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Nonparametric Pricing Of Multivariate Contingent Claims
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Book Synopsis Nonparametric Pricing of Multivariate Contingent Claims by : Joshua V. Rosenberg
Download or read book Nonparametric Pricing of Multivariate Contingent Claims written by Joshua V. Rosenberg and published by . This book was released on 2006 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Results from the method of copulas allow the multivariate risk-neutral density to be written as a product of marginal risk-neutral densities and a risk-neutral dependence function. A technique to price contingent claims can be developed using non-parametrically estimated marginal risk-neutral densities (based on options data) and a non-parametric dependence function (based on historical return data).Non-parametric estimation eliminates the pricing biases that result from incorrect parametric assumptions such as lognormality. The technique generates fitted multivariate contingent claim prices that are consistent with prices of traded univariate options. Under some general conditions, the objective and risk-neutral dependence functions are identical, which justifies the use of historical return data for the non-parametric dependence function, so that no data are required on traded multivariate claims.
Book Synopsis Semiparametric Pricing of Multivariate Contingent Claims by : Joshua Rosenberg
Download or read book Semiparametric Pricing of Multivariate Contingent Claims written by Joshua Rosenberg and published by . This book was released on 1999 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Semiparametric Pricing of Multivariate Contingent Claims by : Joshua V. Rosenberg
Download or read book Semiparametric Pricing of Multivariate Contingent Claims written by Joshua V. Rosenberg and published by . This book was released on 2009 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops and implements a methodology for pricing multivariate contingent claims (MVCC s) based on semiparametric estimation of the multivariate risk-neutral density function.This methodology generates MVCC prices which are consistent with current market prices of univariate contingent claims.This method allows for completely general marginal risk-neutral densities and is compatible with all univariate risk-neutral density estimation techniques. The univariate risk-neutral densities are related by their risk-neutral correlation, which is estimated using time-series data on asset returns and an empirical pricing kernel (Rosenberg and Engle, 1999). This permits the multivariate risk-neutral density to be identified without requiring observation of multivariate contingent claims prices. The semiparametric MVCC pricing technique is used for valuation of one-month options on the better of two equity index returns. Option contracts with payoffs dependent on are four equity indexpairs are considered: Samp;P500 - CAC40, Samp;P500 - NK225, Samp;P500 - FTSE100, and Samp;P500 - DAX30. Five marginal risk-neutral densities (Samp;P500, CAC40, NK225, FTSE100, and DAX30) are estimated semiparametrically using a cross-section of contemporaneously measured equity index option prices in each market. A bivariate risk-neutral Plackett (1965) density is constructed using the given marginals and risk-neutral correlation derived using an empirical pricing kernel and the historical joint density of the index returns. Price differences from a lognormal pricing formulausing historical and risk-neutral return moments are found to be significant.
Book Synopsis A Note on the Pricing of Multivariate Contingent Claims Under a Transformed-Gamma Distribution by : Luiz Vitiello
Download or read book A Note on the Pricing of Multivariate Contingent Claims Under a Transformed-Gamma Distribution written by Luiz Vitiello and published by . This book was released on 2014 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop a framework for pricing multivariate European-style contingent claims in a discrete-time economy based on a multivariate transformed-gamma distribution. In our model, each transformed-gamma distributed underlying asset depends on two terms: a idiosyncratic term and a systematic term, where the latter is the same for all underlying assets and has a direct impact on their correlation structure. Given our distributional assumptions and the existence of a representative agent with a standard utility function, we apply equilibrium arguments and provide sufficient conditions for obtaining preference-free contingent claim pricing equations. We illustrate the applicability of our framework by providing examples of preference-free contingent claim pricing models. Multivariate pricing models are of particular interest when payoffs depend on two or more underlying assets, such as crack and crush spread options, options to exchange one asset for another, and options with a stochastic strike price in general.
Book Synopsis A Lattice Approach for Pricing of Multivariate Contingent Claims by : Niklas Ekvall
Download or read book A Lattice Approach for Pricing of Multivariate Contingent Claims written by Niklas Ekvall and published by . This book was released on 1993 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pricing Multivariate Contingent Claims Using Estimated Risk-Neutral Density Functions by :
Download or read book Pricing Multivariate Contingent Claims Using Estimated Risk-Neutral Density Functions written by and published by . This book was released on 2008 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many asset price series exhibit time-varying volatility, jumps, and other features inconsistent with assumptions about the underlying price process made by standard multivariate contingent claims (MVCC) pricing models. This paper develops an interpolative technique for pricing MVCCs flexible NLS pricing that involves the estimation of a flexible multivariate risk-neutral density function implied by existing asset prices. As an application, the flexible NLS pricing technique is used to value several bivariate contingent claims dependent on foreign exchange rates in 1993 and 1994. The bivariate flexible risk-neutral density function more accurately prices existing options than the bivariate lognormal density implied by a multivariate geometric Brownian motion. In addition, the bivariate contingent claims analyzed have substantially different prices using the two density functions suggesting flexible NLS pricing may improve accuracy over standard methods.
