Sequential sampling for CGMY processes via decomposition of their time changes
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Publication:3120085
DOI10.1002/NAV.21821zbMATH Open1419.91632arXiv1708.00189OpenAlexW2962999767WikidataQ128611901 ScholiaQ128611901MaRDI QIDQ3120085
Publication date: 1 March 2019
Published in: Naval Research Logistics (Search for Journal in Brave)
Abstract: We present a new and easy-to-implement sequential sampling method for CGMY processes with either finite or infinite variation, exploiting the time change representation of the CGMY model and a decomposition of its time change. We find that the time change can be decomposed into two independent components. While the first component is a emph{finite} emph{generalized gamma convolution} process whose increments can be sampled by either the exact double CFTP ("coupling from the past") method or an approximation scheme with high speed and accuracy, the second component can easily be made arbitrarily small in the sense. Simulation results show that the proposed method is advantageous over two existing methods under a model calibrated to historical option price data.
Full work available at URL: https://arxiv.org/abs/1708.00189
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