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A machine learning approach to portfolio pricing and risk...

Author
Lucio Fernandez-Arjona, Damir Filipović
Date Updated
2022/05/08
Category
q-fin.RM
Date Published
2020/04/29
Date Retrieved
2022/05/09
Description
We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. The model learns the features necessary for an effective low-dimensional representation, overcoming the curse of dimensionality common to function approximation in high-dimensional spaces. We show results based on polynomial and neural network bases. Both offer superior results to naive Monte Carlo methods and other existing methods like least-squares Monte Carlo and replicating portfolios.
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Posts
9
Readers
15
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1.25
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URL
https://arxiv.org/abs/2004.14149
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