Document Search
Add To My Bookshelf Sign in or Register Save And Annotate

backtesting sign in to follow this
crisis sign in to follow this
parametric sign in to follow this
historical simulation sign in to follow this
Monte Carlo sign in to follow this

VaR Methods sign in to follow this
--Backtesting sign in to follow this
Discuss This Paper
Sign in to follow this page
Recent Comments
An Analysis of the Maximum Losses Expected Calculated by VaR (Value at Risk) in Moments of Systemic Crisis
Year Of Publication: 2010
Month Of Publication: July
Pages: 18
Download Count: 10
View Count: 1709
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 12-25-2010
Publisher: Administrator
One of the main ways of measuring risks is the calculation of the VaR (Value at Risk), where the risk is measured in value. One of the assumptions of VaR is that the distribution of the financial assets returns follows a normal distribution, but what has evidenced in recent years is a distribution with more extreme values, mainly in function of unexpected financial crises by normality. Therefore, financial disasters are not often enshrined in the maximum expected losses by the financial market. The present work had as its overall objective: To verify if the VaR manages to capture the maximum expected loss in moments of systemic crisis, as well as to analyze which of the three methods used for the calculation has the slightest error in their estimates. To achieve the general objective, the VaR was calculated daily, during the period from 1993 to 2010, with mobile windows, using three methodologies: normal linear, historical simulation and Monte Carlo simulation. It was found that in moments of systemic crisis the VaR is unable to predict accurately the expected maximum loss, not properly safeguarding the investor as the volatility of
Ramos, Bruno V. F. Sign in to follow this author
Lustosa, Paulo R. B. Sign in to follow this author
Paulo, Edilson Sign in to follow this author
This document's citation network:
Similar Documents:
Close window
Sign up in one step, no personal information required. Already a Member?

Repeat Email:
User Name:
Confirm Password:

Sign Up

Welcome to GloriaMundi!
Thanks for singning up

continue or edit your profile