Title

Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach

Publication Type

Journal Article

Publication Date

12-2015

Abstract

We propose to compute the Intraday Value-at-Risk (IVaR) for stocks using real-time transaction data. Tick-by-tick data filtered by price duration are modeled using a two-state asymmetric autoregressive conditional duration (AACD) model, and the IVaR is calculated using Monte Carlo simulation based on the estimated AACD model. Backtesting results for the New York Stock Exchange (NYSE) show that the IVaR calculated using the AACD method outperforms those using the Dionne et al. (2009) and Giot (2005) methods. (C) 2015 Elsevier B.V. All rights reserved.

Keywords

High-frequency transaction data, Market microstructure noise, Asymmetric autoregressive conditional duration model, Intraday Value-at-Risk, Backtesting

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

189

Issue

2

First Page

437

Last Page

446

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2015.03.035

Publisher

Elsevier

Additional URL

http://dx.doi.org/10.1016/j.jeconom.2015.03.035

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