High Frequency Data Aggregation in Value-at-Risk Models: Is Daily Data Enough?

Milda Pranckevičiūtė ()
Additional contact information
Milda Pranckevičiūtė: Risk Manager in AB Lietuvos Draudimas

Chapter 8 in FindEcon Monograph Series: Advances in Financial Market Analysis, 2012, vol. 10, pp 137-149 from University of Lodz

Abstract: Chapter 8 is another example of the use of high frequency data. M. Pranckevičiūtė dealt with the problem of using aggregated high frequency risk factors to estimate Value-at-Risk as VaR estimates are very important to financial institutions in risk management. The empirical experiment on the VaR value dependence on the choice of risk factors aggregation showed how considerably the estimates may differ. According to M. Pranckevičiūtė, recent shocks to the world economy and decreases in the financial markets motivates choosing conservative risk measurement models which result in higher estimates of risk. This makes financial institutions either hold larger amounts of capital or reduce risky portfolios.

Keywords: Value-at-Risk; High frequency data aggregation; Risk management (search for similar items in EconPapers)
JEL-codes: C01 E02 F00 G00 (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.repec.uni.lodz.pl/RePEc/files/findec/2012/2012_No_10_Ch_8.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ann:findec:book:y:2012:n:10:ch:08:mon

Access Statistics for this chapter

More chapters in FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making from University of Lodz Contact information at EDIRC.
Bibliographic data for series maintained by Piotr Wdowiński ().