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, Via dell'Artigliere 19, 37129 Verona, Italy

International Journal of Theoretical and Applied Finance (IJTAF), 2012, vol. 15, issue 03, 1-22

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)
Date: 2012
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Working Paper: Monte Carlo derivative pricing with partial information in a class of doubly stochastic Poisson processes with marks (2010)
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DOI: 10.1142/S0219024912500185

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