---
title: Deep Learning for High-Frequency Cryptocurrency Trend Detection: Incorporating Technical Indicators and A New Approach For Data Stationarity
url: https://www.ml-quant.com/papers/ssrn/4796336/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4796336
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4796336
featured: 2024-04-17
citations: 1
topic: Crypto & DeFi
---


# Deep Learning for High-Frequency Cryptocurrency Trend Detection: Incorporating Technical Indicators and A New Approach For Data Stationarity

The research presents a new data preprocessing technique and a Convolutional Neural Networks (CNN) model for predicting Bitcoin market trends using 15-minute candlestick data.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4796336
- Identifier: SSRN 4796336
- Released: 2024-04-16
- First featured: Quant Letter No. 45 (2024-04-17): https://www.ml-quant.com/issues/2024-04-17/
- Citations (Semantic Scholar): 1
- Published in: not yet
- Topic: Crypto & DeFi

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