More Accurate Volatility Estimation and Forecasts Using Price Durations

62 Pages Posted: 11 Jan 2016 Last revised: 20 Mar 2018

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Stephen J. Taylor

Lancaster University - Department of Accounting and Finance

Xiaolu Zhao

Dongbei University of Finance and Economics

Date Written: March 16, 2018

Abstract

We investigate price duration variance estimators that have long been ignored in the literature. We show i) how price duration estimators can be used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and ii) how they are affected by a) important market microstructure noise effects such as the bid/ask spread, irregularly spaced observations in discrete time and discrete price levels, as well as b) price jumps. We develop i) simple-to-construct non-parametric estimators and ii) parametric price duration estimators using autoregressive conditional duration specifications. We provide guidance how these estimators can best be implemented in practice by optimally selecting a threshold parameter that defines a price duration event, or by averaging over a range of non-parametric duration estimators. We provide simulation and forecasting evidence that price duration estimators can extract relevant information from high-frequency data better and produce more accurate forecasts than competing realized volatility and option-implied variance estimators, when considered in isolation or as part of a forecasting combination setting.

Keywords: Volatility estimation; Stochastic sampling; Price durations; High-frequency prices; Market microstructure noise; Forecasting; DJIA stocks.

JEL Classification: C22, C41, C51, C52, C53, C14, C13

Suggested Citation

Nolte, Ingmar and Taylor, Stephen J. and Zhao, Xiaolu, More Accurate Volatility Estimation and Forecasts Using Price Durations (March 16, 2018). Available at SSRN: https://ssrn.com/abstract=2713322 or http://dx.doi.org/10.2139/ssrn.2713322

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Stephen J. Taylor

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom
+ 44 15 24 59 36 24 (Phone)
+ 44 15 24 84 73 21 (Fax)

HOME PAGE: http://www.lancs.ac.uk/staff/afasjt

Xiaolu Zhao (Contact Author)

Dongbei University of Finance and Economics ( email )

217 Jianshan St,
Shahekou
Dalian, Liaoning
China

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