that the divergence series can reveal subtle shifts in the stock's trend. Since the MACD is based on moving averages, it is a lagging indicator. As a future metric of price trends, the MACD is less useful for stocks that are not trending (trading in a range) or are trading with unpredictable price action. Hence the trends will already be completed or almost done by the time MACD shows the trend. Terminology Over the years, elements of the MACD have become known by multiple and often over-loaded terms. The common definitions of particularly overloaded terms are: Divergence: As the D in MACD, "divergence" refers to the two underlying moving averages drifting apart, while "convergence" refers to the two underlying moving averages coming towards each other. Gerald Appel referred to a "divergence" as the situation where the MACD line does not conform to the price movement, e.g. a price low is not accompanied by a low of the MACD. Thomas Asprey dubbed the difference between the MACD and its signal line the "divergence" series. In practice, definition number 2 above is often preferred. Histogram: Gerald Appel referred to bar graph plots of the basic MACD time series as "histogram". In Appel's Histogram the height of the bar corresponds to the MACD value for a particular point in time. The difference between the MACD and its Signal line is often plotted as a bar chart and called a "histogram". In practice, definition number 2 above is often preferred. Formula The formula for the MACD line is based on two exponential moving averages of the close prices, usually with the periods of 12 and 26: The signal line is then built as the exponential moving average of the MACD line: Mathematical interpretation In signal processing terms, the MACD series is a filtered measure of the derivative of the input (price) series with respect to time. (The derivative is called "velocity" in technical stock analysis.) MACD estimates the derivative as if it were calculated and then filtered by the two low-pass filters in tandem, multiplied by a "gain" equal to the difference in their time constants. It also can be seen to approximate the derivative as if it were calculated and then filtered by a single low pass exponential filter (EMA) with time constant equal to the sum of time constants of the two filters, multiplied by the same gain. So, for the standard