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.
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Marc S. Paolella is Professor of Empirical Finance at the University of Zurich, Switzerland. He is also the Editor of Econometrics and an Associate Editor of the Royal Statistical Society Journal Series. With almost 20 years of teaching experience, he is a frequent collaborator to journals and a member of many editorial boards and societies.
Linear Models and Time-Series Analysis
Regression, ANOVA, ARMA and GARCH
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 chapters on regression, ANOVA, and ARMA cover much standard ground, with the emphasis on clear, detailed derivations of all major results, as well as development of MATLAB codes and use of simulations to show the theory. Important topics such as (small-sample distribution theory associated with) unit root tests and time-varying parameter regression models, and order selection in ARMAX models, are also discussed in detail.
Several chapters are dedicated to very modern methods in empirical finance, risk management, and portfolio optimization. In particular, various methods for non-Gaussian, non-elliptic, large-scale portfolio optimization are developed, along with MATLAB codes, and the incorporation of transaction costs. The use of such models is shown, with real data, to highly outperform common models such as Markowitz, Gaussian CCC, and DCC.
Further highlights include:
This book 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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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