Recently, while looking into stock technical indicators, I found that many people don’t fully understand the divergence rate tool. In fact, it’s one of the most straightforward indicators for judging overbought and oversold conditions.

Put simply, the divergence rate measures how far the stock price deviates from the moving average. When the stock price rises too fast and moves too far away from the moving average, the probability of a pullback increases; conversely, when it falls too much, the opportunity for a rebound appears. This logic is actually quite simple—just like water flowing downhill; when prices move to extremes, they naturally swing back to adjust.

The calculation is not complicated either: subtract the N-day moving average from the day’s closing price, then divide by the moving average to get the divergence rate percentage. When the stock price is above the moving average, it is called a positive divergence rate; when it is below, it is a negative divergence rate.

When setting a divergence rate, first you need to choose an appropriate moving average period. For short-term trading, people usually look at the 5, 10, and 12-day lines; for medium-term, the 20 and 60-day lines; and long-term investors can use the 120 and 240-day lines. Then choose parameters based on your own trading style—common ones are 6, 12, and 24 days. For highly active stocks, using short-cycle divergence rates makes the indicator more sensitive and faster in response; longer cycles are smoother and better suited for trend judgment.

How do you use the divergence rate to find buy and sell points? A key part is setting positive and negative thresholds. For example, a 5-day divergence rate can be set around 2–3%, but this number should be adjusted based on market volatility and historical data. When the divergence rate exceeds the positive threshold, it indicates overbought conditions, and you may consider selling; when it falls below the negative threshold, it indicates oversold conditions, and you may consider buying.

My own approach is to look at the divergence rates of multiple moving averages together—such as observing both the 5-day and 20-day moving average lines—so you can understand short-term and medium-term market trends more comprehensively. Another very important technique is to watch for divergence. If the stock price hits a new high but the divergence rate does not make a new high, that is usually a top signal; on the other hand, if the stock makes a new low but the divergence rate does not make a new low, that may be a bottom signal.

However, divergence rate also has limitations, and you need to pay attention to them. First, if the chosen stock has been moving sideways for the long term or has very small volatility, the effectiveness of the divergence rate will be greatly reduced. Second, divergence rate has a lag, so it’s not recommended to rely on it alone when selling; for buying, you can use it as a reference. Also, for stocks with different market capitalizations, the accuracy of the divergence rate will differ—large-cap stocks are generally more stable and easier to judge, while small-cap stocks are more volatile, making it harder to use this indicator effectively.

In actual trading, I suggest you shouldn’t look only at the divergence rate. It’s best to combine it with other indicators as well, such as the KD stochastic indicator or Bollinger Bands. Combining divergence rate with KD can make rebound trading more timely, and pairing it with Bollinger Bands is better suited to identifying oversold rebound buying opportunities. Parameter selection is also crucial: too short can make it overly sensitive, while too long can make it respond too slowly—so you need to adjust it based on your trading style.

The last point is to use the divergence rate flexibly. When good-company stocks fall, they rebound quickly because everyone is afraid of missing the chance to buy cheap; when bad-company stocks fall, their rebounds are much slower. So, the divergence rate is just a tool—you still need to combine it with fundamentals and market sentiment to make better judgments, and you shouldn’t treat it as a purely formula-based method.