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- Title
The Normal-Generalised Gamma-Pareto Process: A Novel Pure-Jump Lévy Process with Flexible Tail and Jump-Activity Properties.
- Authors
Ayed, Fadhel; Juho Lee; Caron, François
- Abstract
We propose a novel family of self-decomposable Lévy processes where one can control separately the tail behavior and the jump activity of the process, via two different parameters. Crucially, we show that one can sample exactly increments of this process, at any time scale; this allows the implementation of likelihood-free Markov chain Monte Carlo algorithms for (asymptotically) exact posterior inference. We use this novel process in Lévy-based stochastic volatility models to predict the returns of stock market data, and show that the proposed class of models leads to superior predictive performances compared to classical alternatives.
- Subjects
LEVY processes; MARKOV chain Monte Carlo; STOCHASTIC analysis; STOCK exchanges; PARAMETERIZATION; GENERALIZATION
- Publication
Bayesian Analysis, 2024, Vol 19, Issue 1, p123
- ISSN
1936-0975
- Publication type
Article
- DOI
10.1214/22-BA1343