Heavy tails and copulas : topics in dependence modelling in economics and finance / Rustam Ibragimov and Artem Prokhorov.
Material type:
- 9789814689793 (hardcover)
- 330.015195 23 Ib14
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|
Books | ISI Library, Kolkata | 330.015195 Ib14 (Browse shelf(Opens below)) | Available | 138359 |
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330.015195 H878 Modern econometric analysis | 330.015195 H967 Designing economic mechanisms | 330.015195 H996 Modelling seasonality | 330.015195 Ib14 Heavy tails and copulas : | 330.015195 Ic16 Markets, games, and organizations | 330.015195 In61 Nonlinear statistical modeling | 330.015195 J82 Econometrics |
Includes bibliographical references and index.
1.Introduction and Overview --
1.1.Crises, contagion and other features of modern economic and financial data --
1.2.Econometric tools for modern financial and economic data --
1.2.1.Multivariate distributions and copulas --
1.2.2.Heavy tailed stable and power law distributions --
1.3.Robustness to heavy tails and to copula misspecification --
1.3.1.Robustness of models to heavy tails --
1.3.2.Robustness of methods to heavy tails and to copula misspecification --
1.4.Plan for the book --
2.Portfolio Diversification under Independent Fat Tailed Risks --
2.1.Introduction --
2.2.Notation and classes of distributions --
2.3.Value-at-Risk (VaR): Definition and main properties --
2.4.Majorization, diversification and (non-)coherency of VaR --
2.4.1.Majorization of random vectors and diversification of portfolio riskiness --
2.4.2.Subadditivity of VaR --
2.4.3.Extensions to heterogeneity and skewness --
2.5.Concluding remarks Note continued: 5.1.Introduction --
5.2.Copula estimation --
5.2.1.Parametric models: MLE and IFM --
5.2.2.Nonparametric models: Empirical and Bernstein copulas --
5.2.3.Semiparametric estimation: Copulas vs marginals --
5.3.Copula-based estimation of time series models --
5.3.1.Parametric and semiparametric estimation of Markov processes --
5.3.2.Nonparametric copula inference for time series --
5.3.3.Dependence properties of copula-based time series --
5.4.Improved and robust parametric estimators --
5.4.1.QMLE and improved QMLE --
5.4.2.Full MLE as GMM --
5.4.3.Efficiency and redundancy of copulas --
5.4.4.Validity and robustness of copulas --
5.4.5.Efficiency and redundancy under misspecified but robust copulas --
5.5.Robustness and efficiency of nonparametric copulas --
5.5.1.Efficient semiparametric estimation of parameters in marginals --
5.5.2.Bayesian efficiency and consistency --
5.6.Robustness of estimators to heavy tails --
5.6.1.Trimming Note continued: 5.7.Concluding remarks --
5.8.Appendix: Proofs --
6.Copula Tests Using Information Matrix --
6.1.Introduction --
6.2.Tests of copula robustness --
6.2.1.Test of overidentifying restrictions --
6.2.2.Two step test --
6.3.Tests of copula correctness --
6.3.1.Copulas and information matrix equivalence --
6.3.2.Information matrix test --
6.3.3.Generalized information matrix tests --
6.3.4.Power study --
6.4.Concluding remarks --
6.5.Appendix: Proofs --
7.Summary and Conclusion --
7.1.Summary --
7.2.Future research.
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. Readership: Advanced students in economics, finance, financial econometrics; risk managers; actuaries; finance professionals; business analysts; banking regulators; and for those interested in the functioning of modern financial markets and statistical models of financial contagion.
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