[4E3-GS-2] Machine learning

[4E3-GS-2-02] Time Series Clustering Using Technical Indicators

〇Yoshiki Nakagawa¹, Tohgoroh Matsui², Koichi Moriyama¹, Kosuke Shima¹, Atsuko Mutoh¹, Nobuhiro Inuduka¹ (1. Nagoya Institute of Technology, 2. Chubu University)

Keywords:Clustering, Time series data, Machine learning

In this paper, we propose a method for clustering time-series data using technical indicators. Although a method for clustering companies by industry has been proposed for time-series stock price data, the clustering was performed on time-series data as independent features at each time, and the time-series nature of the data was not taken into account. The method proposed in this paper takes into account the time-series nature of the data, calculates technical indicators from the time-series data, and performs clustering using these indicators as features. By using technical indicators as features, clustering can be expected to take into account the time-series nature of the data. The proposed method is applied to actual stock price data and ECG data to confirm its effectiveness.