# Predicting Stock Price Movement as an Image Classification Problem

Source: [Predicting Stock Price Movement as an Image Classification Problem](<https://www.sota2.com/research/paper/68fa7acb1e209131cea8520a>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T05:26:48.092Z

Authors: Matej Steinbacher

Published: 2023-03-02T09:47:14.000Z

## Abstract

The paper studies intraday price movement of stocks that is considered as an image classification problem. Using a CNN-based model we make a compelling case for the high-level relationship between the first hour of trading and the close. The algorithm managed to adequately separate between the two opposing classes and investing according to the algorithm's predictions outperformed all alternative constructs but the theoretical maximum. To support the thesis, we ran several additional tests. The findings in the paper highlight the suitability of computer vision techniques for studying financial markets and in particular prediction of stock price movements.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2303.01111>)

[PDF](<https://arxiv.org/pdf/2303.01111.pdf>)