6 Types of Moving Averages every Trader should know!
A thread(🧵)... (1/21)
A thread(🧵)... (1/21)
1. Simple Moving Average(SMA): #SMA is calculated by averaging the most recent price points.
Different types of prices like High, Low, Open, or Close are used to calculate SMA (2/21)
Different types of prices like High, Low, Open, or Close are used to calculate SMA (2/21)
2. Exponential Moving Average(EMA): EMA gives weightage to the most recent price points and makes it more responsive to recency.
The formula for calculating #EMA is as follows👇 (3/21)
The formula for calculating #EMA is as follows👇 (3/21)
Current EMA= [Closing Price - EMA(Previous time)] X Multiplier + EMA(Previous Time Period) (4/21)
3. Weighted Moving Average(WMA): Another reliable #indicator used for analyzing trade direction or buy/sell signals!
Here, weightage is given to the recent data points and less weightage to past data points (5/21)
Here, weightage is given to the recent data points and less weightage to past data points (5/21)
It is calculated by multiplying each point in the data set by a predefined weighing factor👇 (6/21)
4. Double Exponential Moving Average(DEMA): This indicator has been formulated to reduce lag results and is more responsive, helping short-term traders in spotting #trend reversals (7/21)
DEMA allocates more weightage to the most recent data points, thus being more reactive to short-term changes👇(8/21)
5. Triple Exponential Moving Average (TEMA): DEMA was developed by Patrick Mullay, after finding out the lag in the calculation of DEMA IN 1994👇(9/21)
The only difference between DEMA and TEMA is that TEMA's formula uses a triple-smoothed EMA, which is considered to be an upgraded, reducing the lag even DEMA could have had👇 (10/21)
6. Linear Regression/Least Square Moving Averages(LSMA): Calculates the least-squares regression lines of the preceding periods, helping with forwarding #price projections from the current period👇(11/21)
#Traders use this indicator to find out what can happen if the regression line is continued! (12/21)
The indicator is calculated based on the sum of least squares for finding a straight line that best fits the data for a specific time👇
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