Moving Average Technical Indicator
The Moving Average Technical Indicator shows the mean instrument
price value for a certain period of time. When one calculates the
moving average, one averages out the instrument price for this time
period. As the price changes, its moving average either increases, or
decreases.
There are four different types of moving averages:
Simple (also referred to as Arithmetic),
Exponential,
Smoothed and
Linear Weighted.
Moving averages may be calculated for any sequential data set,
including opening and closing prices, highest and lowest prices,
trading volume or any other indicators. It is often the case when
double moving averages are used.
The only thing where moving averages of different types diverge
considerably from each other, is when weight coefficients, which are
assigned to the latest data, are different. In case we are talking of
simple moving average, all prices of the time period in question, are
equal in value. Exponential and Linear Weighted Moving Averages attach more value to the latest prices.
The most common way to interpreting the price moving average is to
compare its dynamics to the price action. When the instrument price
rises above its moving average, a buy signal appears, if the price
falls below its moving average, what we have is a sell signal.
This trading system, which is based on the moving average, is not
designed to provide entrance into the market right in its lowest point,
and its exit right on the peak. It allows to act according to the
following trend: to buy soon after the prices reach the bottom, and to
sell soon after the prices have reached their peak.
Moving averages may also be applied to indicators. That is where the
interpretation of indicator moving averages is similar to the
interpretation of price moving averages: if the indicator rises above
its moving average, that means that the ascending indicator movement is
likely to continue: if the indicator falls below its moving average,
this means that it is likely to continue going downward.
Here are the types of moving averages on the chart:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Linear Weighted Moving Average (LWMA)
Calculation:
Simple Moving Average (SMA)
Simple, in other words, arithmetical moving average is calculated by
summing up the prices of instrument closure over a certain number of
single periods (for instance, 12 hours). This value is then divided by
the number of such periods.
SMA = SUM(CLOSE, N)/N
Where: N — is the number of calculation periods.
Exponential Moving Average (EMA)
Exponentially smoothed moving average is calculated by adding the
moving average of a certain share of the current closing price to the
previous value. With exponentially smoothed moving averages, the latest
prices are of more value. Ppercent exponential moving average will look like:
EMA = (CLOSE(i)*P)+(EMA(i1)*(1P))
Where: CLOSE(i) — the price of the current period closure; EMA(i1) — Exponentially Moving Average of the previous period closure; P — the percentage of using the price value.
Smoothed Moving Average (SMMA)
The first value of this smoothed moving average is calculated as the simple moving average (SMA):
SUM1 = SUM(CLOSE, N) SMMA1 = SUM1/N
The second and succeeding moving averages are calculated according to this formula:
PREVSUM = SMMA(i1) *N SMMA(i) = (PREVSUMSMMA(i1)+CLOSE(i))/N
Where: SUM1 — is the total sum of closing prices for N periods; PREVSUM — is the smoothed sum of the previous bar; SMMA1 — is the smoothed moving average of the first bar; SMMA(i) — is the smoothed moving average of the current bar (except for the first one); CLOSE(i) — is the current closing price; N — is the smoothing period.
Linear Weighted Moving Average (LWMA)
In the case of weighted moving average, the latest data is of more
value than more early data. Weighted moving average is calculated by
multiplying each one of the closing prices within the considered
series, by a certain weight coefficient.
LWMA = SUM(Close(i)*i, N)/SUM(i, N)
Where: SUM(i, N) — is the total sum of weight coefficients.
Source Code
Full MQL4 source of Moving Averages is available in the Code Base: Moving Averages
