ML Based Macroeconomic Model Simulator

Abstract - This AutoFi, a cutting-edge AI-driven macroeconomic simulation model, provides a robust framework for forecasting financial markets. Financial markets are deeply influenced by macroeconomic indicators such as GDP, unemployment rates, inflation, and interest rates. Accurate forecasting of these indicators is critical for optimizing investment strategies. This research presents AutoFi, a machine learning-based macroeconomic simulation model that predicts key financial indicators and asset performance over time. The proposed system incorporates historical macroeconomic data, time series forecasting models, and regression-based asset prediction to estimate the future value of investments. Additionally, an interactive financial assistant provides investment insights, enhancing accessibility and decision-making. The system enables investors to input their capital allocation preferences across different asset classes and receive projected portfolio values. The results demonstrate the potential of AI-driven economic modeling to improve financial decision-making and risk assessment. Key Words: Macroeconomic forecasting, financial markets, AI-driven investment, AutoFi, machine learning, economic simulation, portfolio management, asset performance prediction