Estimation Of Volatilities Under A Merton S Jump Diffusion Model And An Uncertain Volatility Model

Energy Risk Modeling is a primer on statistical methods for managers, students and anybody interested in the field. Illustrated through elementary and more advanced statistical Methods, it is primarily aimed at those individuals who need a gentle introduction in how to go about using statistical methods for modeling energy price risk. Statistical ideas are presented by outlining the necessary concepts and illustrating how these ideas can be implemented. This is the first energy risk book on the market to focus specifically on the role of statistical methods. Its practical approach makes the book a very useful reference and an interesting read.

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.

The disciplines of financial engineering and numerical computation differ greatly, however computational methods are used in a number of ways across the field of finance. It is the aim of this book to explain how such methods work in financial engineering; specifically the use of numerical methods as tools for computational finance. By concentrating on the field of option pricing, a core task of financial engineering and risk analysis, this book explores a wide range of computational tools in a coherent and focused manner and will be of use to the entire field of computational finance. Starting with an introductory chapter that presents the financial and stochastic background, the remainder of the book goes on to detail computational methods using both stochastic and deterministic approaches. Now in its fifth edition, Tools for Computational Finance has been significantly revised and contains: A new chapter on incomplete markets which links to new appendices on Viscosity solutions and the Dupire equation; Several new parts throughout the book such as that on the calculation of sensitivities (Sect. 3.7) and the introduction of penalty methods and their application to a two-factor model (Sect. 6.7) Additional material in the field of analytical methods including Kim’s integral representation and its computation Guidelines for comparing algorithms and judging their efficiency An extended chapter on finite elements that now includes a discussion of two-asset options Additional exercises, figures and references Written from the perspective of an applied mathematician, methods are introduced as tools within the book for immediate and straightforward application. A ‘learning by calculating’ approach is adopted throughout this book enabling readers to explore several areas of the financial world. Interdisciplinary in nature, this book will appeal to advanced undergraduate students in mathematics, engineering and other scientific disciplines as well as professionals in financial engineering.

"Elements of Financial Risk Management" focuses on implementation, especially techniques which facilitate "bridging the gap" between standard textbooks on risk and real-life risk management systems. This title should appeal to practitioners in the financial services and investment industries, as well as graduate students and advanced undergraduates who want exposure to these techniques.

Modeling and Pricing of Swaps for Financial and Energy Markets with Stochastic Volatilities is devoted to the modeling and pricing of various kinds of swaps, such as those for variance, volatility, covariance, correlation, for financial and energy markets with different stochastic volatilities, which include CIR process, regime-switching, delayed, mean-reverting, multi-factor, fractional, Levy-based, semi-Markov and COGARCH(1,1). One of the main methods used in this book is change of time method. The book outlines how the change of time method works for different kinds of models and problems arising in financial and energy markets and the associated problems in modeling and pricing of a variety of swaps. The book also contains a study of a new model, the delayed Heston model, which improves the volatility surface fitting as compared with the classical Heston model. The author calculates variance and volatility swaps for this model and provides hedging techniques. The book considers content on the pricing of variance and volatility swaps and option pricing formula for mean-reverting models in energy markets. Some topics such as forward and futures in energy markets priced by multi-factor Levy models and generalization of Black-76 formula with Markov-modulated volatility are part of the book as well, and it includes many numerical examples such as S&P60 Canada Index, S&P500 Index and AECO Natural Gas Index. Contents:Stochastic VolatilityStochastic Volatility ModelsSwapsChange of Time MethodsBlack-Scholes Formula by Change of Time MethodModeling and Pricing of Swaps for Heston ModelModeling and Pricing of Variance Swaps for Stochastic Volatilities with DelayModeling and Pricing of Variance Swaps for Multi-Factor Stochastic Volatilities with DelayPricing Variance Swaps for Stochastic Volatilities with Delay and JumpsVariance Swap for Local Lévy-Based Stochastic Volatility with DelayDelayed Heston Model: Improvement of the Volatility Surface FittingPricing and Hedging of Volatility Swap in the Delayed Heston ModelPricing of Variance and Volatility Swaps with Semi-Markov VolatilitiesCovariance and Correlation Swaps for Markov-Modulated VolatilitiesVolatility and Variance Swaps for the COGARCH(1,1) ModelVariance and Volatility Swaps for Volatilities Driven by Fractional Brownian MotionVariance and Volatility Swaps in Energy MarketsExplicit Option Pricing Formula for a Mean-Reverting Asset in Energy MarketsForward and Futures in Energy Markets: Multi-Factor Lévy ModelsGeneralization of Black-76 Formula: Markov-Modulated Volatility Readership: Post-graduate level researchers and professionals with interest in the modeling and pricing of swaps for energy and financial markets. Keywords:Stochastic Volatilities;Variance, Volatility, Covariance, Correlation Swaps;Change of Time;Option Pricing;Stochastic Volatilities with Delay;Multi-Factor Stochastic Volatilities Models;Regime-Switching Stochastic Volatilities;Levy-Based Stochastic Volatilities with Delay;COGARCH Stochastic Volatility;Stochastic Volatility Driven by Fractional Brownian Motion;Delayed Heston Model;Semi-Markov Stochastic Volatilities;Energy Markets;Forward and Futures in Energy MarketsKey Features:Provides coverage on topic of swaps not covered in such detail by other titles, in relation to energy and financial marketsIn particular, offers a comprehensive treatment of various types of swaps and a variety of stochastic volatility models, in relation to energy and financial marketsReviews: “A separate session about the derivative pricing on the energy market is included. Moreover, this book provides many numerical examples to illustrate applications of the stochastic volatility pricing models. This book is quite useful not only for academics and researchers in mathematical and energy finance, but also for practitioners in the financial and energy industries.” Zentralblatt MATH

This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.

The latest research on measuring, managing and pricing financial risk. Three broad perspectives are considered: financial risk in non-financial corporations; in financial intermediaries such as banks; and finally within the context of a portfolio of securities of different credit quality and marketability.

This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.