility smiles, time-inhomogeneous jump processes and stochastic volatility models with jumps. The authors illustrate the mathematical concepts with many numerical and empirical examples and provide the details of numerical implementation of pricing and calibration algorithms. This book demonstrates that the concepts and tools necessary for understanding and implementing models with jumps can be more intuitive that those involved in the Black Scholes and diffusion models. If you have even a basic familiarity with quantitative methods in finance, Financial Modelling with Jump Processes will give you a valuable new set of tools for modelling market fluctuations.
Stochastic processes --- Finance --- Jump processes. --- Finances --- Processus de sauts --- Mathematical models. --- Modèles mathématiques --- Jump processes --- Mathematical models --- mathematische modellen, toegepast op economie --- stochastische modellen --- opties --- risk management --- -Jump processes --- 332.01519233 --- Processes, Jump --- Markov processes --- Funding --- Funds --- Economics --- Currency question --- Modèles mathématiques --- Finance - Mathematical models
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Approximation of Large-Scale Dynamical Systems
Probabilities. --- 519.21 --- #WWIS:STAT --- 519.21 Probability theory. Stochastic processes --- Probability theory. Stochastic processes --- Probability theory --- Probabilities --- Jump processes --- Markov processes --- Ergodic theory
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This monograph is a concise introduction to the stochastic calculus of variations (also known as Malliavin calculus) for processes with jumps. It is written for researchers and graduate students who are interested in Malliavin calculus for jump processes. In this book "processes with jumps" includes both pure jump processes and jump-diffusions. The author provides many results on this topic in a self-contained way; this also applies to stochastic differential equations (SDEs) "with jumps". The book also contains some applications of the stochastic calculus for processes with jumps to the control theory and mathematical finance. Namely, asymptotic expansions functionals related with financial assets of jump-diffusion are provided based on the theory of asymptotic expansion on the Wiener-Poisson space. Solving the Hamilton-Jacobi-Bellman (HJB) equation of integro-differential type is related with solving the classical Merton problem and the Ramsey theory. The field of jump processes is nowadays quite wide-ranging, from the Lévy processes to SDEs with jumps. Recent developments in stochastic analysis have enabled us to express various results in a compact form. Up to now, these topics were rarely discussed in a monograph. Contents: Preface Preface to the second edition Introduction Lévy processes and Itô calculus Perturbations and properties of the probability law Analysis of Wiener-Poisson functionals Applications Appendix Bibliography List of symbols Index
Malliavin calculus. --- Calculus of variations. --- Jump processes. --- Stochastic processes. --- Random processes --- Probabilities --- Processes, Jump --- Markov processes --- Isoperimetrical problems --- Variations, Calculus of --- Maxima and minima --- Calculus, Malliavin --- Stochastic analysis
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There is strong evidence that interest rates and bond yield movements exhibit both stochastic volatility and unanticipated jumps. The presence of frequent jumps makes it natural to ask whether there is a premium for jump risk embedded in observed bond yields. This paper identifies a class of jump-diffusion models that are successful in approximating the term structure of interest rates of emerging markets. The parameters of the term structure of interest rates are reconciled with the associated bond yields by estimating the volatility and jump risk premia in highly volatile markets. Using the simulated method of moments (SMM), results suggest that all variants of models which do not take into account stochastic volatility and unanticipated jumps cannot generate the non-normalities consistent with the observed interest rates. Jumps occur (8,10) times a year in Argentina and Brazil, respectively. The size and variance of these jumps is also of statistical significance.
Banks and Banking --- Macroeconomics --- Interest Rates: Determination, Term Structure, and Effects --- Price Level --- Inflation --- Deflation --- Finance --- Yield curve --- Short term interest rates --- Interest rate modelling --- Asset prices --- Market interest rates --- Interest rates --- Prices --- Argentina --- Risk --- Jump processes --- Bonds --- Econometric models.
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