 Lassoing the HAR model: A Model Selection Perspective on Realized Volatility DynamicsFrancesco Audrino and Simon Knaus () No 1224, Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Abstract: Realized volatility computed from high-frequency data is an important measure for many applications in finance. However, its dynamics are not well understood to date. Recent notable advances that perform well include the heterogeneous autoregressive (HAR) model which is economically interpretable and but still easy to estimate. It also features good out-of-sample performance and has been extremely well received by the research community. We present a data driven approach based on the absolute shrinkage and selection operator (lasso) which should identify the aforementioned model. We prove that the lasso indeed recovers the HAR model asymptotically if it is the true model, and we present Monte Carlo evidence in finite sample. The HAR model is not recovered by the lasso on real data. This, together with an empirical out-of-sample analysis that shows equal performance of the HAR model and the lasso approach, leads to the conclusion that the HAR model may not be the true model but it captures a linear footprint of the true volatility dynamics. Keywords: Realized Volatility; Heterogeneous Autoregressive Model; Lasso; Model Selection (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:usg:econwp:2012:24 Access Statistics for this paper More papers in Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Contact information at EDIRC. |
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