 The signal and the noise volatilitiesSelma Chaker Research in International Business and Finance, 2019, vol. 50, issue C, 79-105 Abstract: This paper explores the volatility forecasting implications of a model in which the high-frequency market microstructure noise is related to the true underlying volatility. The contribution of this paper is to propose a theoretical framework under which the realized variance, based on the highest frequency to compute returns, may improve volatility forecasting if the noise variance is an affine function of the fundamental volatility. In this new setting, we extend the work of Andersen et al. (2011) and quantify the predictive ability of several measures of integrated variance. We find that the traditional realized variance based on the highest frequency returns outperforms alternative realized measures. We also evaluate the usefulness of our approach by conducting an empirical application and show several improvements resulting from the assumption of time-varying noise variance. Keywords: Realized volatility; Volatility forecasting; Heteroscedastic noise; Eigenfunction stochastic volatility models (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:50:y:2019:i:c:p:79-105 DOI: 10.1016/j.ribaf.2019.04.008 Access Statistics for this article Research in International Business and Finance is currently edited by T. Lagoarde Segot More articles in Research in International Business and Finance from Elsevier |
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