Stock recommendation methods for stability

In this study, we propose a method for recommending appropriate combinations of stocks based on the waveforms of stock price changes. Many Japanese prefer to maintain stability when managing their assets. Specialized knowledge is required to invest in stocks while reducing risk. Hence, stock recommendation methods with different characteristics are required. Stock price movements can be captured as waveforms. Dynamic time warping (DTW), cross–correlation functions, and fast Fourier transforms (FFTs) are used to compare the features of the waveforms. A combination of stocks with different waveforms avoids the risk of simultaneous crashes. In the current experiment, one–year stock waveforms are used to obtain the recommended stock. The combined stocks selected using the DTW, cross–correlation functions, and FFT are shown to be suitable.