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The paper studies intraday price movement of stocks that is considered as animage classification problem. Using a CNN-based model we make a compelling casefor the high-level relationship between the first hour of trading and theclose. The algorithm managed to adequately separate between the two opposingclasses and investing according to the algorithm's predictions outperformed allalternative constructs but the theoretical maximum. To support the thesis, weran several additional tests. The findings in the paper highlight thesuitability of computer vision techniques for studying financial markets and inparticular prediction of stock price movements.

Predicting Stock Price Movement as an Image Classification Problem