The purpose of this repository is to analyze one research paper in the area of ML, Finance and Algorithmic Trading, and possibly improve strategies and models.
This is a personal project of mine, and meant only as a collection of ideas for keeping up with academic results.
Below is a list of current and future papers I'm planning to upload. Each subfolder is meant for one research paper and consists of a summary notebook.
This research paper combines technical analysis, k-line patterns and classification models to predict stock market trends. The authors reported an accuracy of around 60% with the help of an ensemble of KNN, SVM, GDB and RF.
My implementation on a different sample and time-frame achieved a 87% accuracy.
As a student, my work is purely theoretical, with no intention to profit from it. Every research paper is properly referenced in both the summary notebooks and in this file as well. Authors are given credit for their work, and my intent is only to receive inspiration from their work.
Lin, Yaohu & Lin, Shancun & Yang, Haijun & Wu, Harris. (2021). Stock Trend Prediction Using Candlestick Charting and Ensemble Machine Learning Techniques With a Novelty Feature Engineering Scheme. IEEE Access. 9. 101433-101446. 10.1109/ACCESS.2021.3096825.