In this chapter we introduce jump-diffusion processes and provide a theoretical framework that justifies the nonparametric (data-based) extraction of the parameters and functions controlling the arrival of a jump and the distribution of the jump size from the estimated conditional Kramers–Moyal moments. The method and the results are applicable to both stationary and nonstationary time series in the presence of discontinuous jump components; see Chap. 17.
CITATION STYLE
Tabar, M. R. R. (2019). Jump-Diffusion Processes. In Understanding Complex Systems (pp. 111–121). Springer Verlag. https://doi.org/10.1007/978-3-030-18472-8_12
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