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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Bitcoin: Exploring Price Predictability and the Impact of Investor Sentiment
Author(s)
Everton Anger Cavalheiro
Paulo Sérgio Ceretta
Luíza Roloff Falck
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DOI:10.17265/1537-1506/2023.02.002
Affiliation(s)
Federal University of Pelotas, Pelotas, Brazil
Federal University of Santa Maria, Santa Maria, Brazil
Federal University of Pelotas, São Lourenço do Sul, Brazil
ABSTRACT
This article addresses the predictability of Bitcoin’s price by examining relationships between Bitcoin and financial and emotional variables such as the Fear and Greed Index (FGI), the American Interest Rate (FED), and the Stock Market Index (NASDAQ). Through the use of statistical techniques such as the Johansen Cointegration Test and Granger Causality, as well as forecasting models, the study reveals that, despite the notorious volatility of the cryptocurrency market, it is possible to identify consistent behavioral patterns that can be successfully used to predict Bitcoin returns. The approach that combines VAR models and neural networks stands out as an effective tool to assist investors and analysts in making informed decisions in an ever-changing market environment.
KEYWORDS
Bitcoin, price predictability, fear and greed index, American interest rate, NASDAQ
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