Computational Tools for the Analysis of Market Risk
Alberto Suárez () and
Santiago Carrillo ()
Computational Economics, 2003, vol. 21, issue 1, 153-172
Abstract:
The estimation and management of risk is an important and complex task faced by market regulators and financial institutions. Accurate and reliable quantitative measures of risk are needed to minimize undesirable effects on a given portfolio fromlarge fluctuations in market conditions. To accomplish this, a series of computational tools has beendesigned, implemented, and incorporated into MatRisk, an integratedenvironment for risk assessment developed in MATLAB. Besides standard measures, such as Value at Risk(VaR), the application includes other more sophisticated risk measures that address the inability of VaRproperly to characterize the structure of risk. Conditionalrisk measures can also be estimated for autoregressive models with heteroskedasticity, including some novel mixture models. These tools are illustrated with a comprehensive risk analysis of the Spanish IBEX35 stock index. Copyright Kluwer Academic Publishers 2003
Keywords: risk analysis; Value-at-Risk; Extreme Value Theory; Shortfall; MaxVaR; heteroskedasticity; autoregressive processes; mixture models (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1023/A:1022267720606 (text/html)
Access to full text is restricted to subscribers.
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:kap:compec:v:21:y:2003:i:1:p:153-172
Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2
DOI: 10.1023/A:1022267720606
Access Statistics for this article
Computational Economics is currently edited by Hans Amman
More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().