Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models’ econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective.
Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts.
This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.
About the Author
Gregory Connor is professor of finance at the National University of Ireland, Maynooth, and senior research associate at the London School of Economics and Political Science. Lisa R. Goldberg is executive director of analytic initiatives at MSCI Barra and adjunct professor of statistics at the University of California, Berkeley. Robert A. Korajczyk is professor of finance at Northwestern University.
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