Predicting price volatility crytocurrency ethereum

Volatility is essential when trading or investing in cryptocurrency Ethereum. Over the years, investors, traders and investment banks have found it difficult to predict the price volatility of Ethereumdue to its rapid price fluctuation. This report focuses on forecasting the price volatility of Ethereum for the next two days using daily historical observations of the price of Ethereumobtained from Coindesk and tweets extracted from Twitter ranging from the 1st of August 2022 to the 8th of August 2022. Two models are used to compute the forecast for the next two days: support vector regression and recurrent neural network. The main evaluationmetric used is the mean absolute error. In this study, according to MAE, RNN without tweets forecasts outperformthe SVR model without tweets forecasts, with the best model being the RNN without tweets producing an MAE of 0.0309.

Author dc:creator

• Rambevha, Vhukhudo Ronny

Advisors dc:contributor.advisor

• Sigauke, Caston
• Ravele, Thakhani

• Crytocurrency
• Ethereum
• Recurrent neural network
• Support vector regression
• Volatility forecasting
• UCTD

Statement dc:rights

• University of Venda

Language dc:language.iso

en

Repository record dc:identifier.uri

https://univendspace.univen.ac.za/handle/11602/3103

OAI identifier oai:identifier

oai:univendspace.univen.ac.za:11602/3103