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Portfolio risk analysis / Gregory Connor, Lisa R. Goldberg, Robert A. Korajczyk.

By: Contributor(s): Material type: TextTextPublication details: Princeton : Princeton University Press, ©2010.Description: 1 online resource (xxi, 354 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781400835294
  • 1400835291
  • 0691128286
  • 9780691128283
Subject(s): Genre/Form: Additional physical formats: Print version:: Portfolio risk analysis.DDC classification:
  • 332.6 22
LOC classification:
  • HG4529.5 .C657 2010eb
Other classification:
  • QK 810
Online resources:
Contents:
Measures of risk and return -- Unstructured covariance matrices -- Industry and country risk -- Statistical factor analysis -- The macroeconomy and portfolio risk -- Security characteristics and pervasive risk factors -- Measuring and hedging foreign exchange risk -- Integrated risk models -- Dynamic volatilities and correlations -- Portfolio return distributions -- Credit risk -- Transaction costs and liquidity risk -- Alternative asset classes -- Performance measurement.
Summary: 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. --From publisher's description.
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Includes bibliographical references and index.

Measures of risk and return -- Unstructured covariance matrices -- Industry and country risk -- Statistical factor analysis -- The macroeconomy and portfolio risk -- Security characteristics and pervasive risk factors -- Measuring and hedging foreign exchange risk -- Integrated risk models -- Dynamic volatilities and correlations -- Portfolio return distributions -- Credit risk -- Transaction costs and liquidity risk -- Alternative asset classes -- Performance measurement.

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. --From publisher's description.

Print version record.

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