Bitcoin at High Frequency

Round  1

Reviewer 1 Report

The proposed manuscript deals with an interesting and timely topic (the behavior of Bitcoin returns) using high frequency data and appropriate methods. Accordingly, the manuscript succeeds the time and methods constraints. However, some shortcomings need to be addressed before publication.

1-      The cited literature is limited. It misses some relevant papers related to the long memory (Bouri et al., 2018), predictability of returns and volatility (Blacilar et al., 2017), GARCH-based models and uncover evidence of a leverage effect (Bouri et al., 2017), HAR model (Aalborg et al.,2018).

Balcilar M., Bouri E., Gupta, R. and Roubaud D. (2017). Can volume predict Bitcoin returns? A quantiles-based Approach. Economic Modelling, Vol. 64, pp. 172-189. http://dx.doi.org/10.1016/j.econmod.2017.03.019.

Bouri E., Gil-Alana L.A., Gupta R. and Roubaud D. (2018). Modelling Long Memory Volatility in the Bitcoin Market: Evidence of Persistence and Structural Breaks. International Journal of Finance and Economics, https://doi.org/10.1002/ijfe.1670

Bouri E., Azzi G. and Dyhrberg, A.H. (2017). On the Return-volatility Relationship in the Bitcoin Market around the Price Crash of 2013. Economics: The Open-Access, Open-Assessment E-Journal, 11 (2017-2), pp. 1-16. http://dx.doi.org/10.5018/economics-ejournal.ja.2017-2

Aalborg, H. A., Molnár, P., and de Vries, J. E. (2018). What can explain the price, volatility and trading volume of Bitcoin?. Finance Research Letters. https://doi.org/10.1016/j.frl.2018.08.010

2-      The results have to be better discussed and compared to prior findings. In a related issue, their economic significance needs further elaboration.

3-      The conclusion section should go beyond just the summarization of the paper. Policy implications should be added as well as new paths for future research.

Author Response

See the attached pdf.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper present some interesting findings.

I suggest the author to account for the following points.

1) Please explain why Coinbase was used instead of GDAX, when GDAX is the parental exchange and Coinbase is a sub exchange of GDAX. Surely the data on GDAX reflects a better representation?

2) I suggest the author to reference the paper by Zhang et al. (2019), which provides some interesting results on market efficiency on high frequency cryptocurrencies. This should be included at the introduction literature section.

Zhang, Y., Chan, S., Chu, J., & Nadarajah, S. (2019). Stylised facts for high frequency cryptocurrency data. Physica A: Statistical Mechanics and its Applications, 513, 598-612.

3) Please provide more motivation on the purpose of the work.

Author Response

See the attached pdf.

Author Response File: Author Response.pdf

Round  2

Reviewer 1 Report

Although the overall quality of the revised manuscript has enhanced, I am quite surprised (in a negative way) how the authors have addressed some of my comments: My previous comment (#1) was formulated with the aim of better positioning the paper  within the related literature. However, the authors ignored most of it and when they follow part of it, they cited one related paper in a footnote (footnote #3) and ignored the others that are more important and even more related to their paper, which make the authors to miss the opportunity to use the proposed studies to better enhance the added value of paper and to better discuss the results in light of the existing studies.

Anyway, I don't want to push you further to make more changes.

Therefore I will accept it