Various methods to predict stock prices have been studied. In a linked paper, we propose a stock price prediction method that applies DTW on scaled daily stock price patterns. We showed its performance using TOPIX data. In this paper, we further analyze the effectiveness of the proposed method using other price indexes, such as the S&P 500, CAC40, DAX, FTSE100, foreign exchange rates, and Cryptocurrency. This paper also reports the importance of pattern length and starting points of patterns. We also discuss the hidden behavior of investors which seems to explain the prediction ability of the proposed method.
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