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Bitcoin is a decentralized digital currency, without a central bank or single administrator, that can be sent from user to user on the peer-to-peer bitcoin network without the need for intermediaries. Transactions are verified by network nodes through cryptography and recorded in a public distributed ledger called a blockchain. Bitcoin is unique in that there are a finite number of them.
Invented in 2008, Bitcoin now has become a popular financial instrument for speculation. There exist, however, very few approaches for trading it systematically. To develop a profitable quantitative trading strategy for Bitcoin, one has to understand and model the dynamics of the underlying.
Reference [1] explored a systematic approach to Bitcoin trading,
The objective of this thesis was to research mean reversion and momentum trading strategies performance on short timeframe Bitcoin trading. The aim is to find out if there are any notable performance differences between these strategies. This study finds the most optimal parameter set ups for moving average cross overs and Bollinger band strategies and then compares them to a simple buy-and-hold strategy.
It concluded that it’s very difficult to develop a systematic trading approach for Bitcoin that beats buy and hold,
The main finding of this study is that buy-and-hold strategy is very challenging to win by using momentum or mean reversion strategies. Although difficult, it is not impossible to generate larger annual returns with short time frame trading. Some momentum strategies were able to generate larger annual returns than buy-and-hold strategy, but the results were not consistent when different data subset were used. None of the mean reversion strategies on the other hand were able to win buy-and hold strategy on short time frame trading based on annual returns. Sharpe ratio and maximum draw down values were better with both momentum and mean reversion strategies compared to buy-and-hold strategy on training set, but these results could not be repeated with different data subset, except for Sharpe ratios on momentum strategies.
We found some merits in the research methodology. We observed, however, that the trading system universe examined in this paper is rather small. Only simple moving average cross-over and Bollinger band systems were investigated. Therefore the results are rather weak.
Let us know what you think in the comment below.
References
[1] Merituuli Jääskeläinen, Momentum and mean reversion trading strategy comparison and parameter tuning on short timeframe Bitcoin trading between years 2016 and 2021, 2022, Lappeenranta–Lahti University of Technology LUT
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