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• W2799176022 abstract "The weak variance-alpha-gamma process is a multivariate Lévy process constructed by weakly subordinating Brownian motion, possibly with correlated components with an alpha-gamma subordinator. It generalises the variance-alpha-gamma process of Semeraro constructed by traditional subordination. We compare three calibration methods for the weak variance-alpha-gamma process, method of moments, maximum likelihood estimation (MLE) and digital moment estimation (DME). We derive a condition for Fourier invertibility needed to apply MLE and show in our simulations that MLE produces a better fit when this condition holds, while DME produces a better fit when it is violated. We also find that the weak variance-alpha-gamma process exhibits a wider range of dependence and produces a significantly better fit than the variance-alpha-gamma process on a S&P500-FTSE100 data set, and that DME produces the best fit in this situation." @default.
• W2799176022 created "2018-05-07" @default.
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• W2799176022 date "2018-08-23" @default.
• W2799176022 modified "2023-09-27" @default.
• W2799176022 title "Calibration for Weak Variance-Alpha-Gamma Processes" @default.
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• W2799176022 doi "https://doi.org/10.1007/s11009-018-9655-y" @default.
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