Topological Data Analysis for Portfolio Management of Cryptocurrencies
This provides a new tool for cryptocurrency investors, though it is incremental as it adapts an existing TDA approach to a specific domain.
The authors tackled portfolio management for cryptocurrencies by applying Topological Data Analysis (TDA) with persistence landscapes to a dataset of over 1500 cryptocurrencies over 6 years, showing it outperforms a classic method without requiring feature engineering or TDA domain knowledge.
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.