Topological Data Analysis for Portfolio Management of Cryptocurrencies

Rodrigo Rivera-Castro, Polina Pilyugina and Evgeny Burnaev

Papers from arXiv.org

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.

Date: 2020-09
New Economics Papers: this item is included in nep-pay
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Published in 2019 International Conference on Data Mining Workshops (ICDMW)

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