# Implementation of two Backward SDEs using a Monte Carlo regression method

*label*Mathematics

*timer*Asked: Jun 24th, 2018

*account_balance_wallet*$60

**Question description**

Hi everyone, I have a project to do where I have to implement two different backward SDEs in a jupyter notebook (kernel python 3) and solving them via a montecarlo regression method. All the theoretical background is in the paper attached "Acturial_Sci_Quant_Finance_009_final_v5" and my personal task is the one to solve the FVA and KVA implementation using the function called "u" in the paper. The aim of the assignment is to represents a graph as the one in page 10 (the first graph by left) that represents the values of FVA and KVA wrt alpha. In the other pdf file, you can find the final implementation to do, with the formulas (file pdf "Projects" only slides 6 and 7). The pdf file "0508491" is a paper I found online that I think represents a possible algorithm to follow. I am not really sure about that, but feel free to ask. If you have no experience with stochastic calculus implementation with python, I recommend you not to bid for this question.

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