Financial Engineering Workshop - Roberto Baviera (Politecnico di Milano)
Bayes Business School, 106 Bunhill Row
Room 3002 (3rd floor)
106 Bunhill Row, London EC1Y 8TZ, UK
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Abstract
In this paper, we present a fast Monte Carlo scheme for additive processes. We analyze in detail numerical error sources and propose a technique that reduces the two major sources of error. We also compare our results with a benchmark method: the jump simulation with Gaussian approximation. We show an application to additive normal tempered stable processes, a class of additive processes that calibrates "exactly" the implied volatility surface. Numerical results are relevant. The algorithm is an accurate tool for pricing path-dependent discretely-monitoring options with errors of one bp or below. The scheme is also fast: the computational time is of the same order of magnitude of standard algorithms for Brownian motions.
Bio
Roberto Baviera is Associate Professor at Politecnico di Milano; his main interests are derivative pricing, model risk and energy finance. Previously, he has been interest rates trader in leading Italian investment banks for more than 8 years and specialist consultant for some of the major European financial institutions for 4 years. Prior to joining the financial industry, Prof. Baviera has been in the Department of Finance&Economie HEC (Paris) for two years; he holds a Ph.D. in Physics with a thesis on information theory applications to derivative pricing and portfolio selection.
The Financial Engineering Workshop will take place in-person and online via Zoom.
To access the link to the online seminar, please register the day before the seminar, otherwise you may not be given access.
Food Provided (Light refreshments )
Where
Bayes Business School, 106 Bunhill Row
Room 3002 (3rd floor)
106 Bunhill Row, London EC1Y 8TZ, UK