Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders
Not on the map. Why?
Abstract (arXiv)
In this paper, we study the ability to make the short-term prediction of the exchange price fluctuations towards the United States dollar for the Bitcoin market. We use the data of realized volatility collected from one of the largest Bitcoin digital trading offices in 2016 and 2017 as well as order information. Experiments are performed to evaluate a variety of statistical and machine learning approaches.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Feb 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 1; 2025: 1.
6 papers.
- 2021Ask "Who", Not "What": Bitcoin Volatility Forecasting with Twitter Datacited by 4
- 2024Review of deep learning models for crypto price prediction: implementation and evaluationcited by 2
- 2025MountainLion: A Multi-Modal LLM-Based Agent System for Interpretable and Adaptive Financial Tradingcited by 2
- 2023TCGAN: Convolutional Generative Adversarial Network for Time Series Classification and Clusteringcited by 0
- 2023A Spatiotemporal Deep Neural Network for Fine-Grained Multi-Horizon Wind Predictioncited by 0
- 2023A Data-driven Deep Learning Approach for Bitcoin Price Forecastingcited by 0
- 2025MountainLion: A Multi-Modal LLM-Based Agent System for Interpretable and Adaptive Financial Trading13 Jul 2025
- 2024Review of deep learning models for crypto price prediction: implementation and evaluation19 May 2024
- 2023A Data-driven Deep Learning Approach for Bitcoin Price Forecasting27 Oct 2023
- 2023A Spatiotemporal Deep Neural Network for Fine-Grained Multi-Horizon Wind Prediction9 Sep 2023
- 2023TCGAN: Convolutional Generative Adversarial Network for Time Series Classification and Clustering9 Sep 2023
- 2021Ask "Who", Not "What": Bitcoin Volatility Forecasting with Twitter Data27 Oct 2021