Comprehensive Analysis of FUTCOM and NASDAQ Commodities for Gold using Machine Learning and Technical Analysis

This paper covers commodity stock market (FUTCOM and NASDAQ) data using machine learning and technical analysis. Commodity stock markets play a crucial role in global economies, affecting everything from raw material prices to consumer goods. Their inherent volatility and sensitivity to geopolitical and economic factors make them challenging to predict. Addressing the prime problem of price fluctuations, this research highlights the need for accurate forecasting models, where machine learning can significantly enhance decision-making and risk management. It includes data preprocessing, RNN model creation, future price prediction, descriptive stats, correlation analysis, volatility, trend analysis, seasonality, volume analysis, and Monte Carlo simulation. Using Pandas, NumPy, TensorFlow, and Plotly libraries, it provides insights into market trends and forecasting. Results are intended for market participants and decision-makers,