Exploring time series stock market forecasting with CPI, PPI and Nonfarm data

Abstract

This capstone study explores the interaction between macroeconomic variables and the United State Stock Market Index. It considers monthly time series data of the Consumer Price Index, Producer Price Index, and Non-Farm data(Employment, Unemployment, and Unemployment Ratio) from 2000 to 2022, and it attempts to discover the relationship of these variables on Standard & Poor’s 400/500/600 stock index. This study uses methodologies such as OLS Analysis, Polynomial Linear Regression, Auto-ARIMA, and Facebook Prophet models to research the long-term relationship between five macroeconomic variables and the market index. The crucial finding is that macroeconomic variables do have an impact on the United State Stock Index. In addition, when analyzing the publicly listed companies’ quarter financial statements, individual investors should also consider macroeconomic variables released by the government.