The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility

44 Pages Posted: 1 May 2019 Last revised: 8 Jul 2021

See all articles by Ruijun Bu

Ruijun Bu

University of Liverpool - Management School (ULMS)

Rodrigo Hizmeri

University of Liverpool - Management School (ULMS)

Marwan Izzeldin

Lancaster University Management School

Anthony Murphy

Federal Reserve Banks - Federal Reserve Bank of Dallas

Mike Tsionas

Lancaster University

Multiple version iconThere are 2 versions of this paper

Date Written: June 30, 2021

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-second 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.

Keywords: Volatility Forecasting, Jump Measures, Business Sampling, Calendar Sampling, Market Microstructure Noise, Model Averaging

JEL Classification: C51, C53, C58, G15, G17

Suggested Citation

Bu, Ruijun and Hizmeri, Rodrigo and Izzeldin, Marwan and Murphy, Anthony and Tsionas, Efthymios G., The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility (June 30, 2021). Available at SSRN: https://ssrn.com/abstract=3361972 or http://dx.doi.org/10.2139/ssrn.3361972

Ruijun Bu

University of Liverpool - Management School (ULMS) ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

Rodrigo Hizmeri (Contact Author)

University of Liverpool - Management School (ULMS) ( email )

Chatham St.
Liverpool, L69 7ZH
United Kingdom

HOME PAGE: http://www.rodrigohizmeri.com

Marwan Izzeldin

Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom
01524 594674 (Phone)

HOME PAGE: http://www.lums.lancs.ac.uk/profiles/marwan-izzeldin/

Anthony Murphy

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

Efthymios G. Tsionas

Lancaster University ( email )

Lancaster LA1 4YX
United Kingdom

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