Topological Data Analysis for Portfolio Management of Cryptocurrencies

TL;DR

This paper introduces a Topological Data Analysis-based system for cryptocurrency portfolio management, demonstrating its ability to outperform traditional methods without requiring feature engineering or domain expertise.

Contribution

It presents a novel TDA-based approach for cryptocurrency portfolio management, leveraging persistence landscapes to identify investment opportunities.

Findings

Outperforms classic portfolio management methods

Works effectively with over 1500 cryptocurrencies and 6 years of data

Eliminates need for feature engineering or domain knowledge

Abstract

Portfolio management is essential for any investment decision. Yet, traditional methods in the literature are ill-suited for the characteristics and dynamics of cryptocurrencies. This work presents a method to build an investment portfolio consisting of more than 1500 cryptocurrencies covering 6 years of market data. It is centred around Topological Data Analysis (TDA), a recent approach to analyze data sets from the perspective of their topological structure. This publication proposes a system combining persistence landscapes to identify suitable investment opportunities in cryptocurrencies. Using a novel and comprehensive data set of cryptocurrency prices, this research shows that the proposed system enables analysts to outperform a classic method from the literature without requiring any feature engineering or domain knowledge in TDA. This work thus introduces TDA-based portfolio management of cryptocurrencies as a viable tool for the practitioner.