Predicting Stock Prices using ARIMA, Fourier Transforms, and Technical Indicators with Deep Learning: A Comprehensive Guide

In this article, we will explore the use of ARIMA and Fourier Transforms as features in a deep learning model for financial prediction.

ARIMA (AutoRegressive Integrated Moving Average) is a widely used time-series analysis technique that can help predict future values based on past performance. Fourier Transforms, on the other hand, are a mathematical technique that can be used to analyze time-series data by breaking it down into its component parts, including different frequencies.

With the use of powerful techniques like ARIMA and Fourier Transforms, combined with popular technical indicators, we can make accurate predictions and gain a competitive edge in the dynamic world of finance.

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