https://orcid.org/0000-0003-4443-0750
![Sample our Behavioral Sciences journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/110801/TOC-Subject-Sample-2021-Behavioral-Sciences.jpg"})
Abstract
This study introduces a comprehensive Google search volume based Bitcoin Sentiment Index (BSI) and investigates its symmetric and asymmetric association with Bitcoin's returns, volume, and volatility, and with United States Dollar (USD) exchange rates. Our results indicate a positive association of BSI with Bitcoin's returns and volume, but a negative relationship with its return volatility. Besides, Bitcoin's optimistic sentiments have an asymmetric relationship with the USD exchange rate in the short-run, and the Bitcoin price has an asymmetric and negative association with USD in the short-run and long-run. We also found a 35.47% speed of adjustment to long-run equilibrium.
Notes
1. See Kroll, J. A., Davey, I. C., & Felten, E. W. (2013, June). The economics of Bitcoin mining, or Bitcoin in the presence of adversaries. In Proceedings of WEIS (Vol. 2013, p. 11).
2. The Bitcoin related terms are taken from multiple sources (including social media, newspapers, and magazines), the detailed construction of BSI is discussed in the section Measuring Bitcoin Sentiment Index (BSI). Data of the Bitcoin sentiment index (both optimistic BSI and pessimistic BSI) will be provided on demand. Additionally, BSI will be upgraded from time by time.
3. Shin, Yu, and Greenwood-Nimmo (2014) introduced a non-linear autoregressive distributed lagged (NARDL) model. It is an extension of autoregressive distributed lagged (ARDL) by (Pesaran & Shin, 1998).
5. According to Tversky and Kahneman (1992) people value losses 2.25 times more than gains. In other words, losses heart 2.25 times more than pleasure comes from a profit of the same amount.