US-GDP-Forecasting

Forecast quarterly GDP values in the US using various time series models. Evaluated models using MAPE and RMSE. Auto ARIMA model provided best fit. Predicted future GDP values for next 4 quarters. This repository contains a comprehensive analysis and forecasting of the quarterly Gross Domestic Product (GDP) of the United States from 2003 to 2022. The project report includes data preprocessing, exploration, visualization, and the implementation of various time series models such as ARIMA, Holt-Winters, Auto-regressive, and Moving Average. The goal of the project was to build an accurate model for predicting future GDP values based on historical trends. The repository serves as a resource for understanding and implementing time series analytics for economic forecasting. This repository contains code for forecasting quarterly GDP values in the United States using various time series models. The models were evaluated using the mean absolute percentage error (MAPE) and root mean squared error (RMSE). The results indicated that the Auto ARIMA model provided the best fit for the data. The model was then used to predict future GDP values for the next four quarters, and the results were found to be within a reasonable range of accuracy.