Cryptocurrency Trader's Risky Decision on Social Sentiment

Bitcoin is the latent disruptive innovation to revolutionize the current financial markets. Its technological idea enables digital transaction between parties without the need of an intermediary. In economic decision making, exploring the changes in the market value of Bitcoin on social, cognitive, and emotional factors is a scholarly project with business and policy implications. This study examines the static and dynamic interaction between social sentiment and the market value of bitcoin using machine based methods and exploratory empiricism. This work employs kernel regularized least square and Bayesian network and use vector error correction and vector autoregressive for dynamic causality with textual analysis. In a static model, the results show that Google trend and social sentiment has an immediate impact on bitcoin price. And the coin markets are influenced by the overall stock market. However, the dynamic estimation indicates that Bitcoin price affects Google trend and social sentiment formation, whereas Google trend and social sentiment influences Bitcoin trading volumes. Interestingly, Bayesian network analysis demonstrates that cryptocurrency traders show a tendency to sell bitcoin in a positive mood, while they tend to buy the coin in a negative mood. The results illustrate an investor behavior in the coin market on his/her prospect. Our findings show that social sentiment is formed by reflecting on Bitcoin market value but affects its transaction in the coin markets. In the condition, cryptocurrency traders’ investment attitude changes depending on the increase or decrease in social sentiment at the current emotion level. This study offers a new insight of how cryptocurrency traders make a risky decision in the coin markets where social sentiment is prevalent.