Analysis of Bitcoin prices using market and sentiment variables
Bibliographic Data
| ID | 21543392 |
|---|---|
| Authors | Burcu Kapar (0000-0002-1557-4723, American University in Dubai Dubai United Arab Emirates), José Olmo (0000-0002-0437-7812, Department of Economic Analysis Universidad de Zaragoza Zaragoza Spain, corresponding author) |
| Year | 2021 |
| Volume | 44 |
| Issue | 1 |
| Pages | 45-63 |
| Publication date | 2021-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | World Economy (JOURNAL) |
| Journal identifiers | ISSN: 0378-5920 • E-ISSN: 1467-9701 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/twec.13020 |
| OpenAlex | W3048753459 |
| Language | EN |
| Citations received | 1 |
| References cited | 32 |
This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices
Cryptocurrency · Econometrics · Economics · Financial economics · Monetary economics · Blockchain Technology Applications and Security · Computer Science · Financial Markets and Investment Strategies · Market Dynamics and Volatility · Mathematics
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,25 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |