Testing the Lag Structure of Assets' Realized Volatility Dynamics

Francesco Audrino; Lorenzo Camponovo; Constantin Roth; Francesco Audrino; Lorenzo Camponovo; Constantin Roth

doi:10.3934/QFE.2017.4.363

Quantitative Finance and Economics

2017, Volume 1, Issue 4: 363-387. doi: 10.3934/QFE.2017.4.363

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Research article Special Issues

Testing the Lag Structure of Assets' Realized Volatility Dynamics

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

Received: 07 September 2017 Accepted: 19 October 2017 Published: 13 December 2017

A (conservative) test is applied to investigate the optimal lag structure for modeling realized volatility dynamics. The testing procedure relies on the recent theoretical results that show the ability of the adaptive least absolute shrinkage and selection operator (adaptive lasso) to combine e cient parameter estimation, variable selection, and valid inference for time series processes. In an application to several constituents of the S & P 500 index it is shown that (ⅰ) the optimal significant lag structure is time-varying and subject to drastic regime shifts that seem to happen across assets simultaneously; (ⅱ) in many cases the relevant information for prediction is included in the first 22 lags, corroborating previous results concerning the accuracy and the diffculty of outperforming outof-sample the heterogeneous autoregressive (HAR) model; and (ⅲ) some common features of the optimal lag structure can be identified across assets belonging to the same market segment or showing a similar beta with respect to the market index.
- 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[J]. Quantitative Finance and Economics, 2017, 1(4): 363-387. doi: 10.3934/QFE.2017.4.363

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Abstract

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

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