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Book Estimating Tail Dependence and Testing for Contagion Using Tail Indices

Download or read book Estimating Tail Dependence and Testing for Contagion Using Tail Indices written by Carmela Quintos and published by . This book was released on 2001 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper introduces a measure of extremal correlation. Our measure of tail dependence does not require parametric specification of a copula (or dependence) function. It relies instead on the fact that moments of co-exceedances can be written in terms of tail indices. This simplifies the calculation of extremal dependence considerably for the tail index requires only an assumption on the asymptotic form of the tails rather than the full distribution. Furthermore, the distributional properties of extreme value estimators for the tail index are well known. This enables us to derive the distributional properties of our extremal correlation estimator, unlike the methods that rely on the specification of a copula where a closed form solution for the tail dependence parameter does not exist. Our estimator is Normally distributed so inference is straightforward. We illustrate the use of our statistic to testing for contagion in Asian markets and find a lack of a significant change in the extremal correlation before and after the crisis.

Book Nonparametric Estimation of Tail Dependence

Download or read book Nonparametric Estimation of Tail Dependence written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Tail Index and Quantile Estimation with Very High Frequency Data

Download or read book Tail Index and Quantile Estimation with Very High Frequency Data written by Casper G. de Vries and published by . This book was released on 1996 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Tail Index Estimation

Download or read book Tail Index Estimation written by Jón Daníelsson and published by . This book was released on 2019 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The selection of upper order statistics in tail estimation is notoriously difficult. Methods that are based on asymptotic arguments, like minimizing the asymptotic MSE, do not perform well in finite samples. Here, we advance a data-driven method that minimizes the maximum distance between the fitted Pareto type tail and the observed quantile. To analyze the finite sample properties of the metric, we perform rigorous simulation studies. In most cases, the finite sample-based methods perform best. To demonstrate the economic relevance of choosing the proper methodology, we use daily equity return data from the CRSP database and find economically relevant variation between the tail index estimates"--Abstract.

Book Tail Dependence of Factor Models

Download or read book Tail Dependence of Factor Models written by Yannick Malevergne and published by . This book was released on 2002 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using the framework of factor models, we establish the general expression of the coefficient of tail dependence between the market and a stock (i.e., the probability that the stock incurs a large loss, assuming that the market has also undergone a large loss) as a function of the parameters of the underlying factor model and of the tail parameters of the distributions of the factor and of the idiosyncratic noise of each stock. Our formula holds for arbitrary marginal distributions and in addition does not require any parameterization of the multivariate distributions of the market and stocks. The determination of the extreme parameter, which is not accessible by a direct statistical inference, is made possible by the measurement of parameters whose estimation involves a significant part of the data with sufficient statistics. Our empirical tests find a good agreement between the calibration of the tail dependence coefficient and the realized large losses over the period from 1962 to 2000. Nevertheless, a bias is detected which suggests the presence of an outlier in the form of the crash of October 1987.

Book Detecting Structural Differences in Tail Dependence of Financial Time Series

Download or read book Detecting Structural Differences in Tail Dependence of Financial Time Series written by Carsten Bormann and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: An accurate assessment of tail inequalities and tail asymmetries of financial returns is key for risk management and portfolio allocation. We propose a new test procedure for detecting the full extent of such structural differences in the dependence of bivariate extreme returns. We decompose the testing problem into piecewise multiple comparisons of Cramér-von Mises distances of tail copulas. In this way, tail regions that cause differences in extreme dependence can be located and consequently be targeted by financial strategies. We derive the asymptotic properties of the test and provide a bootstrap approximation for finite samples. Moreover, we account for the multiplicity of the piecewise tail copula comparisons by adjusting individual p-values according to multiple testing techniques. Monte Carlo simulations demonstrate the test's superior finite-sample properties for common financial tail risk models, both in the i.i.d. and the sequentially dependent case. During the last 90 years in US stock markets, our test detects up to 20% more tail asymmetries than competing tests. This can be attributed to the presence of non-standard tail dependence structures. We also find evidence for diminishing tail asymmetries during every major financial crisis - except for the 2007-09 crisis - reflecting a risk-return trade-off for extreme returns.

Book Tail Dependence Measure for Examining Financial Extreme Co Movements

Download or read book Tail Dependence Measure for Examining Financial Extreme Co Movements written by Alexandru Vali Asimit and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and forecasting extreme co-movements in financial market is important for conducting stress test in risk management. Asymptotic independence and asymptotic dependence behave drastically different in modeling such co-movements. For example, the impact of extreme events is usually overestimated whenever asymptotic dependence is wrongly assumed. On the other hand, the impact is seriously underestimated whenever the data is misspecified as asymptotic independent. Therefore, distinguishing between asymptotic independence/dependence scenarios is very informative for any decision-making and especially in risk management. We investigate the properties of the limiting conditional Kendall's tau which can be used to detect the presence of asymptotic independence/dependence. We also propose nonparametric estimation for this new measure and derive its asymptotic limit. A simulation study shows good performances of the new measure and its combination with the coefficient of tail dependence proposed by Ledford and Tawn (1996, 1997). Finally, applications to financial and insurance data are provided.

