About this document
Neural Network Stock Trend Prediction by drahmedbader2 is a document available to read on EtoBox.
This study explores the combination of Neural Networks and Elliott Wave Theory to predict stock trends on the Indonesian Stock Exchange, demonstrating a profit rate exceeding 90%. The methodology involves preprocessing stock data, applying Fast Fourier Transform, and training a Neural Network model to identify patterns for investment decisions. The research aims to validate the effectiveness of this combined approach in stock trading, particularly for stocks listed in the LQ45 index.
- Author
- drahmedbader2
- Language
- EN