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Author: Lorenzo Bergomi
Publisher: CRC Press
ISBN: 1482244071
Category : Business & Economics
Languages : en
Pages : 520
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Book Description
Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility? How do we design models and assess their relevance? How do we tell which models are usable and when does c
Author: Lorenzo Bergomi
Publisher: CRC Press
ISBN: 1482244071
Category : Business & Economics
Languages : en
Pages : 520
Get Book Here
Book Description
Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility? How do we design models and assess their relevance? How do we tell which models are usable and when does c
Author: Stephane Goutte
Publisher: World Scientific
ISBN: 9813278390
Category : Business & Economics
Languages : en
Pages : 827
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Book Description
Modeling the dynamics of energy markets has become a challenging task. The intensification of their financialization since 2004 had made them more complex but also more integrated with other tradable asset classes. More importantly, their large and frequent fluctuations in terms of both prices and volatility, particularly in the aftermath of the global financial crisis 2008-2009, posit difficulties for modeling and forecasting energy price behavior and are primary sources of concerns for macroeconomic stability and general economic performance.This handbook aims to advance the debate on the theories and practices of quantitative energy finance while shedding light on innovative results and technical methods applied to energy markets. Its primary focus is on the recent development and applications of mathematical and quantitative approaches for a better understanding of the stochastic processes that drive energy market movements. The handbook is designed for not only graduate students and researchers but also practitioners and policymakers.
Author: Emanuel Derman
Publisher: John Wiley & Sons
ISBN: 1118959167
Category : Business & Economics
Languages : en
Pages : 528
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Book Description
The Volatility Smile The Black-Scholes-Merton option model was the greatest innovation of 20th century finance, and remains the most widely applied theory in all of finance. Despite this success, the model is fundamentally at odds with the observed behavior of option markets: a graph of implied volatilities against strike will typically display a curve or skew, which practitioners refer to as the smile, and which the model cannot explain. Option valuation is not a solved problem, and the past forty years have witnessed an abundance of new models that try to reconcile theory with markets. The Volatility Smile presents a unified treatment of the Black-Scholes-Merton model and the more advanced models that have replaced it. It is also a book about the principles of financial valuation and how to apply them. Celebrated author and quant Emanuel Derman and Michael B. Miller explain not just the mathematics but the ideas behind the models. By examining the foundations, the implementation, and the pros and cons of various models, and by carefully exploring their derivations and their assumptions, readers will learn not only how to handle the volatility smile but how to evaluate and build their own financial models. Topics covered include: The principles of valuation Static and dynamic replication The Black-Scholes-Merton model Hedging strategies Transaction costs The behavior of the volatility smile Implied distributions Local volatility models Stochastic volatility models Jump-diffusion models The first half of the book, Chapters 1 through 13, can serve as a standalone textbook for a course on option valuation and the Black-Scholes-Merton model, presenting the principles of financial modeling, several derivations of the model, and a detailed discussion of how it is used in practice. The second half focuses on the behavior of the volatility smile, and, in conjunction with the first half, can be used for as the basis for a more advanced course.
Author: Paul Glasserman
Publisher: Springer Science & Business Media
ISBN: 0387216170
Category : Mathematics
Languages : en
Pages : 603
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Book Description
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
Author: Jim Gatheral
Publisher:
ISBN: 9781119202073
Category : Options (Finance)
Languages : en
Pages : 179
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Book Description
Author: Jean-Pierre Fouque
Publisher: Cambridge University Press
ISBN: 9780521791632
Category : Business & Economics
Languages : en
Pages : 222
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Book Description
This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.
Author: Willem Hundsdorfer
Publisher: Springer Science & Business Media
ISBN: 3662090171
Category : Technology & Engineering
Languages : en
Pages : 479
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Book Description
Unique book on Reaction-Advection-Diffusion problems
Author: Jean-Pierre Fouque
Publisher: Cambridge University Press
ISBN: 113950245X
Category : Mathematics
Languages : en
Pages : 456
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Book Description
Building upon the ideas introduced in their previous book, Derivatives in Financial Markets with Stochastic Volatility, the authors study the pricing and hedging of financial derivatives under stochastic volatility in equity, interest-rate, and credit markets. They present and analyze multiscale stochastic volatility models and asymptotic approximations. These can be used in equity markets, for instance, to link the prices of path-dependent exotic instruments to market implied volatilities. The methods are also used for interest rate and credit derivatives. Other applications considered include variance-reduction techniques, portfolio optimization, forward-looking estimation of CAPM 'beta', and the Heston model and generalizations of it. 'Off-the-shelf' formulas and calibration tools are provided to ease the transition for practitioners who adopt this new method. The attention to detail and explicit presentation make this also an excellent text for a graduate course in financial and applied mathematics.
Author: Alireza Javaheri
Publisher: John Wiley & Sons
ISBN: 111894397X
Category : Business & Economics
Languages : en
Pages : 325
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Book Description
A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate data Integrate past observation with Bayesian probability Exploit posterior distribution of the hidden state for optimal estimation Boost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.
Author: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
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Book Description
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
