YOLO-Based Detection of Buy and Sell Signals in Candlestick Charts with Moving Averages

• Marco Antonio Sousa Santos UTFPR
• Adriano Rivolli da Silva UTFPR
• André Roberto Ortoncelli UTFPR

DOI: https://doi.org/10.5753/eniac.2025.12471

Abstract

In stock trading, identifying trends is essential. Candlestick charts show price variations while moving averages help smooth these fluctuations and highlight trends. Some works focus on event detection in candlestick charts but without using moving averages. In this study, we investigate whether incorporating semantic information from moving averages into candlestick chart analysis can enhance the detection of buy and sell signals. The proposed approach includes image generation, data augmentation, labeling, and signal identification in short-term trading scenarios. We conducted experiments using four versions of YOLO (v3, v8, v9, and v11). Compared to previous work that did not use moving averages, our results were significantly better regarding F1-Score (up to 0.06 higher) and recall (up to 0.18 higher).

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