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Book Nonlinear Drift and Stochastic Volatility

Download or read book Nonlinear Drift and Stochastic Volatility written by Licheng Sun and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this article I provide new evidence on the role of nonlinear drift and stochastic volatility in interest rate modeling. I compare various model specifications for the short-term interest rate using the data from five countries. I find that modeling the stochastic volatility in the short rate is far more important than specifying the shape of the drift function. The empirical support for nonlinear drift is weak with or without the stochastic volatility factor. Although a linear drift stochastic volatility model fits the international data well, I find that the level effect differs across countries.

Book Modelling and Simulation of Stochastic Volatility in Finance

Download or read book Modelling and Simulation of Stochastic Volatility in Finance written by Christian Kahl and published by Universal-Publishers. This book was released on 2008 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: The famous Black-Scholes model was the starting point of a new financial industry and has been a very important pillar of all options trading since. One of its core assumptions is that the volatility of the underlying asset is constant. It was realised early that one has to specify a dynamic on the volatility itself to get closer to market behaviour. There are mainly two aspects making this fact apparent. Considering historical evolution of volatility by analysing time series data one observes erratic behaviour over time. Secondly, backing out implied volatility from daily traded plain vanilla options, the volatility changes with strike. The most common realisations of this phenomenon are the implied volatility smile or skew. The natural question arises how to extend the Black-Scholes model appropriately. Within this book the concept of stochastic volatility is analysed and discussed with special regard to the numerical problems occurring either in calibrating the model to the market implied volatility surface or in the numerical simulation of the two-dimensional system of stochastic differential equations required to price non-vanilla financial derivatives. We introduce a new stochastic volatility model, the so-called Hyp-Hyp model, and use Watanabe's calculus to find an analytical approximation to the model implied volatility. Further, the class of affine diffusion models, such as Heston, is analysed in view of using the characteristic function and Fourier inversion techniques to value European derivatives.

Book Nonparametric Stochastic Volatility

Download or read book Nonparametric Stochastic Volatility written by Federico M. Bandi and published by . This book was released on 2018 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: We provide nonparametric methods for stochastic volatility modeling. Our methods allow for the joint evaluation of return and volatility dynamics with nonlinear drift and diffusion functions, nonlinear leverage effects, and jumps in returns and volatility with possibly state-dependent jump intensities, among other features. In the first stage, we identify spot volatility by virtue of jump- robust nonparametric estimates. Using observed prices and estimated spot volatilities, the second stage extracts the functions and parameters driving price and volatility dynamics from nonparametric estimates of the bivariate process' infinitesimal moments. For these infinitesimal moment estimates, we report an asymptotic theory relying on joint in-fill and long-span arguments which yields consistency and weak convergence under mild assumptions.

Book Drift and Volatility Estimation for Stochastic Differential Equations

Download or read book Drift and Volatility Estimation for Stochastic Differential Equations written by Shannon Marie Kelly and published by . This book was released on 1998 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Stochastic Volatility in Financial Markets

Download or read book Stochastic Volatility in Financial Markets written by Antonio Mele and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed `stochastic volatility', or `conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part goes beyond the statistical aspects of stochastic volatility models: it constructs and uses new fully articulated, theoretically-sounded financial asset pricing models that allow for the presence of conditional heteroskedasticity. The third part shows how the inclusion of the statistical aspects of stochastic volatility in a rigorous economic scheme can be faced from an empirical standpoint.

Book A Class of Nonlinear Stochastic Volatility Models

Download or read book A Class of Nonlinear Stochastic Volatility Models written by Jun Yu and published by . This book was released on 2013 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a class of nonlinear stochastic volatility models based on the Box-Cox transformation which offers an alternative to the one introduced in Andersen (1994). The proposed class encompasses many parametric stochastic volatility models that have appeared in the literature, including the well known lognormal stochastic volatility model, and has an advantage in the ease with which different specifications on stochastic volatility can be tested. In addition, the functional form of transformation which induces marginal normality of volatility is obtained as a byproduct of this general way of modeling stochastic volatility. The efficient method of moments approach is used to estimate model parameters. Empirical results reveal that the lognormal stochastic volatility model is rejected for daily index return data but not for daily individual stock return data. As a consequence, the stock volatility can be well described by the lognormal distribution as its marginal distribution, consistent with the result found in a recent literature (cf Andersen et al (2001a)). However, the index volatility does not follow the lognormal distribution as its marginal distribution.

