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Book
Analytically Tractable Stochastic Stock Price Models
Author:
ISBN: 3642433863 3642312136 9786613943408 3642312144 1283630958 Year: 2012 Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer,

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Abstract

Asymptotic analysis of stochastic stock price models is the central topic of the present volume. Special examples of such models are stochastic volatility models, that have been developed as an answer to certain imperfections in a celebrated Black-Scholes model of option pricing. In a stock price model with stochastic volatility, the random behavior of the volatility is described by a stochastic process. For instance, in the Hull-White model the volatility process is a geometric Brownian motion, the Stein-Stein model uses an Ornstein-Uhlenbeck process as the stochastic volatility, and in the Heston model a Cox-Ingersoll-Ross process governs the behavior of the volatility. One of the author's main goals is to provide sharp asymptotic formulas with error estimates for distribution densities of stock prices, option pricing functions, and implied volatilities in various stochastic volatility models. The author also establishes sharp asymptotic formulas for the implied volatility at extreme strikes in general stochastic stock price models. The present volume is addressed to researchers and graduate students working in the area of financial mathematics, analysis, or probability theory. The reader is expected to be familiar with elements of classical analysis, stochastic analysis and probability theory.

Keywords

Capital assets pricing model. --- Global analysis (Mathematics). --- Stocks -- Prices -- Mathematical models. --- Business & Economics --- Economic Theory --- Stock price forecasting --- Stock price indexes. --- Mathematical models. --- Averages, Stock --- Indexes, Stock --- Stock averages --- Stock indexes --- Mathematics. --- Mathematical analysis. --- Analysis (Mathematics). --- Approximation theory. --- Applied mathematics. --- Engineering mathematics. --- Economics, Mathematical. --- Probabilities. --- Quantitative Finance. --- Analysis. --- Probability Theory and Stochastic Processes. --- Approximations and Expansions. --- Applications of Mathematics. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Economics --- Mathematical economics --- Econometrics --- Engineering --- Engineering analysis --- Mathematical analysis --- Theory of approximation --- Functional analysis --- Functions --- Polynomials --- Chebyshev systems --- 517.1 Mathematical analysis --- Math --- Science --- Methodology --- Price indexes --- Finance. --- Distribution (Probability theory. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Analysis, Global (Mathematics) --- Differential topology --- Functions of complex variables --- Geometry, Algebraic --- Funding --- Funds --- Currency question --- Economics, Mathematical . --- Social sciences --- Mathematics in Business, Economics and Finance. --- Probability Theory.


Book
Large Deviations and Asymptotic Methods in Finance
Authors: --- --- --- ---
ISBN: 9783319116051 3319116045 9783319116044 3319116053 Year: 2015 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

Topics covered in this volume (large deviations, differential geometry, asymptotic expansions, central limit theorems) give a full picture of the current advances in the application of asymptotic methods in mathematical finance, and thereby provide rigorous solutions to important mathematical and financial issues, such as implied volatility asymptotics, local volatility extrapolation, systemic risk and volatility estimation. This volume gathers together ground-breaking results in this field by some of its leading experts. Over the past decade, asymptotic methods have played an increasingly important role in the study of the behaviour of (financial) models. These methods provide a useful alternative to numerical methods in settings where the latter may lose accuracy (in extremes such as small and large strikes, and small maturities), and lead to a clearer understanding of the behaviour of models, and of the influence of parameters on this behaviour. Graduate students, researchers and practitioners will find this book very useful, and the diversity of topics will appeal to people from mathematical finance, probability theory and differential geometry.

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