Bias-corrected realized variance

Jin Huei Yeh, Jying Nan Wang

研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)

摘要

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.

原文???core.languages.en_GB???
頁(從 - 到)170-192
頁數23
期刊Econometric Reviews
38
發行號2
DOIs
出版狀態已出版 - 7 2月 2019

指紋

深入研究「Bias-corrected realized variance」主題。共同形成了獨特的指紋。

引用此