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license: mit |
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### Model Card for Telegram Trading Bot |
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#### Overview |
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- **Project Name:** Telegram Trading Bot |
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- **Purpose:** Predict stock market prices and generate trade signals |
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- **Platforms Supported:** TradingView, Forex, Coinbase, Binance, Yahoo Finance, Bloomberg |
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#### Model Details |
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- **Model Type:** Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) layers |
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- **Framework Used:** TensorFlow/Keras |
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- **Input Data:** Historical price data (open, high, low, close, volume) from various financial platforms |
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- **Output:** Predicted price and trade signal (Buy/Sell) |
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#### Data Sources |
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- **Binance:** Real-time cryptocurrency prices |
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- **Alpha Vantage:** Stock and Forex market data |
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- **Yahoo Finance:** Stock prices and financial data |
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- **TradingView:** Technical analysis and financial market data (Placeholder for future integration) |
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- **Bloomberg:** Financial data and news (Placeholder for future integration) |
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- **Coinbase:** Cryptocurrency prices (Placeholder for future integration) |
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#### Features |
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- ♦ **Real-time Data Acquisition:** |
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- Fetches latest market data from multiple platforms |
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- Supports diverse financial instruments including stocks, forex, and cryptocurrencies |
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- ♦ **Data Preprocessing:** |
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- Normalizes and scales data for model input |
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- Handles missing data and ensures consistency across datasets |
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- ♦ **Neural Network Model:** |
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- Utilizes LSTM layers to capture temporal dependencies in financial data |
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- Trained on historical price data to predict future prices |
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- ♦ **Trade Signal Generation:** |
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- Generates Buy/Sell signals based on predicted price trends |
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- Provides actionable insights for trading on platforms like Binomo |
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- ♦ **Integration with Telegram:** |
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- Responds to user commands for real-time trading signals |
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- Simple and interactive user interface through Telegram bot |
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#### Usage |
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- **Command: `/start`** |
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- Initializes the bot and provides basic instructions |
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- **Command: `/signal [pair]`** |
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- Generates and returns a trade signal for the specified currency pair (default: BTCUSDT) |
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#### Performance Metrics |
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- **Evaluation Metrics:** |
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- Mean Squared Error (MSE) for regression accuracy |
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- Accuracy of trade signals (Buy/Sell) compared to actual market movements |
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- **Training Data:** |
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- Historical price data from supported platforms |
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- **Validation:** |
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- Split historical data into training and validation sets |
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- Evaluate model performance on unseen validation data |
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#### Limitations and Future Work |
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- ♦ **Current Limitations:** |
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- Placeholder integrations for TradingView, Bloomberg, and Coinbase |
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- Model performance highly dependent on the quality and granularity of data |
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- Limited to hourly predictions; higher frequency data may be needed for intraday trading |
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- ♦ **Future Enhancements:** |
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- Complete integration with TradingView, Bloomberg, and Coinbase |
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- Experiment with different neural network architectures and hyperparameters |
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- Incorporate additional features such as sentiment analysis from news and social media |
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#### Ethical Considerations |
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- **User Discretion:** |
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- The bot provides trade signals but users should exercise caution and perform their own analysis before making trading decisions. |
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- **Data Privacy:** |
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- Ensure secure handling of API keys and user data. |
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- **Financial Risk:** |
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- Trading involves financial risk; users should understand the risks involved and use the bot responsibly. |
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This model card provides a comprehensive overview of the Telegram Trading Bot, highlighting its capabilities, data sources, features, and considerations for future development. |
