|Appears in Collections:||Accounting and Finance Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Forecasting Realised Volatility: Does the LASSO approach outperform HAR?|
|Citation:||Ding Y, Kambouroudis D & McMillan D (2021) Forecasting Realised Volatility: Does the LASSO approach outperform HAR?. Journal of International Financial Markets, Institutions and Money, 74, Art. No.: 101386. https://doi.org/10.1016/j.intfin.2021.101386|
|Abstract:||The HAR model dominates current volatility forecasting. This model implies a restricted lag approach, with three parameters accounting for an AR(22) structure. This paper uses the Lasso method, which selects a parsimonious lag structure, while allowing both a flexible lag structure and lags greater than 22. In-sample results suggest that while significance is largely found among the first 22 lags, consistent with the HAR model, there is evidence that longer lags contain information, as Lasso models provide an improved fit. Out-of-sample forecasts for daily, weekly and monthly volatility, evaluated using MSE, QLIKE, MCS and VaR measures, suggest that the ordered Lasso model provides the preferred forecasts using an AR(100) at the daily level and an AR(22) for the weekly and monthly horizons. The results support the view that a more flexible lag structure is preferred over the HAR approach.|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Ding Y, Kambouroudis D & McMillan D (2021) Forecasting Realised Volatility: Does the LASSO approach outperform HAR? Journal of International Financial Markets, Institutions and Money, 74, Art. No.: 101386. https://doi.org/10.1016/j.intfin.2021.101386 © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
|lasso_final.pdf||Fulltext - Accepted Version||1.25 MB||Adobe PDF||Under Embargo until 2022-07-17 Request a copy|
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