Bias-corrected realized variance

Jin-Huei Yeh and Jying-Nan Wang

Econometric Reviews, 2019, vol. 38, issue 2, 170-192

Abstract: We propose a novel “bias-corrected realized variance” (BCRV) estimator based upon the appropriate re-weighting of two realized variances calculated at different sampling frequencies. Our bias-correction methodology is found to be extremely accurate, with the finite sample variance being significantly minimized. In our Monte Carlo experiments and a finite sample MSE comparison of alternative estimators, the performance of our straightforward BCRV estimator is shown to be comparable to other widely-used integrated variance estimators. Given its simplicity, our BCRV estimator is likely to appeal to researchers and practitioners alike for the estimation of integrated variance.

Date: 2019
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DOI: 10.1080/07474938.2016.1222230

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