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Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models

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  • Nikolay Gospodinov
  • Raymond Kan
  • Cesare Robotti

Abstract

This article derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously-updated GMM estimators in models that may not satisfy the fundamental asset-pricing restrictions in population. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. While the results for the maximum likelihood estimator are only applicable to linear asset-pricing models, the asymptotic distribution of the continuously-updated GMM estimator is derived for general, possibly nonlinear, models. The large corrections in the asymptotic variances, that arise from explicitly incorporating model misspecification in the analysis, are illustrated using simulations and an empirical application.

Suggested Citation

  • Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:7:p:695-718
    DOI: 10.1080/07474938.2016.1165945
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    Cited by:

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    2. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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