Weighted Moving Average (WMA) is one of the configurations of simple moving average which accounts not only for price values but also their weight.
Calculated as per formula:
where: Pi — price value for the number of i-periods, (today i =1),
Wi — weight value for price for the number of i-periods.
In simpler words, elements with an account of their values are summed and divided for the sum of weights of those elements, thus, generally speaking, arithmetical average of those elements is calculated.
It is accepted that weight changes according to linear function where W1 takes the largest weight and then calculation uses simple arithmetical progression, for instance: 1, 2, 3, 4, 5, 6...; (or any other: 0,5, 0,75, 1, 1,25). Such representation is called Linear Weighted Moving Average, (LWMA). Let's take period equal to 5:
,
where: P1 and P2 — are the prices for today and yesterday.
Some configurations may use more complicated formula with non-linear distribution, involving logarithmic, parabolic and other functions, for example, if following is accounted:
- the number of ticks in bar;
- the length of passed distance in candle (High - Low)
- weight average against the distance; - the size of candle body (|Close - Open|).
Price can also be different: Close, Open, High, Low, Median Price, Typical Price.
Application of WMA
Weighted Moving Average is usually applied in the same cases in which simple moving average is applied for technical analysis purposes. Though under similar entrance and exit market alerts LWMA responds to price change faster because weight is accounted for the latest periods. That allows not to miss lucky moments for entering the market during important economic news, interventions and other significant moves.
For stock market analysis it is recommended to use parameters equal to 7 and 14, for currency market – 5 and 20. As you can see on the image, the larger period is, the smoother moving average is and the bigger fluctuation range is has.
Sine-Weighted Moving Average ( SWMA) uses sine function during its calculation as weight (W). Thanks to SWMA, it is possible to filter noises, determine bottom and top with a higher precision.
Pros and cons of WMA
Due to taking in account weight of elements, WMA is more sensitive towards price change in contrast to simple moving average, which allows getting entrance and exit alerts faster. However, as any other MA, weight also has a certain delay.
It is better to apply it in short- and mid-term strategies, because the latest price changes has the biggest weight. In other words, at high time-frame WMA looks smoother because of low market noise and it does not provide such clear alerts.