Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (5.7%) to scientific vocabulary
Repository
Research project 6620
Basic Info
- Host: GitHub
- Owner: am2fq
- License: mit
- Language: Python
- Default Branch: main
- Size: 113 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
BitcoinForecasting
Research project 6620
Abstract
Bitcoin is known for its high volatility, which makes it challenging to accurately predict future prices. In this study, we aim to forecast Bitcoin prices for a month by incorporating exogenous variables, specifically the interest rate and recession probability. Our primary objective is to explore whether these variables have a positive impact on the prediction of Bitcoin prices. We used two popular time series forecasting models: Long Short-Term Memory (LSTM) and Facebook Prophet. Our approach involves exploring the impact of these exogenous variables on the performance of the models and comparing their results through plots and cross-validation. We trained the models using historical Bitcoin price data along with exogenous variables and evaluated their performance on a test dataset. Our results indicate that LSTM outperforms Facebook Prophet in terms of Bitcoin price prediction accuracy. This is because, while Facebook Prophet is optimized for statistical forecasting modeling, LSTM has the capability to learn intricate patterns and relationships given the right architecture with sufficient neurons. Importantly, we demonstrate that incorporating interest rates and recession probabilities significantly enhances the predictive capability of our models. Our findings suggest that changes in interest rates and recession probabilities have an impact on Bitcoin prices, and our models perform better when equipped with this valuable information.
Owner
- Name: Adel Mahfooz
- Login: am2fq
- Kind: user
- Location: USA
- Website: https://adelmahfooz.wixsite.com/mysite
- Repositories: 1
- Profile: https://github.com/am2fq
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Mahfooz" given-names: "Adel" orcid: "https://orcid.org/0000-0000-0000-0000" title: "BitcoinForecasting" version: 1.0.0 doi: 10.5281/zenodo.1234 date-released: 2023-04-18 url: "https://github.com/am2fq/BitcoinForecasting"