Forecasting Market Trends Using Time Series Analysis in Technology Industries

Abstract

Forecasting market trends in technology industries is increasingly critical in a rapidly evolving economic landscape. This manuscript explores the application of time series analysis to predict market trends in the technology sector. Through the integration of statistical models such as ARIMA, Exponential Smoothing, and Neural Network approaches, this study demonstrates how historical data can be used to forecast future market behaviors. The manuscript details the methodology, statistical analysis, and results, highlighting the benefits and limitations of time series forecasting techniques. It concludes with recommendations for both practitioners and researchers, as well as outlining potential avenues for future study.