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Monte Carlo derivative pricing with partial information in a class of doubly stochastic Poisson processes with marks

Silvia Centanni () and Marco Minozzo ()
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Silvia Centanni: Department of Economics (University of Verona)

No 22/2010, Working Papers from University of Verona, Department of Economics

Abstract: To model intraday stock price movements we propose a class of marked doubly stochastic Poisson processes, whose intensity process can be interpreted in terms of the effect of information release on market activity. Assuming a partial information setting in which market agents are restricted to observe only the price process, a filtering algorithm is applied to compute, by Monte Carlo approximation, contingent claim prices, when the dynamics of the price process is given under a martingale measure. In particular, conditions for the existence of the minimal martingale measure Q are derived, and properties of the model under Q are studied.

Keywords: Minimal martingale measure; News arrival; Marked point process; Nonlinear filtering; Reversible jump Markov chain Monte Carlo; Ultra high frequency data (search for similar items in EconPapers)
JEL-codes: C01 C15 G12 G13 G17 (search for similar items in EconPapers)
Pages: 34
Date: 2010-12
New Economics Papers: this item is included in nep-mst and nep-ore
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Journal Article: MONTE CARLO DERIVATIVE PRICING WITH PARTIAL INFORMATION IN A CLASS OF DOUBLY STOCHASTIC POISSON PROCESSES WITH MARKS (2012) Downloads
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