BTC Dump - Professional Bitcoin Price Prediction Tool

A professional-grade Bitcoin price prediction tool using ensemble machine learning models (XGBoost, Random Forest, and Gradient Boosting) with technical analysis indicators.

Features

• Ensemble ML Models: Combines XGBoost, Random Forest, and Gradient Boosting for robust predictions
• Technical Analysis: RSI, MACD, Bollinger Bands, Moving Averages
• Real-time Data: Fetches live BTC/USDT data from Binance API
• Multiple Timeframes: 5min, 30min, 1h, 4h, 1d
• Live Auto Mode: Continuous prediction with customizable refresh intervals
• Visualization: Interactive price charts with technical indicators
• Signal Generation: STRONG BUY/BUY/SELL/STRONG SELL/HOLD signals

Installation

# Clone the repository
git clone https://github.com/codingcreatively/BTCDump.git
cd BTCDump

# Install required dependencies
active venv
pip install -r requirements.txt

Basic Usage

Run the tool:

python3 BTCDump.py

Menu Options

1. Select Timeframe - Choose prediction interval (5min to 1day)
2. Train & Predict - Fetch data, train models, and get prediction
3. Show Live Chart - Display price chart with technical indicators
4. Refresh Data Only - Update market data without retraining
5. Show Last Prediction - Display previous analysis results
6. Auto Live Mode - Continuous predictions with custom refresh interval

Technical Analysis Indicators

The tool calculates the following technical indicators:

• Moving Averages: MA5, MA20, MA50
• Relative Strength Index (RSI): 14-period RSI
• MACD: 12/26 EMA with 9-period signal line
• Bollinger Bands: 20-period SMA with 2 standard deviations
• Volume Analysis: Volume SMA and ratio

Machine Learning Models

The tool uses a weighted average of three models:

1. XGBoost Regressor

   • n_estimators: 200
   • learning_rate: 0.05
   • max_depth: 6

2. Random Forest Regressor

   • n_estimators: 200
   • max_depth: 10
   • min_samples_split: 5

3. Gradient Boosting Regressor

   • n_estimators: 200
   • learning_rate: 0.05
   • max_depth: 5

Features Used for Prediction

• Current price and volume
• RSI, MACD values
• Moving averages (MA5, MA20, MA50)
• Bollinger Band positions
• Volume ratios

Signal Generation Logic

| Condition | Signal | |-----------|--------| | Change > 1.5% AND RSI < 70 AND MACD > Signal AND Price > MA20 | STRONG BUY | | Change > 0.5% AND RSI < 65 AND MACD > Signal | BUY | | Change < -1.5% AND RSI > 30 AND MACD < Signal AND Price < MA20 | STRONG SELL | | Change < -0.5% AND RSI > 35 AND MACD < Signal | SELL | | Otherwise | HOLD |

Configuration

Binance API

The tool uses Binance's public API endpoint:

https://api.binance.com/api/v3/klines

No API key required for public market data.

Timeframe Options

| Option | Timeframe | Description | |--------|-----------|-------------| | 1 | 5m | 5 Minutes | | 2 | 30m | 30 Minutes | | 3 | 1h | 1 Hour | | 4 | 4h | 4 Hours | | 5 | 1d | 1 Day |

Output Example

╔════════════════════════════════════════════════════════════════════╗
║  TOOL      : DUMP BTC                                              ║
║  AUTHOR    : alexxx                                                ║
║  INSTAGRAM : arcane.__01                                           ║
╚════════════════════════════════════════════════════════════════════╝

BTC ANALYSIS
======================================================================
Current Price:  $43,250.00
AI Prediction:  $44,100.00
Change:         +1.97%
RSI:            58.3
Signal:         STRONG BUY
Model Error:    2.34%
Timeframe:      1h
Last Update:    2026-03-19 14:30:00
======================================================================

Architecture

BTCPredictorPro
├── fetch_data()      → Get BTC/USDT data from Binance
├── indicators()      → Calculate technical indicators
├── features()        → Create feature matrix
├── train()           → Train ensemble models
├── predict()         → Generate price prediction
├── signal()          → Generate trading signal
├── chart()           → Display price chart
├── auto_live()       → Continuous predictions
└── main_menu()       → User interface

Performance Notes

• Model Error: Typically 1-3% MAPE on test data
• Training Time: ~10-30 seconds per model
• Prediction Speed: <1 second per prediction
• Data Requirements: Minimum 100 candles for training

Disclaimer

⚠️ This tool is for educational and research purposes only.

• Cryptocurrency trading involves significant risk
• Past performance does not guarantee future results
• Do not use this tool for actual trading decisions
• The author assumes no liability for financial losses

Author

• GitHub: @codingcreatively
• Instagram: @arcane.__01

Acknowledgments

• Binance API for real-time market data
• Scikit-learn, XGBoost, and Pandas communities
• Technical analysis principles from traditional finance

How to use? Tutorial Video

Coming Soon

Join Now

Yotutuhe:- https://youtube.com/@cyberarcane8?si=ufFzu1ubtIzTrbHZ

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