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- W2969879804 abstract "Accurate forecasting of risk is the key to sucessful riskmanagement techniques. Given the fat-tailed characterisitic offinancial returns, the assumptions of modeling these returns withthe thin-tailed Gaussian distribution is inappropriate. In this papera more accurate VaR estimate is tested using the “stable” or “α-stable” distribution, which allows for varying degrees of tailheaviness and varying degrees of skewness. Stable VaRmeasures are estimated and forecasted using the main LatinAmerican stock market indexes. The results show that the stablemodeling provides conservative 99% VaR estimates, while thenormal VaR modeling significantly underestimates 99% VaR. The95% VaR stable and normal estimates, using a window length of50 observations, are satisfactory. However, increasing thewindow length to 125 and 250 observations worsens the stableand the normal VaR measurements." @default.
- W2969879804 created "2019-08-29" @default.
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- W2969879804 date "2001-01-01" @default.
- W2969879804 modified "2023-09-28" @default.
- W2969879804 title "Measuring risk based on stable distributions: an examination of Latin American stock indexes" @default.
- W2969879804 hasPublicationYear "2001" @default.
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