Maximum Likelihood Tests of Option Pricing Models
Author | : Giovanni Barone-Adesi |
Publisher | : |
Total Pages | : 32 |
Release | : 1985 |
Genre | : Options (Finance) |
ISBN | : |
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Author | : Giovanni Barone-Adesi |
Publisher | : |
Total Pages | : 32 |
Release | : 1985 |
Genre | : Options (Finance) |
ISBN | : |
Author | : Jeffrey Owen Katz |
Publisher | : McGraw Hill Professional |
Total Pages | : 449 |
Release | : 2005-03-21 |
Genre | : Business & Economics |
ISBN | : 0071454705 |
Advanced Option Pricing Models details specific conditions under which current option pricing models fail to provide accurate price estimates and then shows option traders how to construct improved models for better pricing in a wider range of market conditions. Model-building steps cover options pricing under conditional or marginal distributions, using polynomial approximations and “curve fitting,” and compensating for mean reversion. The authors also develop effective prototype models that can be put to immediate use, with real-time examples of the models in action.
Author | : Chenghu Ma |
Publisher | : World Scientific |
Total Pages | : 818 |
Release | : 2011 |
Genre | : Business & Economics |
ISBN | : 184816632X |
This book provides a broad introduction to modern asset pricing theory. The theory is self-contained and unified in presentation. Both the no-arbitrage and the general equilibrium approaches of asset pricing theory are treated coherently within the general equilibrium framework. It fills a gap in the body of literature on asset pricing for being both advanced and comprehensive. The absence of arbitrage opportunities represents a necessary condition for equilibrium in the financial markets. However, the absence of arbitrage is not a sufficient condition for establishing equilibrium. These interrelationships are overlooked by the proponents of the no-arbitrage approach to asset pricing.This book also tackles recent advancement on inversion problems raised in asset pricing theory, which include the information role of financial options and the information content of term structure of interest rates and interest rates contingent claims.The inclusion of the proofs and derivations to enhance the transparency of the underlying arguments and conditions for the validity of the economic theory made it an ideal advanced textbook or reference book for graduate students specializing in financial economics and quantitative finance. The detailed explanations will capture the interest of the curious reader, and it is complete enough to provide the necessary background material needed to delve deeper into the subject and explore the research literature.Postgraduate students in economics with a good grasp of calculus, linear algebra, and probability and statistics will find themselves ready to tackle topics covered in this book. They will certainly benefit from the mathematical coverage in stochastic processes and stochastic differential equation with applications in finance. Postgraduate students in financial mathematics and financial engineering will also benefit, not only from the mathematical tools introduced in this book, but also from the economic ideas underpinning the economic modeling of financial markets.Both these groups of postgraduate students will learn the economic issues involved in financial modeling. The book can be used as an advanced text for Masters and PhD students in all subjects of financial economics, financial mathematics, mathematical finance, and financial engineering. It is also an ideal reference for practitioners and researchers in the subjects.
Author | : William Gould |
Publisher | : Stata Press |
Total Pages | : 352 |
Release | : 2010-10-27 |
Genre | : Mathematics |
ISBN | : 9781597180788 |
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Author | : Jianwei Zhu |
Publisher | : Springer Science & Business Media |
Total Pages | : 188 |
Release | : 2000 |
Genre | : Business & Economics |
ISBN | : 9783540679165 |
The sound modeling of the smile effect is an important issue in quantitative finance as, for more than a decade, the Fourier transform has established itself as the most efficient tool for deriving closed-form option pricing formulas in various model classes. This book describes the applications of the Fourier transform to the modeling of volatility smile, followed by a comprehensive treatment of option valuation in a unified framework, covering stochastic volatilities and interest rates, Poisson and Levy jumps, including various asset classes such as equity, FX and interest rates, as well as various numberical examples and prototype programming codes. Readers will benefit from this book not only by gaining an overview of the advanced theory and the vast range of literature on these topics, but also by receiving first-hand feedback on the practical applications and implementations of the theory. The book is aimed at financial engineers, risk managers, graduate students and researchers.
Author | : Stefano M. Iacus |
Publisher | : John Wiley & Sons |
Total Pages | : 402 |
Release | : 2011-02-23 |
Genre | : Business & Economics |
ISBN | : 1119990203 |
Presents inference and simulation of stochastic process in the field of model calibration for financial times series modelled by continuous time processes and numerical option pricing. Introduces the bases of probability theory and goes on to explain how to model financial times series with continuous models, how to calibrate them from discrete data and further covers option pricing with one or more underlying assets based on these models. Analysis and implementation of models goes beyond the standard Black and Scholes framework and includes Markov switching models, Lévy models and other models with jumps (e.g. the telegraph process); Topics other than option pricing include: volatility and covariation estimation, change point analysis, asymptotic expansion and classification of financial time series from a statistical viewpoint. The book features problems with solutions and examples. All the examples and R code are available as an additional R package, therefore all the examples can be reproduced.
Author | : William Gould |
Publisher | : Stata Press |
Total Pages | : 312 |
Release | : 2006 |
Genre | : Computers |
ISBN | : 1597180122 |
Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions. New ml commands and their functions: constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS) ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)
Author | : G. S. Maddala |
Publisher | : |
Total Pages | : 760 |
Release | : 1996-12-11 |
Genre | : Business & Economics |
ISBN | : |
A comprehensive reference work for teaching at graduate level and research in empirical finance. The chapters cover a wide range of statistical and probabilistic methods applied to a variety of financial methods and are written by internationally renowned experts.