MVA Calculation and Optimization with Machine Learning Techniques

In the last few years a new margin requirement, the Initial Margin, was introduced by both Central Counterparties for cleared derivatives and BCBS\&IOSCO for derivatives Over The Counter in order to reduce the counterparty credit risk when dealing derivatives. Besides, due to its segregation, the IM funding always represents a cost. Consequently, a pricing adjustment, called (Initial) Margin Valuation Adjustment, needs to be applied. Since the IM is based on a risk measure (i.e. Value at Risk or Expected Shortfall), the MVA calculation involves a nested Monte Carlo simulation, which is computationally intractable with "brute force". Firstly, we are going to analyze several approaches discussed in recent literature in order to solve the computational problem. Then we are going to test Machine Learning algorithms to minimize the MVA from a monetary point of view. In conclusion, we are going to show two different methods for the computational time optimization.