Event-based historical Value-at-Risk

Author

Hogenboom, Frederik ; de Winter, M. ; Jansen, Maarten ; Hogenboom, A. ; Frasincar, Flavius ; Kaymak, Uzay

Author_Institution

Erasmus Sch. of Econ., Erasmus Univ. Rotterdam, Rotterdam, Netherlands

fYear

2012

Firstpage

1

Lastpage

7

Abstract

Value-at-Risk (VaR) is an important tool to assess portfolio risk. When calculating VaR based on historical stock return data, we hypothesize that this historical data is sensitive to outliers caused by news events in the sampled period. In this paper, we research whether the VaR accuracy can be improved by considering news events as additional input in the calculation. This involves processing the historical data in order to reflect the impact of news on the stock returns. Our experiments show that when an event occurs, removing the noise (that is caused by an event) from the measured stock prices for a small time window can improve VaR predictions.

Keywords

investment; probability; risk analysis; stock markets; VaR accuracy; VaR predictions; event-based historical value-at-risk; financial markets; historical stock return data; portfolio risk; small time window; Companies; Measurement uncertainty; Noise; Optimized production technology; Portfolios; Reactive power; Standards;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Financial Engineering & Economics (CIFEr), 2012 IEEE Conference on

Conference_Location

New York, NY

ISSN

PENDING

Print_ISBN

978-1-4673-1802-0

Electronic_ISBN

PENDING

Type

conf

DOI

10.1109/CIFEr.2012.6327787

Filename

6327787