Abstract
In this paper, we come up with an original trading strategy on Bitcoins. The methodology we propose is profit-oriented, and it is based on buying or selling the so-called Contracts for Difference, so that the investor’s gain, assessed at a given future time t, is obtained as the difference between the predicted Bitcoin price and an apt threshold. Starting from some empirical findings, and passing through the specification of a suitable theoretical model for the Bitcoin price process, we are able to provide possible investment scenarios, thanks to the use of a Recurrent Neural Network with a Long Short-Term Memory for predicting purposes.
Highlights
For last decades, cryptocurrencies have been increasingly playing a leading role in the worldwide economic and financial scenario
The aforementioned moving average (MA) is the key tool for another type of trading strategies. Such Moving Average trading rules slightly differ from the techniques previously introduced, as they directly look at the traded asset prices, without resorting to any momentum indicator, and the signal line coincides with the MA considered
We can set up the strategy, by taking into account a given number of suitable financial instruments that provide profit in terms of the spread between the underlying value and the optimal frontier of a synthetic American-style derivative
Summary
Cryptocurrencies have been increasingly playing a leading role in the worldwide economic and financial scenario. The research lines dedicated to the explanation of cryptocurrencies’ pricing through behavioral economics is becoming increasingly popular, especially thanks to social networks, see e.g., Kim et al (2016) Within such a broad literature, the present paper aims at enriching the recent strand of the literature that studies technical trading rules in cryptocurrency markets, see e.g., Detzel et al (2018), Hudson and Urquhart (2019), Vo and Yost-Bremm (2018), Cohen (2020), using statistical techniques of supervised learning for estimation and inference. To the best of our knowledge, this occurs for the first time in the literature Such a comparison shows once again the potential of our proposal: the technical analysis performed highlights that our strategy is comparable with the others in terms of returns, but is more conservative, as it guarantees significantly lower losses.
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