Ethereum Price Prediction using Topological Data Analysis

【Author】 Hafez, Samia M.; ElNainay, Mustafa; Abougabal, Mohamed; Kosba, Ahmed

【Source】2022 IEEE GLOBAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS (GCAIOT)

【影响因子】

【Abstract】The popularity of cryptocurrencies is increasing, as they have become an economy of their own, due to the observed returns of investments in cryptocurrencies and digital assets. This led to an increasing interest in the prediction of their prices over the past few years. Ethereum is one of the most popular cryptocurrencies that has witnessed an increase of prices since 2015 while having the second largest market cap. Ethereum is a decentralized platform that incorporates several interactions, not limited to asset trading only; it is also a platform of smart contracts execution and token trading. In this work, we aim at reflecting the interactions perceived in the Ethereum network on Ether prices using Topological Data Analysis (TDA). We introduce a method to extract the TDA features of the indicators of different interaction networks; traded volumes, smart contracts, and transactions between accounts. We conducted an analysis of the effect of using TDA features on Ether price prediction and extended our method to predict the prices of eight Ethereum tokens. Our method resulted in 0.75%, 4.9%, and 13.75% MAPE in hourly, daily, and weekly forecasts respectively, outperforming the previously reported results.

【Keywords】Blockchains; Prediction methods; Cryptocurrency; Time series analysis

【发表时间】2022

【收录时间】2023-05-24

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-价格预测