The University of Southampton
University of Southampton Institutional Repository

Overnight news and daily equity trading risk limits

Overnight news and daily equity trading risk limits
Overnight news and daily equity trading risk limits
This paper proposes a new bivariate modeling approach for setting daily equity-trading risk limits using high-frequency data. We construct one-day-ahead Value-at-Risk (VaR) forecasts by taking into account the different dynamics of the overnight and daytime return processes and their covariance. The covariance is motivated by market microstructure effects such as price staleness and news spillover. Among the competitors we include a simpler bivariate model where the overnight return is redefined by moving the open price further into the trading day, and a univariate model based on the close-to-close return and an overnight-adjusted realized volatility. We illustrate the different approaches using data on the S&P 500 and Russell 2000 indices. The evidence in favour of modeling the covariance is more convincing for the latter index due to the lower trading volumes and, relatedly, the less efficient price discovery at market open for small-cap stocks.
overnight, price discovery, realized volatility, risk management, value-at-risk
1479-8409
1-27
Ahoniemi, K.
26caf4ab-5468-4b5f-8947-1112c5d4bbbb
Fuertes, A.-M.
fa47c7a7-1299-402d-9c9d-523a9b9aa634
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e
Ahoniemi, K.
26caf4ab-5468-4b5f-8947-1112c5d4bbbb
Fuertes, A.-M.
fa47c7a7-1299-402d-9c9d-523a9b9aa634
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e

Ahoniemi, K., Fuertes, A.-M. and Olmo, J. (2015) Overnight news and daily equity trading risk limits. Journal of Financial Econometrics, 13 (1), 1-27. (doi:10.1093/jjfinec/nbu032).

Record type: Article

Abstract

This paper proposes a new bivariate modeling approach for setting daily equity-trading risk limits using high-frequency data. We construct one-day-ahead Value-at-Risk (VaR) forecasts by taking into account the different dynamics of the overnight and daytime return processes and their covariance. The covariance is motivated by market microstructure effects such as price staleness and news spillover. Among the competitors we include a simpler bivariate model where the overnight return is redefined by moving the open price further into the trading day, and a univariate model based on the close-to-close return and an overnight-adjusted realized volatility. We illustrate the different approaches using data on the S&P 500 and Russell 2000 indices. The evidence in favour of modeling the covariance is more convincing for the latter index due to the lower trading volumes and, relatedly, the less efficient price discovery at market open for small-cap stocks.

Text
Manuscript_JFEC-2013-084.pdf - Accepted Manuscript
Restricted to Registered users only
Download (577kB)
Request a copy

More information

Accepted/In Press date: 23 December 2014
e-pub ahead of print date: 13 February 2015
Keywords: overnight, price discovery, realized volatility, risk management, value-at-risk
Organisations: Economics

Identifiers

Local EPrints ID: 376503
URI: http://eprints.soton.ac.uk/id/eprint/376503
ISSN: 1479-8409
PURE UUID: d14ded1d-cd41-4551-9206-5126f4fc0c78
ORCID for J. Olmo: ORCID iD orcid.org/0000-0002-0437-7812

Catalogue record

Date deposited: 29 Apr 2015 15:26
Last modified: 15 Mar 2024 03:46

Export record

Altmetrics

Contributors

Author: K. Ahoniemi
Author: A.-M. Fuertes
Author: J. Olmo ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×