Time Series Trend Analysis Based on K-Means and Support Vector Machine

keywords: Machine learning, time series trend analysis, support vector machines, k-means clustering
In this paper, we apply both supervised and unsupervised machine learning techniques to predict the trend of financial time series based on trading rules. These techniques are K-means for clustering the similar group of data and support vector machine for training and testing historical data to perform a one-day-ahead trend prediction. To evaluate the method, we compare the proposed method with traditional back-propagation neural network and a standalone support vector machine. In addition, to implement this combination method, we use the financial time series data obtained from Yahoo Finance website and the experimental results also validate the effectiveness of the method.
mathematics subject classification 2000: 68-T05
reference: Vol. 35, 2016, No. 1, pp. 111–127