Home  Journals  Financial Analytics: Science and Experience  1(359) - 2022 January-March

Forecasting cryptocurrency market prices

Received: 27 January 2022

Received in revised form: 4 February 2022

Accepted: 11 February 2022

Available online: 28 February 2022

Subject Heading: MATHEMATICAL ANALYSIS AND MODELING IN ECONOMICS

JEL Classification: C32, C53, E42

Pages: 42–64

https://doi.org/10.24891/fa.15.1.42

Subject. This article explores the cryptocurrency market and the changes in the three most popular cryptocurrencies currently, namely Bitcoin, Ethereum and Tether, in particular.
Objectives. The article aims to answer the question whether it is possible to predict the cryptocurrency rate taking into account the high market value volatility or not.
Results. Testing the cryptocurrency market for information efficiency made it possible to choose the most adequate model for predicting the market prices of cryptocurrency, namely the Heterogeneous Autoregressive model of Realized Volatility – HAR-RV model. Despite the simplicity of the structure, the HAR-RV model shows good results in predicting the market prices of cryptocurrency. Taking into account that forecasting the changes in time series using regression models fails with unexpected spikes in market information, the Shannon entropy gets calculated, the values of which warn the researcher in advance about the growth or decline of the cryptocurrency rate. The article proposes to enhance the predictive properties of the HAR-RV model by calculating the Shannon information entropy for the studied time series.
Conclusions and Relevance. Currently, despite the high volatility of the cryptocurrency, the changes in its market price can be predicted quite accurately. Cryptocurrency meets all the Austrian School's requirements for money, and in the future, it will be able to compete with fiat currencies significantly. The proposed method of forecasting the changes in time series can be used by analysts and traders concerning their stock, exchange, and money market activities.

Keywords: Bitcoin, efficiency, heterogeneous market, realized volatility, entropy

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