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Valuing Credit Risk - Variance Reduction Techniques for Monte Carlo Methods ab 4.99 € als epub eBook: . Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik,

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From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential. The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.

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Valuing Credit Risk - Variance Reduction Techniques for Monte Carlo Methods ab 4.99 EURO

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This book gives an overview of one of the most widespread Value at Risk Models in use in most of risk management departments across the financial industry. VaR calculates the worst expected loss over a given horizon at a given confidence level under normal market conditions. VaR estimates can be calculated for various types of risk: market, credit, operational, etc. I focused only on Market Risk. Market risk is the risk that the value of an investment will decrease due to moves in market factors such as prices, rates, volatilities and other relevant market parameters. In such a context, VaR provides a single number summarizing the organization's exposure to market risk and the likelihood of an unfavorable move. There are mainly three groups of VaR: Analytical (also called Parametric), Historical Simulations, and Monte Carlo Simulations. Non Parametric: GARCH, EGARCH. Semi Parametric: CaVaR, Extreme Value Theory etc. Here I have used parametric and non parametric VaR models for NSE daily and intraday data.

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In developing countries the provision of housing finance is very problematic because of the volatile macroeconomic environment and the lack of regulatory framework that supports collateralised lending. As an emerging market, Turkey has experienced the problem of economic instability with highly volatile inflation from the 1980s to the early 2000s. This book describes the Turkish government's housing policy for financing the public sector housing during the late 1990s and evaluates the performance of inflation-indexed mortgage contract, designed for middle-income civil servants. It demonstrates the use of Option pricing models to price the credit risk of inflation-indexed mortgages. The emphasis on using a backward pricing method rather than Monte Carlo simulation method to evaluate inflation-indexed mortgage with its embedded default option, sets this book apart. This book also discusses the recent developments in the Turkish real estate sector and the key issues in the creation of secondary mortgage market in Turkey. The book will provide important implications for professionals in mortgage sector of other developing mortgage markets, where the inflation uncertainty is high.

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Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques.This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios.The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."

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The interaction between mathematicians and statisticians has been shown to be an eective approach for dealing with actuarial, insurance and financial problems, both from an academic perspective and from an operative one. The collection of original papers presented in this volume pursues precisely this purpose. It covers a wide variety of subjects in actuarial, insurance and finance fields, all treated in the light of the successful cooperation between the above two quantitative approaches.The papers published in this volume present theoretical and methodological contributions and their applications to real contexts. With respect to the theoretical and methodological contributions, some of the considered areas of investigation are: actuarial models, alternative testing approaches, behavioral finance, clustering techniques, coherent and non-coherent risk measures, credit scoring approaches, data envelopment analysis, dynamic stochastic programming, financial contagion models, financial ratios, intelligent financial trading systems, mixture normality approaches, Monte Carlo-based methods, multicriteria methods, nonlinear parameter estimation techniques, nonlinear threshold models, particle swarm optimization, performance measures, portfolio optimization, pricing methods for structured and non-structured derivatives, risk management, skewed distribution analysis, solvency analysis, stochastic actuarial valuation methods, variable selection models, time series analysis tools. As regards the applications, they are related to real problems associated, among the others, to: banks, collateralized fund obligations, credit portfolios, defined benefit pension plans, double-indexed pension annuities, efficient-market hypothesis, exchange markets, financial time series, firms, hedge funds, non-life insurance companies, returns distributions, socially responsible mutual funds, unit-linked contracts.This book is aimed at academics, Ph.D. students, practitioners, professionals and researchers. But it will also be of interest to readers with some quantitative background knowledge.

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This research monograph provides an introduction to tractable multidimensional diffusion models, where transition densities, Laplace transforms, Fourier transforms, fundamental solutions or functionals can be obtained in explicit form. The book also provides an introduction to the use of Lie symmetry group methods for diffusions, which allows to compute a wide range of functionals. Besides the well-known methodology on affine diffusions it presents a novel approach to affine processes with applications in finance. Numerical methods, including Monte Carlo and quadrature methods, are discussed together with supporting material on stochastic processes. Applications in finance, for instance, on credit risk and credit valuation adjustment are included in the book. The functionals of multidimensional diffusions analyzed in this book are significant for many areas of application beyond finance. The book is aimed at a wide readership, and develops an intuitive and rigorous understanding of the mathematics underlying the derivation of explicit formulas for functionals of multidimensional diffusions.

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