Approximation of skewed and leptokurtic return distributions
Autor: | Young Shin Kim, Frank J. Fabozzi, Svetlozar T. Rachev, Matthias Scherer |
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Rok vydání: | 2012 |
Předmět: | |
Zdroj: | Applied Financial Economics. 22:1305-1316 |
ISSN: | 1466-4305 0960-3107 |
Popis: | There is considerable empirical evidence that financial returns exhibit leptokurtosis and nonzero skewness. As a result, alternative distributions for modelling a time series of the financial returns have been proposed. A family of distributions that has shown considerable promise for modelling financial returns is the tempered stable and tempered infinitely divisible distributions. Two representative distributions are the classical tempered stable and the Rapidly Decreasing Tempered Stable (RDTS). In this article, we explain the practical implementation of these two distributions by (1) presenting how the density functions can be computed efficiently by applying the Fast Fourier Transform (FFT) and (2) how standardization helps to drive efficiency and effectiveness of maximum likelihood inference. |
Databáze: | OpenAIRE |
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