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Generalized Method of Moments: Applications in Finance


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


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.

Suggested Citation

  • Jagannathan, Ravi & Skoulakis, Georgios & Wang, Zhenyu, 2002. "Generalized Method of Moments: Applications in Finance," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 470-481, October.
  • Handle: RePEc:bes:jnlbes:v:20:y:2002:i:4:p:470-81

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    Cited by:

    1. Dinh, Minh Thi Hong, 2018. "The relationship between volume imbalance and spread," Research in International Business and Finance, Elsevier, vol. 44(C), pages 76-87.
    2. Kola, Katlego & Kodongo, Odongo, 2017. "Macroeconomic risks and REITs returns: A comparative analysis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1228-1243.
    3. Alessandra Amendola & Giuseppe Storti, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers SFB649DP2009-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Shabir Ahmad Hakim & Zarinah Hamid & Ahamed Kameel Mydin Meera, 2016. "Capital Asset Pricing Model and Pricing of Islamic Financial Instruments نموذج تسعير الأصول الرأسمالية وتسعير الأدوات المالية الإسلامية," Journal of King Abdulaziz University: Islamic Economics, King Abdulaziz University, Islamic Economics Institute., vol. 29(1), pages 21-39, January.
    5. Gur Huberman & Zhenyu Wang, 2005. "Arbitrage pricing theory," Staff Reports 216, Federal Reserve Bank of New York.
    6. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    7. 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.
    8. Nicky Grant, 2013. "Identification Robust Inference with Singular Variance," The School of Economics Discussion Paper Series 1315, Economics, The University of Manchester.
    9. 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.
    10. 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.
    11. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    12. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
    13. Ali, Heba, 2019. "Does downside risk matter more in asset pricing? Evidence from China," Emerging Markets Review, Elsevier, vol. 39(C), pages 154-174.

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