What is a moving average?

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The whole variety of financial indicators could be split into three classes: Trend Following, Oscillators and Others. Trend Following indicators are effective when the market is moving in trend but become dangerous on stable market. Oscillators show firm market turning points and may send out untimely or false signals on moving market. Other indicators monitor the state of investors’ mass psych.

The most important Trend Following indicators are moving average, MACD (Moving Average Convergence/Divergence), MACD-histogram, Average Directional Index (ADX) and Accumulation/distribution index. All of them are lagging indicators – they change when the trend had already changed.

A moving average (MA), also called rolling average, is an average price movement indicator, showing average value of the data within specific time frame. It’s used to smooth out short-term fluctuations and highlight longer-term trends.

Likewise all other instruments a moving average has its own advantages and disadvantages. The weakest point is that it does not warn about upcoming change of the trend. The greatest advantage – it helps us to determine current movement of the trend and to confirm change when it actually happens.

Moving average levels are interpreted as resistance in a rising market, or support in a falling market. Here a support level means a price rank where the price tends to find “support” as it is going down. The price is more likely to “bounce” off this level rather than break through it. A resistance level is the opposite of a support level and is an upper extremum where the price tends to find resistance as it is going up.

Modern graphical analytic programs calculate wide range of different Moving Average types and offer assortment of their visualization styles. A time frame for calculation could be set as short, intermediate or long term. For long term trend the 200-days average is most popular; for medium term – 50-days average and for short term – 10 days average. Following types of rolling averages are used more often than others: a simple moving average (SMA); a weighted moving average (WMA) and an exponentially moving average (EMA).

Although a simple moving average (arithmetical average of unweighted prices for past periods) is most commonly used it can be disproportionately influenced by old data, embed in its calculation. In order to avoid that an extra weight is given to more recent data points coming to a weighted moving average. WMA is also more sensitive than SMA and is closer to price trend. In an exponentially moving average a coefficient is set to represent the degree of weighting decrease, a constant smoothing factor between 0 and 1. Then both recent data and EMA for previous period are weighted according to the chosen coefficient. By this means data for all preceding time periods is automatically included in the calculation but the recent prices still have more weight.

    General analysis of moving averages is founded on next key items

  • Determining crossing points of price and MA graphs;
  • Determining minimum and maximum of MA;
  • Detecting maximum dispersion between price and Moving Average;
  • Following a movement of a Moving Average

Usually two Moving Averages, build upon different time frames, are used for market trend analysis. Correlation between their lines could give essential information about trend’s strength. In strong upward trend, for example, short term moving average rise faster than long term and spread between the lines widens. If the spread starts to shrink this gives us early notice that upward trend is losing its momentum.

Because moving averages are trend following indicators, they are more useful on the trendy market. When the market is stable, the lags from the nature of moving averages smoothing generate false signals.