Book Parameter Estimation in Stochastic Volatility Models

Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.

Book Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate

Download or read book Testing the Empirical Performance of Stochastic Volatility Models of the Short Term Interest Rate written by Turan G. Bali and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: I introduce two-factor discrete time stochastic volatility models of the short-term interest rate to compare the relative performance of existing and alternative empirical specifications. I develop a nonlinear asymmetric framework that allows for comparisons of non-nested models featuring conditional heteroskedasticity and sensitivity of the volatility process to interest rate levels. A new class of stochastic volatility models with asymmetric drift and nonlinear asymmetric diffusion process is introduced in discrete time and tested against the popular continuous time and symmetric and asymmetric GARCH models. The existing models are rejected in favor of the newly proposed models because of the asymmetric drift of the short rate, and the presence of nonlinearity, asymmetry, GARCH, and level effects in its volatility. I test the predictive power of nested and non-nested models in capturing the stochastic behavior of the risk-free rate. Empirical evidence on three-, six-, and 12-month U.S. Treasury bills indicates that two-factor stochastic volatility models are better than diffusion and GARCH models in forecasting the future level and volatility of interest rate changes.

Book Hidden Markov Models in Finance

Download or read book Hidden Markov Models in Finance written by Rogemar S. Mamon and published by Springer. This book was released on 2014-05-14 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors’ Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance and showcases the formulation of emerging potential applications of new research over the book’s 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market.

Book Nonlinear filtering in stochastic volatility models

Download or read book Nonlinear filtering in stochastic volatility models written by and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Uncertain Volatility Models

Download or read book Uncertain Volatility Models written by Robert Buff and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the only books to describe uncertain volatility models in mathematical finance and their computer implementation for portfolios of vanilla, barrier and American options in equity and FX markets. Uncertain volatility models place subjective constraints on the volatility of the stochastic process of the underlying asset and evaluate option portfolios under worst- and best-case scenarios. This book, which is bundled with software, is aimed at graduate students, researchers and practitioners who wish to study advanced aspects of volatility risk in portfolios of vanilla and exotic options. The reader is assumed to be familiar with arbitrage pricing theory.

Book On Estimation of the Linearized Drift for Nonlinear Stochastic Differential Equations

Download or read book On Estimation of the Linearized Drift for Nonlinear Stochastic Differential Equations written by Rafail Z. Chasʹminskij and published by . This book was released on 2001 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book American Type Options

    Book Details:
  • Author : Dmitrii S. Silvestrov
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 2015-03-03
  • ISBN : 3110389908
  • Pages : 672 pages

Download or read book American Type Options written by Dmitrii S. Silvestrov and published by Walter de Gruyter GmbH & Co KG. This book was released on 2015-03-03 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gives a systematical presentation of stochastic approximation methods 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 volume presents 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.

Book A Non linear Stochastic Volatility Model

Download or read book A Non linear Stochastic Volatility Model written by Eckhard Platen and published by . This book was released on 1997 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonlinear Causality  with Applications to Liquidity and Stochastic Volatility

Download or read book Nonlinear Causality with Applications to Liquidity and Stochastic Volatility written by Christian Gouriéroux and published by . This book was released on 2007 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Quantum Finance

Download or read book Quantum Finance written by Belal E. Baaquie and published by Cambridge University Press. This book was released on 2007-07-23 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book applies the mathematics and concepts of quantum mechanics and quantum field theory to the modelling of interest rates and the theory of options. Particular emphasis is placed on path integrals and Hamiltonians. Financial mathematics is dominated by stochastic calculus. The present book offers a formulation that is completely independent of that approach. As such many results emerge from the ideas developed by the author. This work will be of interest to physicists and mathematicians working in the field of finance, to quantitative analysts in banks and finance firms and to practitioners in the field of fixed income securities and foreign exchange. The book can also be used as a graduate text for courses in financial physics and financial mathematics.