Main Article Content
This research explores various methods to estimate Value at Risk for a portfolio of high and medium liquidity Colombian stocks. It concludes that, according to the characteristics of these assets, Full Montecarlo is more robust than other parametric methods –particularly the Normal method-, and the historical simulation. However, to avoid model risk, it requires a correct specification of the stochastic process followed by each of the risk factors. Given the evidence of fat tails on the return series, volatility models such as GARCH, EGARCH, PARCH and APARCH are used for this purpose. After that, we compare the one-step ahead VaR forecast given by these models with the one obtained by parametric methods. It is found that Garch models predict VaR better since they capture the fat tails characteristic of these series. Once the stochastic process for each asset is properly identified, the Full Montecarlo is applied to estimate VaR.
Download data is not yet available.
VaR, Market Risk, Full Montecarlo, Garch, Egarch, Parch, Aparch.
How to Cite
VERGARA COGOLLO, María Auxiliadora; MAYA OCHOA, Cecilia. Structured Monte Carlo. Estimated value at risk in a stock portfolio in Colombia. AD-minister, [S.l.], n. 15, p. 68-88, dec. 2009. ISSN 2256-4322. Available at: <http://publicaciones.eafit.edu.co/index.php/administer/article/view/204>. Date accessed: 19 mar. 2018.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under aCreative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).