Book Synopsis The Valuation of Multivariate Options by : Christian Hassold
Download or read book The Valuation of Multivariate Options written by Christian Hassold and published by diplom.de. This book was released on 2004-07-19 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inhaltsangabe:Abstract: During the last decades, capital markets have transformed rapidly. Derivative securities or more simply derivatives like swaps, futures, and options supplemented the trading of stocks and bonds. These financial products can frequently be seen in the media: Due to derivatives, Procter & Gamble lost $150 million in 1994, Barings Bank lost $1.3 billion in 1995 and Long-Term Capital Management (LTCM) lost $3.5 billion in 1998. Though these figures seem daunting, derivatives can be useful financial instruments. Applications include risk management, speculation, reduced transaction costs, and regulatory arbitrage. Theory and practice of option valuation were revolutionized in 1973, when Fischer Black and Myron Scholes published their celebrated Black Scholes formula in the landmark paper The pricing of options and corporate liabilities . Afterwards, a vast amount of papers on option valuation was published which employ all kinds of stochastic processes. Thereby, the special features of financial return data are tried to be taken into account. Advancing option valuation theory to options with multiple underlyings, lead to the problem that the dependence structure of the underlying securities needs to be considered. Though linear correlation is a widely used dependence measure, it may be inappropriate for multivariate return data. Throughout the last years, dependence modelling through copulas has become common. Copulas are multivariate distributions on the d-dimensional unit-hyper-square which couples d marginal distributions to a joint distribution. Copulas can be used to construct dependence measures like the rank correlation coefficients of Spearman or Kendall. They are also a useful tool in the context of option valuation. The prices of multivariate options depend on the distributional assumptions of stock price changes and the dependence structure. This thesis exhibits the features of multivariate financial return data. Evidence of (multi-)non-normality is presented. A general overview on multivariate option valuation theory is given. A nonparametric model and two Esscher models are introduced in detail. Then, the multivariate normal and the multivariate normal inverse Gaussian distribution are assumed as return distributions for an empirical study. The study exhibits the influence of the dependence structure and the properties of the assumed return distribution on option prices. Inhaltsverzeichnis:Table of [...]
Book Synopsis Multi-moment Asset Allocation and Pricing Models by : Emmanuel Jurczenko
Download or read book Multi-moment Asset Allocation and Pricing Models written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2006-10-02 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: While mainstream financial theories and applications assume that asset returns are normally distributed and individual preferences are quadratic, the overwhelming empirical evidence shows otherwise. Indeed, most of the asset returns exhibit “fat-tails” distributions and investors exhibit asymmetric preferences. These empirical findings lead to the development of a new area of research dedicated to the introduction of higher order moments in portfolio theory and asset pricing models. Multi-moment asset pricing is a revolutionary new way of modeling time series in finance which allows various degrees of long-term memory to be generated. It allows risk and prices of risk to vary through time enabling the accurate valuation of long-lived assets. This book presents the state-of-the art in multi-moment asset allocation and pricing models and provides many new developments in a single volume, collecting in a unified framework theoretical results and applications previously scattered throughout the financial literature. The topics covered in this comprehensive volume include: four-moment individual risk preferences, mathematics of the multi-moment efficient frontier, coherent asymmetric risks measures, hedge funds asset allocation under higher moments, time-varying specifications of (co)moments and multi-moment asset pricing models with homogeneous and heterogeneous agents. Written by leading academics, Multi-moment Asset Allocation and Pricing Models offers a unique opportunity to explore the latest findings in this new field of research.
Book Synopsis Dynamic Copula Methods in Finance by : Umberto Cherubini
Download or read book Dynamic Copula Methods in Finance written by Umberto Cherubini and published by John Wiley & Sons. This book was released on 2011-10-20 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest tools and techniques for pricing and risk management This book introduces readers to the use of copula functions to represent the dynamics of financial assets and risk factors, integrated temporal and cross-section applications. The first part of the book will briefly introduce the standard the theory of copula functions, before examining the link between copulas and Markov processes. It will then introduce new techniques to design Markov processes that are suited to represent the dynamics of market risk factors and their co-movement, providing techniques to both estimate and simulate such dynamics. The second part of the book will show readers how to apply these methods to the evaluation of pricing of multivariate derivative contracts in the equity and credit markets. It will then move on to explore the applications of joint temporal and cross-section aggregation to the problem of risk integration.
