Machine Learning-Based Analysis of Crypto Currency Market Financial Risk Management

Abstract

Crypto currency is a form of digital currency that relies on cryptography to maintain and verify transactions, instead of a centralized authority. However, this decentralized nature can lead to several risks that can impact the assessments carried out by risk auditors. Money laundering is a significant financial risk associated with the growing popularity of crypto currency. This paper proposes machine learning - based approach that uses Hierarchical Risk Parity and unsupervised machine learning to analyse the financial risk associated with crypto currency markets. The study finds that machine learning algorithms can effectively capture the complex relationships between variables and provide accurate risk management. The study underscores the potential of machine learning based analysis to improve financial risk management in the constantly evolving world of crypto currencies.