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In the intricate landscape of Indonesia’s financial sector, the pronounced stock price volatility stands out as a topic of pressing concern. This volatility, often perceived as a hallmark of emerging markets, manifests distinctly in the Indonesian context. This paper uses the UMA (Unusual Market Activity) as a primary reference point to unravel the patterns underlying stock-price manipulations. Benchmarked against the IDX80 and LQ45 indexes, our exploration reveals overarching trends in the behavior of potentially manipulated stocks. To refine our analysis further, we incorporated machine learning tools, including a Support Vector Machine (SVM) and a Random Forest classifier, as supportive instruments. Our study offers a panoramic view of Indonesia’s stock market dynamics, shedding light on areas that warrant regulatory attention and paving the way for informed decision-making for investors and market stakeholders. G1, G4, G12, G14.
Sergi et al. (Fri,) studied this question.
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