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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.

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.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with Levy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it. The book's framework includes the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. Reviews the basics of probability distributions Analyzes a continuous time option pricing model (the so-called exponential Levy model) Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods Studies two multivariate settings that are suitable to explain joint extreme events Financial Models with Levy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.

An A to Z options trading guide for the new millennium and the new economy Written by professional trader and quantitative analyst Euan Sinclair, Option Trading is a comprehensive guide to this discipline covering everything from historical background, contract types, and market structure to volatility measurement, forecasting, and hedging techniques. This comprehensive guide presents the detail and practical information that professional option traders need, whether they're using options to hedge, manage money, arbitrage, or engage in structured finance deals. It contains information essential to anyone in this field, including option pricing and price forecasting, the Greeks, implied volatility, volatility measurement and forecasting, and specific option strategies. Explains how to break down a typical position, and repair positions Other titles by Sinclair: Volatility Trading Addresses the various concerns of the professional options trader Option trading will continue to be an important part of the financial landscape. This book will show you how to make the most of these profitable products, no matter what the market does.

The how-to guide to building an adaptive, productive business environment Graham Winter, author of the best-selling Think One Team, brings you First Be Nimble: A Story about How to Adapt, Innovate and Perform in a Volatile Business World. This book addresses the challenge of how to equip businesses to adapt and thrive in an unpredictable and demanding economy. Told in the form of a fable and illustrated with case studies and powerful tools, the book is designed to engage, inspire, and inform readers from all walks of business life. Helping leaders, teams, and whole organisations to bring their values to the frontline of the battle to be adaptive and productive, First Be Nimble shows readers how to align people and teams, collaborate and co-create with others, reduce resistance to change, boost trust, personal resilience, and performance, and prepare for the unique challenges of adaptive change. Helps businesses adapt to today's environment, learn to innovate, and build a «one team'» mentality Gives leaders the practical tools to facilitate change and foster the conversations that help people to learn and grow together Uses a unique, fable-style format, with inspirational examples, to bring key concepts to life While many business leaders are well versed in the importance of company values, they are often ignorant of how to bring them to life, and how to build an adaptive, high performing business. First Be Nimble is here to help.