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Dynamic Conditional Correlation With Elliptical Distributions
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Book Synopsis Dynamic Conditional Correlation with Elliptical Distributions by : Matteo M. Pelagatti
Download or read book Dynamic Conditional Correlation with Elliptical Distributions written by Matteo M. Pelagatti and published by . This book was released on 2013 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Dynamic Conditional Correlation (DCC) model of Engle has made the estimation of multivariate GARCH models feasible for reasonably big vectors of securities' returns. In the present paper we show how Engle's two-steps estimate of the model can be easily extended to elliptical conditional distributions and apply different leptokurtic DCC models to the evaluation of the Value at Risk (VaR) of a portfolio of realistic dimensions. A free software (Ox class) written by the authors to carry out all the required computations is presented as well.
Book Synopsis On the Devolatized Returns and Dynamic Conditional Correlations GARCH Modeling in Selected European Indices by : Stavros Stavroyiannis
Download or read book On the Devolatized Returns and Dynamic Conditional Correlations GARCH Modeling in Selected European Indices written by Stavros Stavroyiannis and published by . This book was released on 2013 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: Typical issues of multivariate GARCH models are dimensionality, which is time consuming, both in terms of computations and their programming, and the availability of very few distributional schemes, since linear correlations are a natural dependence measure, only if the joint distribution of the variables is elliptical. We consider the new approach of devolatized returns, computed as returns standardized by realized volatilities, rather than by GARCH-type volatilities estimates. As a case study, we examine several European indices, and the methodology incorporates a multivariate T-student version of the Dynamic Conditional Correlations GARCH model. The time series under consideration and the results are subjected to several diagnostic tests, including the temporal volatilities and correlations of the asset returns, the validity of the T-DCC model using Value-at-Risk, the empirical cumulative distribution function of the probability integral transform variable, and forecasts of the conditional volatility and correlations. The concluding remarks are consistent, and in agreement with the new devolatized returns concept.
Book Synopsis Financial Modeling Under Non-Gaussian Distributions by : Eric Jondeau
Download or read book Financial Modeling Under Non-Gaussian Distributions written by Eric Jondeau and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Credible Asset Allocation, Optimal Transport Methods, and Related Topics by : Songsak Sriboonchitta
Download or read book Credible Asset Allocation, Optimal Transport Methods, and Related Topics written by Songsak Sriboonchitta and published by Springer Nature. This book was released on 2022-07-29 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes state-of-the-art economic ideas and how these ideas can be (and are) used to make economic decision (in particular, to optimally allocate assets) and to gauge the results of different economic decisions (in particular, by using optimal transport methods). Special emphasis is paid to machine learning techniques (including deep learning) and to different aspects of quantum econometrics—when quantum physics and quantum computing models are techniques are applied to study economic phenomena. Applications range from more traditional economic areas to more non-traditional topics such as economic aspects of tourism, cryptocurrencies, telecommunication infrastructure, and pandemic. This book helps student to learn new techniques, practitioners to become better knowledgeable of the state-of-the-art econometric techniques, and researchers to further develop these important research directions
Book Synopsis Modeling and Valuation of Energy Structures by : Daniel Mahoney
Download or read book Modeling and Valuation of Energy Structures written by Daniel Mahoney and published by Springer. This book was released on 2016-01-26 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Commodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling.
Book Synopsis Handbook of Volatility Models and Their Applications by : Luc Bauwens
Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-04-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.
Book Synopsis Statistical Modeling Using Local Gaussian Approximation by : Dag Tjøstheim
Download or read book Statistical Modeling Using Local Gaussian Approximation written by Dag Tjøstheim and published by Academic Press. This book was released on 2021-10-05 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution, perhaps, the most well-known and most used distribution in statistics, to a large class of non-Gaussian and nonlinear situations through local approximation. This extension enables the reader to follow new methods in assessing dependence and conditional dependence, in estimating probability and spectral density functions, and in discrimination. Chapters in this release cover Parametric, nonparametric, locally parametric, Dependence, Local Gaussian correlation and dependence, Local Gaussian correlation and the copula, Applications in finance, and more. Additional chapters explores Measuring dependence and testing for independence, Time series dependence and spectral analysis, Multivariate density estimation, Conditional density estimation, The local Gaussian partial correlation, Regression and conditional regression quantiles, and a A local Gaussian Fisher discriminant. Reviews local dependence modeling with applications to time series and finance markets Introduces new techniques for density estimation, conditional density estimation, and tests of conditional independence with applications in economics Evaluates local spectral analysis, discovering hidden frequencies in extremes and hidden phase differences Integrates textual content with three useful R packages
Book Synopsis Energy Economics and Financial Markets by : André Dorsman
Download or read book Energy Economics and Financial Markets written by André Dorsman and published by Springer Science & Business Media. This book was released on 2012-10-12 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy issues feature frequently in the economic and financial press. Specific examples of topical energy issues come from around the globe and often concern economics and finance. The importance of energy production, consumption and trade raises fundamental economic issues that impact the global economy and financial markets. This volume presents research on energy economics and financial markets related to the themes of supply and demand, environmental impact and renewables, energy derivatives trading, and finance and energy. The contributions by experts in their fields take a global perspective, as well as presenting cases from various countries and continents.
