Improved Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Deep Learning
By Evangelia Dragazi, Shuaiqiang Liu, Antonis Papapantoleon
Rating
1615
Battle Count: 215
Relevance
9/10
Highly relevant for pricing and risk management of multi-asset options in quantitative trading strategies
Implementation Complexity
7/10
Requires implementation of neural networks and optimization algorithms, but methodology is well-described
Reproducibility
4/5
Detailed methodology and hyperparameters provided, artificial data generation process explained
About this paper
Methodology: Penalization and Deep Learning. Problem types: Option Pricing, Optimization.
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