Con preghiera di diffusione
To Whom It May Concern
Upcoming PhD Course <<<<<<<<<<<<<<<<<<<<<<<<<<<<
Giorgia Callegaro (Università degli Studi di Padova) Lucio Fiorin (Università degli Studi di Padova) Daniele Marazzina (Politecnico di Milano)
Option Pricing: from Monte Carlo Methods to Quantization
The PhD Course (5 CFU) will take place in the Seminar Room of the Third Floor of the Department of Mathematics, Politecnico di Milano, in via Bonardi, 9, Milano, according to the following calendar:
May, 8th: 11am-1pm and 2pm-6pm May, 9th: 9am-1pm and 2pm-4pm May, 15th: 11am-1pm and 2pm-6pm May, 16th: 9am-1pm and 2pm-4pm May, 17th: 10am-12pm and 1pm-3pm
For further details, please contact
Daniele Marazzina daniele.marazzina@polimi.it Giorgia Callegaro gcallega@math.unipd.it
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Abstract:
Monte Carlo methods are extensively used in finance to value and analyze complex instruments, portfolios and investments by simulating the various sources of uncertainty affecting their value. The advantage of Monte Carlo methods over other techniques increases as the dimensions (sources of uncertainty) of the problem increase. However, it is well known that the disadvantage of Monte carlo methods is the slow convergence, and thus the high computational cost of the algorithms.
Quantization is a way to approximate a random vector or a stochastic process using a nearest neighbour projection on a finite codebook. The birth of quantization dates back to the 1950s, when in the Bell laboratories ad hoc signal discretization procedures were developed for signal transmission. In the last years, Quantization has been deeply considered in numerical probability, especially for solving problems arising in mathematical finance, presenting itself as a de facto alternative to Monte Carlo methods. The purpose of the course is to highlight the characteristics of the two methodologies and to deeply analyze (and implement) their applications in financial context, mainly option pricing.