Volatility Measurement with Pockets of Extreme Return Persistence

48 Pages Posted: 4 Nov 2020

See all articles by Torben G. Andersen

Torben G. Andersen

Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); Aarhus University - CREATES

Yingying Li

Hong Kong University of Science & Technology (HKUST), Dept of ISOM and Dept of Finance; Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management; Hong Kong University of Science & Technology (HKUST) - Department of Finance

Viktor Todorov

Northwestern University

Bo Zhou

Durham University Business School

Date Written: September 17, 2020

Abstract

Increasing evidence points towards the episodic emergence of pockets with extreme return persistence. This notion refers to intraday periods of non-trivial duration, for which stock returns are highly positively autocorrelated. Such episodes include, but are not limited to, gradual jumps and prolonged bursts in the drift component. In this paper, we develop a family of integrated volatility estimators, labeled differenced-return volatility (DV) estimators, which provide robustness to these types of Ito semimartingale violations. Specifically, we show that by using differences in consecutive high-frequency returns, our DV estimators can reduce the non-trivial bias, that all commonly-used estimators exhibit during such periods of apparent short-term intraday return predictability. A Monte Carlo study demonstrates the reliability of the newly developed volatility estimators in finite samples. In our empirical volatility forecast application to S&P 500 index futures and individual equities, our DV-based Heterogeneous Autoregressive (HAR) model performs well relative to existing procedures according to standard out-of-sample MSE and QLIKE criteria.

Keywords: extreme return persistence, high-frequency data, integrated volatility estimation, market microstructure noise, volatility forecasting.

JEL Classification: C12, C53, G10, G17

Suggested Citation

Andersen, Torben G. and Li, Yingying and Todorov, Viktor and Zhou, Bo, Volatility Measurement with Pockets of Extreme Return Persistence (September 17, 2020). Available at SSRN: https://ssrn.com/abstract=3694403 or http://dx.doi.org/10.2139/ssrn.3694403

Torben G. Andersen

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Yingying Li

Hong Kong University of Science & Technology (HKUST), Dept of ISOM and Dept of Finance ( email )

Clear Water Bay, Kowloon
Hong Kong

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

Hong Kong University of Science & Technology (HKUST) - Department of Finance ( email )

Clear Water Bay, Kowloon
Hong Kong

Viktor Todorov

Northwestern University ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Bo Zhou (Contact Author)

Durham University Business School ( email )

Mill Hill Lane
Durham, DH1 3LB
United Kingdom

HOME PAGE: http://https://sites.google.com/view/bo-zhou

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