Book Tail Densities of Copulas and Their Applications to Extremal Dependence Analysis of Vines

Download or read book Tail Densities of Copulas and Their Applications to Extremal Dependence Analysis of Vines written by Peiling Wu and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 2. We derive tractable formulas of tail densities of Archimedean and t copulas explicitly.

Book A Guide to IMF Stress Testing

Download or read book A Guide to IMF Stress Testing written by Ms.Li L Ong and published by International Monetary Fund. This book was released on 2014-12-23 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: The IMF has had extensive involvement in the stress testing of financial systems in its member countries. This book presents the methods and models that have been developed by IMF staff over the years and that can be applied to the gamut of financial systems. An added resource for readers is the companion CD-Rom, which makes available the toolkit with some of the models presented in the book (also located at elibrary.imf.org/page/stress-test-toolkit).

Book On Testing the Adequacy of Stable Processes Under Conditional Heteroscedasticity

Download or read book On Testing the Adequacy of Stable Processes Under Conditional Heteroscedasticity written by Rohit Deo and published by . This book was released on 2008 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider a recently proposed method of estimating the tail index and testing thegoodness-of-fit of dependent stable processes. Through Monte Carlo simulations, weevaluate the ability of the procedure to distinguish between stable and non-stable processesin the presence of non-linear dependence and to estimate the tail index of the distribution.We then apply the test to black market East European exchange rates, whose distributionaland tail behaviour has been analysed previously in the literature. After adjusting forseasonality, we conclude, unlike the earlier analysis, that a stable process cannot be rejectedas a model for some of the currencies. Estimates of the tail index for these currencies arealso obtained.

Book IMF Staff Papers  Volume 51  No  2

Download or read book IMF Staff Papers Volume 51 No 2 written by International Monetary Fund. Research Dept. and published by International Monetary Fund. This book was released on 2004-07-29 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second issue for 2004 contains 8 new papers, including notable contributions from: Nancy Brune, Geoffrey Garrett, and Bruce Kogut on the global spread of privatization; and Mark P. Taylor and Elena T. Branson on asymmetric arbitrage and default premiums in the U.S. and Russian markets. Other papers in the issue look at German wage structures, contagion in equity markets, export orientation and productivity in Sub-Saharan Africa, the role of higher vs. basic education in economic development, and issues related to capital account liberalization.

Book Nonparametric Statistical Methods and Related Topics

Download or read book Nonparametric Statistical Methods and Related Topics written by Francisco J. Samaniego and published by World Scientific. This book was released on 2011-09-16 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of 22 research papers by leading researchers in Probability and Statistics. Many of the papers are focused on themes that Professor Bhattacharya has published on research. Topics of special interest include nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. This volume presents state-of-the-art research in statistical theory, with an emphasis on nonparametric inference, linear model theory, time series analysis and asymptotic theory. It will serve as a valuable reference to the statistics research community as well as to practitioners who utilize methodology in these areas of emphasis.

Book Introduction to Bayesian Estimation and Copula Models of Dependence

Download or read book Introduction to Bayesian Estimation and Copula Models of Dependence written by Arkady Shemyakin and published by John Wiley & Sons. This book was released on 2017-02-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.

Book Statistical Modeling Using Local Gaussian Approximation

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 Heavy Tails and Copulas

Download or read book Heavy Tails and Copulas written by Rustam Ibragimov and published by . This book was released on 2017 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers a unified approach to the study of crises, large fluctuations, dependence and contagion effects in economics and finance. It covers important topics in statistical modeling and estimation, which combine the notions of copulas and heavy tails — two particularly valuable tools of today's research in economics, finance, econometrics and other fields — in order to provide a new way of thinking about such vital problems as diversification of risk and propagation of crises through financial markets due to contagion phenomena, among others. The aim is to arm today's economists with a toolbox suited for analyzing multivariate data with many outliers and with arbitrary dependence patterns. The methods and topics discussed and used in the book include, in particular, majorization theory, heavy-tailed distributions and copula functions — all applied to study robustness of economic, financial and statistical models, and estimation methods to heavy tails and dependence."--Publisher's website.

Book The Risks of Financial Institutions

Download or read book The Risks of Financial Institutions written by Mark Carey and published by University of Chicago Press. This book was released on 2007-11-01 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: Until about twenty years ago, the consensus view on the cause of financial-system distress was fairly simple: a run on one bank could easily turn to a panic involving runs on all banks, destroying some and disrupting the financial system. Since then, however, a series of events—such as emerging-market debt crises, bond-market meltdowns, and the Long-Term Capital Management episode—has forced a rethinking of the risks facing financial institutions and the tools available to measure and manage these risks. The Risks of Financial Institutions examines the various risks affecting financial institutions and explores a variety of methods to help institutions and regulators more accurately measure and forecast risk. The contributors--from academic institutions, regulatory organizations, and banking--bring a wide range of perspectives and experience to the issue. The result is a volume that points a way forward to greater financial stability and better risk management of financial institutions.