A news event-driven approach for the historical value at risk method

F.P. Hogenboom, M. Winter, de, F. Frasincar, U. Kaymak

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
3 Downloads (Pure)

Abstract

Value at Risk (VaR) is a tool widely used in financial applications to assess portfolio risk. The historical stock return data used in calculating VaR may be sensitive to rare news events that occur during the sampled period and cause trend disruptions. Therefore, in this paper, we measure the effects of various news events on stock prices. Subsequently, we identify irregular events using a Poisson distribution, and we examine whether VaR accuracy can be improved by considering news events as an additional input in the calculation. Our experiments demonstrate that VaR predictions for rare event occurrences can be improved by removing the event-generated disturbance from the stock prices for a small, optimized time window.
Original languageEnglish
Pages (from-to)4667-4675
Number of pages9
JournalExpert Systems with Applications
Volume42
Issue number10
DOIs
Publication statusPublished - 2015

Fingerprint

Dive into the research topics of 'A news event-driven approach for the historical value at risk method'. Together they form a unique fingerprint.

Cite this