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Testing the Lag Structure of Assets’ Realized Volatility Dynamics

Department of Economics, University of St. Gallen, Bodanstrasse 6, 9000 St.Gallen, Switzerland

Special Issues: Financial Big Data Technology and Its Applications

A (conservative) test is applied to investigate the optimal lag structure for modelingrealized volatility dynamics. The testing procedure relies on the recent theoretical results that showthe ability of the adaptive least absolute shrinkage and selection operator (adaptive lasso) to combinee cient parameter estimation, variable selection, and valid inference for time series processes. In anapplication to several constituents of the S&P 500 index it is shown that (i) the optimal significantlag structure is time-varying and subject to drastic regime shifts that seem to happen across assetssimultaneously; (ii) in many cases the relevant information for prediction is included in the first 22lags, corroborating previous results concerning the accuracy and the diffculty of outperforming outof-sample the heterogeneous autoregressive (HAR) model; and (iii) some common features of theoptimal lag structure can be identified across assets belonging to the same market segment or showinga similar beta with respect to the market index.
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Keywords realized volatility; adaptive lasso; HAR model; test for false positives; lag structure

Citation: Francesco Audrino, Lorenzo Camponovo, Constantin Roth. Testing the Lag Structure of Assets’ Realized Volatility Dynamics. Quantitative Finance and Economics, 2017, 1(4): 363-387. doi: 10.3934/QFE.2017.4.363


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This article has been cited by

  • 1. Francesco Audrino, Chen Huang, Ostap Okhrin, Flexible HAR model for realized volatility, Studies in Nonlinear Dynamics & Econometrics, 2018, 0, 0, 10.1515/snde-2017-0080
  • 2. Ines Wilms, Jeroen Rombouts, Christophe Croux, Multivariate volatility forecasts for stock market indices, International Journal of Forecasting, 2020, 10.1016/j.ijforecast.2020.06.012

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Copyright Info: 2017, Francesco Audrino, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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