Case study demonstrates series representations of levy process for predicting daily returns of Bitcoin and Ethereum, indicating effective simulations.
The paper presents two series representations of a L{\'e}vy process for the Generalized Tempered Stable (GTS) distribution: a series representation generated by the inverse tail integral and a short noise representation. Both series representations are used to simulate the daily returns of Bitcoin and Ethereum. The Q-Q plot analysis shows smooth linear patterns, indicating strong agreement between the empirical and theoretical GTS distributions.
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Aubain Nzokem (2025) studied this question.
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