High-Frequency Volatility Estimation and the Relative Importance of Market Microstructure Variables

63 Pages Posted: 26 Sep 2015 Last revised: 27 May 2018

Yifan Li

Lancaster University - Department of Accounting and Finance

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Sandra Nolte (Lechner)

Lancaster University Management School

Date Written: February 24, 2017

Abstract

In this paper we examine the relative importance of trading volume, bid-ask spread, order flow, order imbalance, total quote depth, quote depth difference and trading intensity for high-frequency volatility estimation. By using a best subset regression approach, we fi nd that contemporaneous trading intensity and order flow contains the most important information about volatility estimation in general, but the rankings of the importance of the market microstructure (MMS) variables vary between securities. Using a Lognormal Log-Autoregressive Conditional Duration (LL-ACD) model, we show that the inclusion of MMS covariates signi ffcantly improves the goodness-of- fit of the model. Furthermore, we show that the inclusion of MMS covariates in the LL-ACD model leads to substantial improvements in the quality of volatility estimates, both on a daily and an intraday level.

Keywords: High-Frequency Volatility Estimation, Market Microstructure Variables, ACD Model, Best Subset Regression.

JEL Classification: C58, C52, C41, G12

Suggested Citation

Li, Yifan and Nolte, Ingmar and Nolte (Lechner), Sandra, High-Frequency Volatility Estimation and the Relative Importance of Market Microstructure Variables (February 24, 2017). Available at SSRN: https://ssrn.com/abstract=2665639 or http://dx.doi.org/10.2139/ssrn.2665639

Yifan Li

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom

Ingmar Nolte (Contact Author)

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Sandra Nolte (Lechner)

Lancaster University Management School ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

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