Trading Model

Overview

This project implements a trading model that fetches historical data from the Binance API, calculates key metrics, trains linear regression models for price prediction, and saves the results to Google Sheets.

Features

@ Data Retrieval: Fetch daily candlestick data for multiple cryptocurrency pairs.
@ Metric Calculation: Calculate important metrics such as highs, lows, and percentage differences.
@ Model Training: Train linear regression models to predict future price movements.
@ Google Sheets Integration: Save calculated data and model results directly to Google Sheets for easy access and sharing.

Prerequisites

@ Python 3.7 or later
@ Required Python packages:

• pandas
• requests
• gspread
• scikit-learn
• joblib

You can install the required packages using pip:

pip install pandas requests gspread scikit-learn joblib

Setup Instructions

1. Clone the Repository

@ Clone the repository to your local machine:

git clone https://github.com/yourusername/crypto-trading-model.git
cd crypto-trading-model

2. Create Google Sheets API Credentials

@ Follow these steps to create your Google Sheets API credentials:

Go to the Google Cloud Console. Create a new project. Enable the Google Sheets API. Create credentials (Service Account). Download the JSON file containing your credentials and save it in the project directory.

3. Modify the Code

@ Update the DataUsingBinance.py with your desired cryptocurrency pairs and the start date for data fetching. @ In trainModel.py, configure the paths for saving the model and loading data from Google Sheets.

4. Run the Scripts

@ To fetch data and calculate metrics, run the following command:

python DataUsingBinance.py

@ To train the models, execute:

python trainModel.py

@ To make predictions (this part needs to be completed in prediction.py), run:

python prediction.py

Usage

@ DataUsingBinance.py: This script fetches data from Binance, calculates metrics, and saves the data to Google Sheets. @ trainModel.py: This script loads the data from Google Sheets, trains linear regression models, and saves the models. @ prediction.py: This script (to be completed) will fetch new data, load trained models, and make predictions.

Contributing

@ Feel free to fork the repository, make changes, and submit a pull request. Contributions are welcome!

License @ This project is licensed under the MIT License.

Acknowledgments @ Binance API Documentation @ Google Sheets API Documentation