Abstract
We analyze the intraday time series of Bitcoin, comparing its features with those of traditional financial assets such as stocks and exchange rates. The results shed light on similarities as well as significant deviations from the standard patterns. In particular, our most interesting finding is the unusual presence of significant negative first-order autocorrelation of returns calculated on medium-frequency timeframes, such as one, two and four hours, signaling the presence of systematic mean reversion. It is also found that larger price movements lead to stronger reversals, in percentage terms. We finally point out the potential exploitability of the phenomenon by implementing a basic algorithmic trading strategy and retroactively applying it to the data. We explain the findings mainly through (i) investor and trader overreaction, (ii) excess volatility and (iii) cascading liquidations due to excessive use of leverage by market participants.
| Item Type: | Journal article |
|---|---|
| Faculties: | Mathematics, Computer Science and Statistics > Mathematics |
| Subjects: | 500 Science > 510 Mathematics |
| Language: | English |
| Item ID: | 97651 |
| Date Deposited: | 05. Jun 2023, 15:26 |
| Last Modified: | 05. Jun 2023, 15:26 |
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