/Xauud_model

Primary LanguagePython

LSTM Model for XAU/USD Price Prediction

This repository contains a Long Short-Term Memory (LSTM) model for predicting the XAU/USD (Gold to US Dollar) price. The model is designed to analyze historical price data and provide forecasts for future price movements.

Overview

  • Model Architecture: This LSTM model utilizes recurrent neural networks (RNNs) to capture temporal dependencies in the price data, making it well-suited for time series forecasting.

  • Dataset: The model is trained on historical XAU/USD price data, which is included in the data directory of this repository.

  • Evaluation: We assess the model's performance using various evaluation metrics, such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE).

Installation

To use this LSTM model, follow these steps:

  1. Clone the repository:
git clone https://github.com/Bytebeem/Xauud_model.git
cd Xauud_model

pip install -r requirements.txt

## Usage
To train the LSTM model and make predictions, you can run the following command:

python live_trading.py

## Evaluation
To assess the model's performance, we calculate the following metrics:

Mean Absolute Error (MAE)
Mean Squared Error (MSE)
Root Mean Squared Error (RMSE)