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Top 36 Moving Averages in Python: Jurik, McGinley, Ichimoku and More

DEV Community·Ayrat Murtazin·6 months ago
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#python#quant#trading#series#period
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Most traders default to simple or exponential moving averages and stop there. But the landscape of moving average design is far richer — engineers, statisticians, and professional traders have developed dozens of specialized smoothing techniques, each making a different tradeoff between lag, noise rejection, and responsiveness. Understanding these alternatives gives you a more complete toolkit for signal construction, trend filtering, and regime detection.

This article — the final part of a four-part series — covers eight niche but powerful moving averages: the Jurik Moving Average (JMA), End Point Moving Average (EPMA), Chande Moving Average (CMA), Harmonic Moving Average, McGinley Dynamic, Anchored Moving Average, Filtered Moving Average, and the Ichimoku Kijun-sen.…

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