Download or read book Estimating the Tail Shape Parameter from Option Prices written by Kam Hamidieh and published by . This book was released on 2015 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, a method to estimate the tail shape parameter of the risk neutral density from option prices is developed. Closed form pricing formulas for out-of-the-money European style options are derived. The pricing formulas satisfy many well known model-free no-arbitrage properties for the options. The focus is only on the tails of the risk neutral density and not on the entire body of the density as many works have already done this. The method is quite general, and applies to a large class of risk neutral densities. Our method can be used without interpolating the implied volatility, or even the knowledge of the current index value or the dividend yield or the risk free rate. This is in contrast to every other method that attempts to estimate the risk neutral density. A case study using S&P 500 Index options is given. In particular, the estimation of the tail shape of S&P 500 index just prior to the market turmoil of the September 2008 shows a thickening of the left tail but a thinning in the midst of the turmoil.

Download or read book Essays on Pricing Kernel Estimation Option Data Filtering and Risk neutral Density Tail Estimation written by Pirmin Meier and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first chapter introduces a new method to estimate the option-implied empirical pricing kernel. Departing from an adequate and economically motivated initial pricing kernel, we apply a customized functional gradient descent (FGD) algorithm based on B-splines. We empirically illustrate the estimation properties of the method using S & P 500 option data and find that the algorithm yields accurate estimates. In addition, we provide evidence of the superior predictive ability of our method in comparison with other approaches recently introduced in the empirical pricing kernel literature. The empirical pricing kernel is time-varying, which reflects changes in the relevant pricing kernel state variables. However, little is known about these factors driving the pricing kernel over time. Therefore, I present in the second chapter a time series model for the evolution of the empirical pricing kernel using a boosting approach based on regression trees. Given that trees have the ability to choose among a set of predictors the most relevant ones, I develop a tool to answer the main question regarding the principal pricing kernel driving factors. I show in the empirical part of the chapter that the influence of relevant driving factors such as volatility, financial and macroeconomic variables and sentiment measures substantially varies over time and I provide some insights on how they affect the pricing kernel shape. In the third chapter, we investigate how to estimate accurately the tails of the option-implied risk-neutral density, which is known to be a challenging problem. We review several methods and additionally introduce a new tail extension approach that combines the idea of price matching with the assumption of tails drawn from a generalized extreme value distribution. Based on a theoretical market model with known implied risk-neutral density, we conduct a performance analysis. We find that the best results are obtained either.

Download or read book Volatility and Time Series Econometrics written by Mark Watson and published by Oxford University Press. This book was released on 2010-02-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: A volume that celebrates and develops the work of Nobel Laureate Robert Engle, it includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics

Download or read book The Fundamentals of Heavy Tails written by Jayakrishnan Nair and published by Cambridge University Press. This book was released on 2022-06-09 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.

Download or read book Option Implied Risk Neutral Distributions and Risk Aversion written by Jens Carsten Jackwerth and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimating Volatility Levels for Option Pricing written by and published by . This book was released on 1997 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semi parametric Estimation of American Option Prices written by Patrick Gagliardini and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Methods in Financial Engineering written by Erricos Kontoghiorghes and published by Springer Science & Business Media. This book was released on 2008-02-26 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational models and methods are central to the analysis of economic and financial decisions. Simulation and optimisation are widely used as tools of analysis, modelling and testing. The focus of this book is the development of computational methods and analytical models in financial engineering that rely on computation. The book contains eighteen chapters written by leading researchers in the area on portfolio optimization and option pricing; estimation and classification; banking; risk and macroeconomic modelling. It explores and brings together current research tools and will be of interest to researchers, analysts and practitioners in policy and investment decisions in economics and finance.

Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.

Download or read book The Impact of Estimation Errors on the Option Pricing written by Patrycja Przytula and published by LAP Lambert Academic Publishing. This book was released on 2011-02 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Normal Inverse Gaussian distribution is used as a model of logarithmic returns of index values. We use the Esscher transform and the Black Scholes formula for the option pricing. The calibration of the distribution parameters afects the calculated prices of the European call options. The basic idea is to use a point estimation and its standard errors and then test combinations when the standard errors are added or subtracted to the point estimates. The study is applied to two indexes of the OMX Nordic Market, the OMXS30 and OMXC20. Our results on these indexes show that the parameter which in uences the option price mostly is the peakeness of the NIG distribution. The skewness parameter has the least in uence on the pricing. The option prices based on the NIG and Esscher transform are also compared with the pricing by using Black-Scholes formula and the market prices. The results show that for the OMXS30 index the NIG assumption and the Esscher transform provide calculated prices which are closer to the market prices that the Black-Scholes prices. For the OMXC20 we obtained contrary results.