Author :Torben Gustav Andersen Publisher :Springer Science & Business Media ISBN 13 :3540712976 Total Pages :1045 pages Book Rating :4.5/5 (47 download)
Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen
Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Book Synopsis The Derivatives Sourcebook by : Terence Lim
Download or read book The Derivatives Sourcebook written by Terence Lim and published by Now Publishers Inc. This book was released on 2006 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Derivatives Sourcebook is a citation study and classification system that organizes the many strands of the derivatives literature and assigns each citation to a category. Over 1800 research articles are collected and organized into a simple web-based searchable database. We have also included the 1997 Nobel lectures of Robert Merton and Myron Scholes as a backdrop to this literature.
Book Synopsis Pricing Multivariate Contingent Claims Using Estimated Risk- Neutral Density Functions by : Joshua V. Rosenberg
Download or read book Pricing Multivariate Contingent Claims Using Estimated Risk- Neutral Density Functions written by Joshua V. Rosenberg and published by . This book was released on 1998 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Economic Forecasting by : Graham Elliott
Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-08-23 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics
Book Synopsis Nonparametric Finance by : Jussi Klemelä
Download or read book Nonparametric Finance written by Jussi Klemelä and published by John Wiley & Sons. This book was released on 2018-03-13 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Machine Learning in Finance, With Mathematical Background, Data Visualization, and R Nonparametric function estimation is an important part of machine learning, which is becoming increasingly important in quantitative finance. Nonparametric Finance provides graduate students and finance professionals with a foundation in nonparametric function estimation and the underlying mathematics. Combining practical applications, mathematically rigorous presentation, and statistical data analysis into a single volume, this book presents detailed instruction in discrete chapters that allow readers to dip in as needed without reading from beginning to end. Coverage includes statistical finance, risk management, portfolio management, and securities pricing to provide a practical knowledge base, and the introductory chapter introduces basic finance concepts for readers with a strictly mathematical background. Economic significance is emphasized over statistical significance throughout, and R code is provided to help readers reproduce the research, computations, and figures being discussed. Strong graphical content clarifies the methods and demonstrates essential visualization techniques, while deep mathematical and statistical insight backs up practical applications. Written for the leading edge of finance, Nonparametric Finance: • Introduces basic statistical finance concepts, including univariate and multivariate data analysis, time series analysis, and prediction • Provides risk management guidance through volatility prediction, quantiles, and value-at-risk • Examines portfolio theory, performance measurement, Markowitz portfolios, dynamic portfolio selection, and more • Discusses fundamental theorems of asset pricing, Black-Scholes pricing and hedging, quadratic pricing and hedging, option portfolios, interest rate derivatives, and other asset pricing principles • Provides supplementary R code and numerous graphics to reinforce complex content Nonparametric function estimation has received little attention in the context of risk management and option pricing, despite its useful applications and benefits. This book provides the essential background and practical knowledge needed to take full advantage of these little-used methods, and turn them into real-world advantage. Jussi Klemelä, PhD, is Adjunct Professor at the University of Oulu. His research interests include nonparametric function estimation, density estimation, and data visualization. He is the author of Smoothing of Multivariate Data: Density Estimation and Visualization and Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance.
Download or read book The Journal of Derivatives written by and published by . This book was released on 2002 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Counting Statistics for Dependent Random Events by : Enrico Bernardi
Download or read book Counting Statistics for Dependent Random Events written by Enrico Bernardi and published by Springer Nature. This book was released on 2021-03-22 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on counting statistics presents a novel copula-based approach to counting dependent random events. It combines clustering, combinatorics-based algorithms and dependence structure in order to tackle and simplify complex problems, without disregarding the hierarchy of or interconnections between the relevant variables. These problems typically arise in real-world applications and computations involving big data in finance, insurance and banking, where experts are confronted with counting variables in monitoring random events. In this new approach, combinatorial distributions of random events are the core element. In order to deal with the high-dimensional features of the problem, the combinatorial techniques are used together with a clustering approach, where groups of variables sharing common characteristics and similarities are identified and the dependence structure within groups is taken into account. The original problems can then be modeled using new classes of copulas, referred to here as clusterized copulas, which are essentially based on preliminary groupings of variables depending on suitable characteristics and hierarchical aspects. The book includes examples and real-world data applications, with a special focus on financial applications, where the new algorithms’ performance is compared to alternative approaches and further analyzed. Given its scope, the book will be of interest to master students, PhD students and researchers whose work involves or can benefit from the innovative methodologies put forward here. It will also stimulate the empirical use of new approaches among professionals and practitioners in finance, insurance and banking.
Download or read book Credit Risk written by Niklas Wagner and published by CRC Press. This book was released on 2008-05-28 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring contributions from leading international academics and practitioners, Credit Risk: Models, Derivatives, and Management illustrates how a risk management system can be implemented through an understanding of portfolio credit risks, a set of suitable models, and the derivation of reliable empirical results. Divided into six sectio
