Shot-Noise Processes in Finance

Thorsten Schmidt ()
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Thorsten Schmidt: University Freiburg, Department of Mathematical Stochastics

Chapter Chapter 18 in From Statistics to Mathematical Finance, 2017, pp 367-385 from Springer

Abstract: Abstract Shot-Noise processes constitute a useful tool in various areas, in particular in finance. They allow to model abrupt changes in a more flexible way than processes with jumps and hence are an ideal tool for modelling stock prices, credit portfolio risk, systemic risk, or electricity markets. Here we consider a general formulation of shot-noise processes, in particular time-inhomogeneous shot-noise processes. This flexible class allows to obtain the Fourier transforms in explicit form and is highly tractable. We prove that Markovianity is equivalent to exponential decay of the noise function. Moreover, we study the relation to semimartingales and equivalent measure changes which are essential for the financial application. In particular we derive a drift condition which guarantees absence of arbitrage. Examples include the minimal martingale measure and the Esscher measure.

Keywords: Shot-noise processes; Martingale measure; Semimartingale; Markovianity; minimal martingale measure; Esscher measure (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-50986-0_18

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DOI: 10.1007/978-3-319-50986-0_18

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