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---
license: mit
language: en
---
# Bitcoin Price Prediction Dataset (60d History -> 4d Forecast)
This dataset is designed for fine-tuning Large Language Models (LLMs) on a time-series forecasting task. Each sample contains 60 days of historical financial and social media data to predict the next 4 days of Bitcoin's closing price.
## Dataset Description
The dataset was generated by combining two primary sources:
1. **Financial Data:** Historical daily prices for Bitcoin (BTC), Gold (GC=F), Crude Oil (CL=F), S&P 500 (^GSPC), and the US Dollar Index (DX-Y.NYB) were fetched from Yahoo Finance.
2. **Social Media Data:** The [Bitcoin Tweets Dataset](https://www.kaggle.com/datasets/kaushiksuresh147/bitcoin-tweets) was used to extract daily tweet volume and sample tweet texts.
### Features Included in the Prompt:
- **60-Day Historical BTC Prices**: The core time-series data.
- **Technical Indicators**: 14-day RSI, 50-day EMA, and 200-day EMA for Bitcoin.
- **Macroeconomic Context**: Daily closing prices of Gold, Oil, S&P 500, and the US Dollar Index.
- **Social Media Sentiment**: A sample of 4 tweets for the most recent day in the historical window.
## Data Fields
The dataset is structured for instruction fine-tuning and contains three columns:
- `instruction`: A string containing the comma-separated closing prices of Bitcoin for the last 60 days.
- `input`: A detailed text block containing all the contextual information (technical indicators, macro data, sample tweets) for the most recent day of the historical period.
- `output`: A string containing the comma-separated closing prices of Bitcoin for the next 4 days (the prediction target).
## Splits
- **train**: The training split (`train_dataset.json`).
- **test**: The validation/test split (`val_dataset.json`).
## Intended Use
This dataset is intended to be used with the `SFTTrainer` from the TRL library or similar frameworks to fine-tune models like Llama 3 for complex, multi-modal time-series forecasting tasks.
Example prompt structure:
```json
{{
"instruction": "45123.45, 45321.89, ... (60 days of prices)",
"input": "Based on the historical data from the last 60 days, predict the Bitcoin closing prices for the next 4 days. The prediction period starts on 2023-11-20 (Weekday). The most recent day's technical analysis (2023-11-19): ...",
"output": "46123.78, 46050.12, 46300.50, 45987.32"
}}
```
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