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Generalized Method of Moments: Applications in Finance

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  • Jagannathan, Ravi
  • Skoulakis, Georgios
  • Wang, Zhenyu

Abstract

We provide a brief overview of applications of generalized method of moments in finance. The models examined in the empirical finance literature, especially in the asset pricing area, often imply moment conditions that can be used in a straight forward way to estimate the model parameters without making strong assumptions regarding the stochastic properties of variables observed by the econometrician. Typically the number of moment conditions available to the econometrician would exceed the number of model parameters. This gives rise to overidentifying restrictions that can be used to test the validity of the model specifications. These advantages have led to the widespread use of the generalized method of moments in the empirical finance literature.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 20 (2002)
Issue (Month): 4 (October)
Pages: 470-81

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Handle: RePEc:bes:jnlbes:v:20:y:2002:i:4:p:470-81

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Cited by:
  1. Nicky Grant, 2013. "Identification Robust Inference with Singular Variance," The School of Economics Discussion Paper Series 1315, Economics, The University of Manchester.
  2. Christian Hawkesby & Ian W Marsh & Ibrahim Stevens, 2005. "Comovements in the prices of securities issued by large complex financial institutions," Bank of England working papers 256, Bank of England.
  3. Gur Huberman & Zhenyu Wang, 2005. "Arbitrage pricing theory," Staff Reports 216, Federal Reserve Bank of New York.
  4. Abel, Ernest & Fletcher, Jonathan, 2004. "An empirical examination of UK emerging market unit trust performance," Emerging Markets Review, Elsevier, vol. 5(4), pages 389-408, December.
  5. Frank Kleibergen & Richard Paap, 2003. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Tinbergen Institute Discussion Papers 03-003/4, Tinbergen Institute.
  6. Alessandra Amendola & Giuseppe Storti, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers SFB649DP2009-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  7. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
  8. Fletcher, Jonathan & Kihanda, Joseph, 2005. "An examination of alternative CAPM-based models in UK stock returns," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 2995-3014, December.

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