Ascertaining price formation in cryptocurrency markets with DeepLearning
This addresses price formation for cryptocurrency traders, but it is incremental as it applies existing deep learning methods to a new market.
The paper tackled the problem of predicting mid-price movements in high-frequency cryptocurrency markets using deep learning, achieving a consistent 78% accuracy on Bitcoin vs US dollars exchange rate predictions.
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. Unlike traditional markets, such as equities, foreign exchange and commodities, cryptocurrency market is considered to have larger volatility and illiquidity. This paper is inspired by the recent success of using deep learning for stock market prediction. In this work, we analyze and present the characteristics of the cryptocurrency market in a high-frequency setting. In particular, we applied a deep learning approach to predict the direction of the mid-price changes on the upcoming tick. We monitored live tick-level data from $8$ cryptocurrency pairs and applied both statistical and machine learning techniques to provide a live prediction. We reveal that promising results are possible for cryptocurrencies, and in particular, we achieve a consistent $78\%$ accuracy on the prediction of the mid-price movement on live exchange rate of Bitcoins vs US dollars.