Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement

In this paper, we present an artificial neural network framework for portfolio compression of a large portfolio of European options with varying maturities (target portfolio) by a significantly smaller portfolio of European options with shorter or same maturity (compressed portfolio), which also rep...

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Veröffentlicht in:	arXiv.org 2024-02
Hauptverfasser:	Vikranth Lokeshwar Dhandapani, Jain, Shashi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Capital requirements Credit risk Exposure Iterative methods Machine learning Monte Carlo simulation Neural networks Parameters Risk management
Online-Zugang:	Volltext
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