# Ascertaining price formation in cryptocurrency markets with DeepLearning

arXiv: https://arxiv.org/abs/2003.00803 · HTML: https://mlsanity.com/paper/2003.00803/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Feb 2020.

## Built on by (most cited first, 1 of 1)

- [Denoised Labels for Financial Time-Series Data via Self-Supervised Learning](https://mlsanity.com/paper/2112.10139/) (2021)

## Abstract (arXiv)

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.