leptokurtosis


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leptokurtosis

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It is one of the most widely used and well-known volatility models due to its flexibility and accuracy to modeling stylized facts of financial asset returns, such as leptokurtosis and volatility clustering.
Financial time series data is generally characterized by volatility clustering, leptokurtosis and heavy tailed distributions.
Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates.
Techniques to Account for Leptokurtosis and Assymetric Behaviour in Returns Distributions, Journal of Risk Finance, 11(5), 464-480.
Although these models can handle some key characteristic of stocks such as leptokurtosis, leverage effects, and volatility clustering, they suffer from many parameters that should be estimated.
Despite the significant differences which derive from the differences in theoretical postulates on which approaches are based, a common feature of the most popular VaR approaches is their inability to be simultaneously effective in capturing leptokurtosis and strong time-varying volatility.
Another advantage of quantile regression over OLS regression is that the quantile regression estimates are more robust against outliers in the response measurements, which gives it an edge when handling heteroskedasticity, skewness, and leptokurtosis in financial data.
All this volatility results in pronounced tail risks, that is, much higher leptokurtosis in the distribution of time series of asset prices and interest rates (Orlowski, 2012; Gabrisch and Orlowski, 2011).
These facts together with a third moment different from zero and a fourth moment higher than three, indicates a non-normal distribution and leptokurtosis.
The analysis of distribution showed that the Polish financial time series behave in the same way as their counterparts from much more developed financial markets, namely, they are characterized by leptokurtosis and "thicker" tails than the normal distribution function.
This method will tend to increase the numbers of zero and large returns, which will tend to increase the variance and induce leptokurtosis.
La distribucion de la Rentabilidad o de Retornos posee leptokurtosis.