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

Nikolay Gospodinov, Raymond Kan and Cesare Robotti

Econometric Reviews, 2018, vol. 37, issue 7, 695-718

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.

Date: 2018
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Working Paper: Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:37:y:2018:i:7:p:695-718

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DOI: 10.1080/07474938.2016.1165945

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