The contribution of jump signs and activity to forecasting stock price volatility

Bu, Ruijun ORCID: 0000-0002-3947-3038, Hizmeri, Rodrigo, Izzeldin, Marwan, Murphy, Anthony and Tsionas, Mike (2023) The contribution of jump signs and activity to forecasting stock price volatility. Journal of Empirical Finance, 70. pp. 144-164.

PDF
Draft_Final_Revised.pdf - Author Accepted Manuscript
Download (915kB) | Preview

Official URL: http://dx.doi.org/10.1016/j.jempfin.2022.12.001

Abstract

We propose a novel approach to decompose realized jump measures by type of activity (finite/infinite) and sign, and also provide noise-robust versions of the ABD jump test (Andersen et al., 2007b) and realized semivariance measures. We find that infinite (finite) jumps improve the forecasts at shorter (longer) horizons; but the contribution of signed jumps is limited. As expected, noise-robust measures deliver substantial forecast improvements at higher sampling frequencies, although standard volatility measures at the 300-s frequency generate the smallest MSPEs. Since no single model dominates across sampling frequency and forecasting horizon, we show that model averaged volatility forecasts – using time-varying weights and models from the model confidence set – generally outperform forecasts from both the benchmark and single best extended HAR model. Finally, forecasts using volatility and jump measures based on transaction sampling are inferior to the forecasts from clock-based sampling.

Item Type:	Article
Additional Information:	Source info: Journal of Empirical Finance, Forthcoming
Uncontrolled Keywords:	Business Sampling, Calendar Sampling, Jump Measures, Market Microstructure Noise, Model Averaging, Volatility Forecasting
Depositing User:	Symplectic Admin
Date Deposited:	07 Dec 2022 11:24
Last Modified:	28 Mar 2023 10:12
DOI:	10.1016/j.jempfin.2022.12.001
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3166507