Using MACD Crossovers, Divergences, and Slope in Python
Summary
This tutorial explains the Moving Average Convergence Divergence indicator as the difference between a shorter and a longer exponential moving average, alongside a signal line formed from an exponential average of MACD. It demonstrates calculating and plotting the indicator with historical AMD prices. The discussion focuses on three readings: bullish and bearish crossovers, divergence between price swings and MACD swings, and unusually steep MACD movement as a possible sign that momentum may be tiring.
The examples are visual illustrations rather than a systematic test, and the article reports no quantified returns or signal accuracy. It cautions that divergences are not dependable as standalone direction signals and presents steep slopes as possible overbought or oversold conditions, not guarantees of reversals. The text also contains an inconsistent description of the moving-average periods in one passage, so readers should confirm the intended formula before implementing it.
Key ideas
- MACD is calculated as the difference between a shorter and a longer exponential moving average.
- A signal line is formed by smoothing MACD with another exponential moving average.
- Crossovers, price-MACD divergences, and steep slopes are presented as possible trading clues.
- The article’s charts are illustrative and do not establish profitability or signal reliability.
- Divergences and steep slopes should be treated as supporting context rather than certain reversal signals.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.