Larger periods apply more weighting to past bars, while smaller periods apply more weighting to the current bar (and therefore make the indicator more responsive). The EMA period is really less of a "period" and more of a conversion factor used in determining the weighting factor or the current bar. In a comparable SMA with a period of 7, the current bar and the previous 6 bars all get an equal weighting factor or approximately 14.3% and the bars preceding these 7 bars aren't considered at all. The previous value of EMA is built using each of the previous bars (or prices) to some degree. So the current bar will be weighted 25% while the previous value of EMA (EMA.1) will be weighted 75%. For example, if you choose an EMA period of 7, then the current bar is going to get a weighting factor of 2/(n+1) or 2/(7+1) in our case, which is 0.25. It is similar to other moving averages however in that the smaller the period, the more responsive the MA will be, as the most recent bar will have a greater effect.ĮMAs place more weight on recent prices than other moving averages such as SMA. The calculation method used by exponential averages is cumulative, meaning that all previous bars have some effect on the EMA value, although that effect diminishes greatly with time. Simple MA's have a memory of only the last X bars (X being the period).Įxponential Moving Average (EMA) - Exponential averages address two problems that are experienced with Simple Moving Averages: SMAs give equal weight to each price in the period, and SMAs change twice with every new bar (new price added while old price is dropped). Each time you add a new price point to the simple MA, you drop the oldest price point. The SMA value at each bar will be computed by taking the close of that bar, and the close of the previous 9 (Period - 1) bars, adding them together, and then dividing by 10 (Period), to get the average. Let's assume we are considering a 10-period simple average of the close. The Simple method gives equal weighting to each price point over the period considered. Simple Moving Average (SMA) - This is probably the most commonly used smoothing type.
Below we'll take a closer look at these 5 averaging methods. The five pre-existing moving averages are Simple, Weighted, Exponential, Welles Wilder, and Least Square.
For example, the Adaptive moving average could be used to smooth the CCI, RSI, or MACD indicator. These new moving averages may be used as overlay indicators showing the moving average of some price type for an instrument, or they may be used as smoothing options in conjunction with other technical indicators. Sine-Weighted Average - The sine-weighted moving average is similar in concept to the triangle moving average, but the weighting factors are based on a sine calculation instead. Endpoint Moving Average - The endpoint moving average uses a least squares (linear regression) fit to derive each point on the moving average line based on the preceding period. For example, for a 7 period moving average, the weighting factors are 1, 2, 3, 4, 3, 2, 1. Triangular Moving Average - The triangular moving average derives its name from the way the weighting factors are applied to the un smoothed data. 18.Īdaptive Moving Average - This moving average moves slowly when prices are moving sideways and moves swiftly when prices move swiftly. 34 of the 1998 Bonus Issue of Stocks and Commodities Magazine, while the other 3 moving averages are described in detail in the June 1999, p. The Adaptive Moving Average is described in detail on p. Four new moving average types were added to Investor/RT 3.8.
The moving average technical indicator in Investor/RT now supports nine distinct moving average types. For instance, if you wanted to smooth Rate of Change, you would simply use the syntax MA(ROC). In addition, the MA token can be used in RTL to smooth just about anything. The following Price options are available as the input data for each smoothing type: Open, Close, High, Low, HI+LO/2, HI+LO+CL/3, O+H+L+C/4, %Change, or OP+CL/2. Some of the averaging methods however are not so much "Moving" as they are "Cumulative" (exponential for one). The term "Moving" is used to refer to the fact that the window of bars that we are considering remain fixed in width (Period) but moves forward with subsequent bar. A moving average reveals the general direction and strength of a stock's price trend over a given period. Data is smoothed in order to help reduce the effect of bar-to-bar price fluctuations and help identify longer term emerging trends. Moving averages provide different options for smoothing data.
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