Download or read book Risk Neutral Moment Based Estimation of Affine Option Pricing Models written by Bruno Feunou and published by . This book was released on 2017 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a novel methodology for estimating option pricing models based on risk-neutral moments. We synthesize the distribution extracted from a panel of option prices and exploit linear relationships between risk-neutral cumulants and latent factors within the continuous time affine stochastic volatility framework. We find that fitting the Andersen, Fusari, and Todorov (2015b) option valuation model to risk-neutral moments captures the bulk of the information in option prices. Our estimation strategy is effective, easy to implement, and robust, as it allows for a direct linear filtering of the latent factors and a quasi-maximum likelihood estimation of model parameters. From a practical perspective, employing risk-neutral moments instead of option prices also helps circumvent several sources of numerical errors and substantially lessens the computational burden inherent in working with a large panel of option contracts.

Download or read book Parameter Estimation and Behavior in the Black Scholes Model written by Deryl Winston Martin and published by . This book was released on 1984 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of Smooth Volatility Functions in Option Pricing Models written by Yohan Kim and published by . This book was released on 2001 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Characteristic Function Based Estimation of Affine Option Pricing Models written by Yannick Dillschneider and published by . This book was released on 2019 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we derive explicit expressions for certain joint moments of stock prices and option prices within a generic affine stochastic volatility model. Evaluation of each moment requires weighted inverse Fourier transformation of a function that is determined by the risk-neutral and real-world characteristic functions of the state vector. Explicit availability of such moment expressions allows to devise a novel GMM approach to jointly estimate real-world and risk-neutral parameters of affine stochastic volatility models using observed individual option prices. Moreover, the moment expressions may be used to include option price information into other existing moment-based estimation approaches.

Download or read book Generalized Parameter Functions for Option Pricing written by Christakis Charalambous and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We extend the benchmark nonlinear deterministic volatility regression functions of Dumas et al. (1998) to provide a semi-parametric method where an enhancement of the implied parameter values is used in the parametric option pricing models. Besides volatility, skewness and kurtosis of the asset return distribution can also be enhanced. Empirical results, using closing prices of the Samp;P 500 index call options (in one day ahead out-of-sample pricing tests), strongly support our method that compares favorably with a model that admits stochastic volatility and random jumps. Moreover, it is found to be superior in various robustness tests. Our semi-parametric approach is an effective remedy to the curse of dimensionality presented in nonparametric estimation and its main advantage is that it delivers theoretically consistent option prices and hedging parameters. The economic significance of the approach is tested in terms of hedging, where the evaluation and estimation loss functions are aligned.

Download or read book Estimating and Testing Option Pricing Models in an Economy with Transaction Costs written by Hyoung-jin Park and published by . This book was released on 2008 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: We examine the effect of transaction costs on implied volatility structure, parameter estimation, and hedging. Using simulations, we document that: (1) Transaction costs can generate the volatility smile phenomena even in the Black-Scholes economy. Especially, volatility smile effect is very strong for short-term options and it disappears as the maturity of options becomes longer. (2) Transaction costs cannot reject the true model falsely. All the parameter values that are supposed to be zero are not statistically significant even in the presence of transaction costs. (3) In hedging, the Black-Scholes model performs better than any other model in any case. This may result from the parameter instability of the cross-sectional estimation method.

Download or read book Nonlinear Valuation and Non Gaussian Risks in Finance written by Dilip B. Madan and published by Cambridge University Press. This book was released on 2022-02-03 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: What happens to risk as the economic horizon goes to zero and risk is seen as an exposure to a change in state that may occur instantaneously at any time? All activities that have been undertaken statically at a fixed finite horizon can now be reconsidered dynamically at a zero time horizon, with arrival rates at the core of the modeling. This book, aimed at practitioners and researchers in financial risk, delivers the theoretical framework and various applications of the newly established dynamic conic finance theory. The result is a nonlinear non-Gaussian valuation framework for risk management in finance. Risk-free assets disappear and low risk portfolios must pay for their risk reduction with negative expected returns. Hedges may be constructed to enhance value by exploiting risk interactions. Dynamic trading mechanisms are synthesized by machine learning algorithms. Optimal exposures are designed for option positioning simultaneously across all strikes and maturities.