All the frequencies matter in the Bitcoin market: an efficiency analysis

ABSTRACT

Most studies in the Bitcoin literature are focused on daily data without considering other options. Therefore, it is necessary to analyse Bitcoin features at different frequencies. In this letter, we examine Bitcoin efficiency from 1 min to weekly data using the generalized Hurst exponent. Our results show that Bitcoin is more efficient over time regardless of the frequency. In particular, we observe that, since 2016, daily data are generally the most efficient frequency while 1 min and weekly data are the most inefficient. These results are relevant for investors and scholars since we detect the most profitable frequencies and underline the relevance of analysing different frequencies than daily data.

KEYWORDS:

• Bitcoin
• market efficiency
• high-frequency data
• low-frequency data

JEL CLASSIFICATION:

• G14

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ The exponential decay is defined by $\alpha =1/\theta$ and $w_0$ is

3 $w_0(\alpha )=\frac{1-{\mathrm{e}}^{-\alpha }}{1-{\mathrm{e}}^{-\alpha \mathrm{\Delta }t}}.$3

² To ensure the precision of the wGHE, especially, in the case of weekly data, the weights’ characteristic time, $\theta$, includes two years of data for each frequency.

³ Instead of holding the asset only one day, traders hold the asset, for instance, 2 days, thus they calculate 2-day returns instead of daily returns.

⁴ For the sake of space, we add the corresponding Tables as supplementary material.

⁵ The only exceptions are: weekly data ($H(1)$) and 1-minute, 15-minute and 30-minute data ($H^w(1)$).

⁶ We also identify the most efficient and inefficient frequency for high frequencies (1 min, 5 min, 15 min, 30 min and 60 min) and low frequencies (1 day, 2 days, 3 days, 4 days, 5 days, 6 days and 1 week).