As a quant-focused strategist, I treat the stock market like a buggy codebase. Sometimes the UI (Price) shows one thing, but the backend logs (Volume) show an error.
Today (Dec 17) was a perfect example of a Data Anomaly in the Indonesian Market (IHSG).
The Algorithm:
Input A (Price): Index breaks resistance > 8,700.
Input B (Volume): Volume < Moving Average (25B vs 43B prior).
Logic: If Price_Delta > 0 AND Volume_Delta < -30% THEN Signal = False_Breakout.
The Execution: Most retail traders only look at Input A. They bought the breakout. My system flagged the anomaly in Input B.
The Bug: The tech stock GOTO showed a +3% rise yesterday. Today, the data showed a lack of buy-side liquidity, causing a -2.9% drop.
The Patch: The system routed capital to BBRI (Banking), which showed high relative strength (+1.3%) and stable volume.
Conclusion: Data visualization saves capital. Today's chart looked bullish, but the underlying data structure was empty. Always check your volume arrays before committing to production (trading).
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