Book Synopsis Elliptically Contoured Models in Statistics and Portfolio Theory by : Arjun K. Gupta
Download or read book Elliptically Contoured Models in Statistics and Portfolio Theory written by Arjun K. Gupta and published by Springer Science & Business Media. This book was released on 2013-09-07 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions. There are two additional chapters, and all the original chapters of this classic text have been updated. Resources in this book will be valuable for researchers, practitioners, and graduate students in statistics and related fields of finance and engineering. Those interested in multivariate statistical analysis and its application to portfolio theory will find this text immediately useful. In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Elliptical distributions have also increased their popularity in finance because of the ability to model heavy tails usually observed in real data. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. A noteworthy function of this book is the collection of the most important results on the theory of matrix variate elliptically contoured distributions that were previously only available in the journal-based literature. The content is organized in a unified manner that can serve an a valuable introduction to the subject.
Book Synopsis Econometric Analysis of Financial and Economic Time Series by : Thomas B. Fomby
Download or read book Econometric Analysis of Financial and Economic Time Series written by Thomas B. Fomby and published by Emerald Group Publishing. This book was released on 2006-03-01 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Talks about the time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, application of the technique of boosting in volatility forecasting, and more.
Book Synopsis Dynamic Conditional Correlation by : Robert F. Engle
Download or read book Dynamic Conditional Correlation written by Robert F. Engle and published by . This book was released on 2008 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with univariate or two step methods based on the likelihood function. It is shown that they perform well in a variety of situations andprovide sensible empirical results.
Book Synopsis Linear Models and Time-Series Analysis by : Marc S. Paolella
Download or read book Linear Models and Time-Series Analysis written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-10-10 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. Covers traditional time series analysis with new guidelines Provides access to cutting edge topics that are at the forefront of financial econometrics and industry Includes latest developments and topics such as financial returns data, notably also in a multivariate context Written by a leading expert in time series analysis Extensively classroom tested Includes a tutorial on SAS Supplemented with a companion website containing numerous Matlab programs Solutions to most exercises are provided in the book Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH is suitable for advanced masters students in statistics and quantitative finance, as well as doctoral students in economics and finance. It is also useful for quantitative financial practitioners in large financial institutions and smaller finance outlets.
Book Synopsis Emerging Markets by : Greg N. Gregoriou
Download or read book Emerging Markets written by Greg N. Gregoriou and published by CRC Press. This book was released on 2009-06-26 with total page 870 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although emerging market economies consist of 50% of the global population, they are relatively unknown. Filling this knowledge gap, Emerging Markets: Performance, Analysis and Innovation compiles the latest research by noteworthy academics and money managers from around the world. With a focus on both traditional emerging markets and new areas, su
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 2011-11-21 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.
Book Synopsis Modelling Systemic Risk in Financial Markets by : Andrea Ugolini
Download or read book Modelling Systemic Risk in Financial Markets written by Andrea Ugolini and published by Ed. Universidad de Cantabria. This book was released on 2017-04-26 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation provides a study on systemic risk in financial markets; it is laid out as follows. Chapter 1 provides a survey of the quantitative measure of systemic risk in the economics and finance literature. In Chapter 2 examine, using conditional VaR (CoVaR), the systemic risk generated by major Spanish financial institutions in the recent global financial crisis and the European sovereign debt crisis as a systemic risk measure. CoVaR was quantified using quantile regression, multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) and copula approaches. We also describe a novel copula-based approach to computing the CoVaR value, given that copula are flexible modellers of joint distribution and are particularly useful for characterizing the tail behaviour that provides such crucial information for the CoVaR.
Book Synopsis Handbook of Computational Finance by : Jin-Chuan Duan
Download or read book Handbook of Computational Finance written by Jin-Chuan Duan and published by Springer Science & Business Media. This book was released on 2011-10-25 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.
Book Synopsis Structural Changes and their Econometric Modeling by : Vladik Kreinovich
Download or read book Structural Changes and their Econometric Modeling written by Vladik Kreinovich and published by Springer. This book was released on 2018-11-24 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on structural changes and economic modeling. It presents papers describing how to model structural changes, as well as those introducing improvements to the existing before-structural-changes models, making it easier to later on combine these models with techniques describing structural changes. The book also includes related theoretical developments and practical applications of the resulting techniques to economic problems. Most traditional mathematical models of economic processes describe how the corresponding quantities change with time. However, in addition to such relatively smooth numerical changes, economical phenomena often undergo more drastic structural change. Describing such structural changes is not easy, but it is vital if we want to have a more adequate description of economic phenomena – and thus, more accurate and more reliable predictions and a better understanding on how best to influence the economic situation.
