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What are moving averages and how are they calculated? 

 

Simple moving average explanation with chart examples and formula

 

 
             Daily Temperature 16 19 21 20 24 21 16 17 11 14 13 20 21
                         
             3 Day Moving Average  - - 18.6 20.0 21.6 21.6 20.3 18.0 14.6 14.0 12.6 15.6 18.0

 

 

In the table above you can see the daily temperature and below is the "simple moving average" of the daily temperature.

 

The colour coding is used to show how the calculations are made.  The first three days are 16, 19, 21 which produce an 3 day average of 18.67.

The calculation is very simple.

 

Day 1 (16) + Day 2 (19) + Day 3 (21) = 56 then we simply divide 56 by 3 days ( as we are making a three day moving average )

 

The correct mathematic statement for this would be (16+19+21) / 3 

The next stage in creating a true moving average is to roll forward to the right by 1 number. So for the next value we will use Days  2 ,3 and 4

 

Therefore (19+21+20) / 3 = 20  this procedure repeats each time a new value or a new day is added to the array of temperatures. You can see of course that 3 days are required to produce the three day average.  Another important factor to understand is that this action of waiting for three days before calculating a value produces a delay in the average which is outputted. This delay is know as LAG.

 

If you look at the Last temperature of 21 you will realise that the 3 day average of 18 is actually "LAGGING BEHIND" 

 

The chart below is a graphic illustration of the daily temperature and the three day average of it.

 

 

 

 

Key points to remember

 

  • Moving averages produce a smoother output value than the actual data value

  • Moving averages produce a delay know as lag.

  • Moving averages need 3 days to compute the first value ( if a three day average is required )

  • Moving averages reduce fluctuation and smooth out "noise"  ( Noise is a term used for jagged and messy data fluctuations )

 

6 Day moving average calculation example

 

 
Stock market price 41 42 40 38 39 36 36 33 32 28 29 33 36 39 44
                             
6 Day Moving Average  - - - - - 39.33 38.50 37.00 35.67 34.00 32.33 31.83 31.83 32.83 34.83

 

 

 

In the table above you can see the daily stock market price and below is the "six day simple moving average" of that stock price.

 

The colour coding is used to show how the calculations are made.  The first six days are coloured orange 41,42,40,38,39,36  which produce an 6 day average of 39.33

 

The calculation is very simple and follows the same method as the first example. However this time the first 6 days are added together and divided by 6 because this time it a 6 day average instead of 3 days as was used in the first example. 

 

Day 1 (41) + Day 2 (42) + Day 3 (40) + Day 4 (38) + Day 5 (39) + Day 6 (36) = 236 then we simply divide 236 by the 6 days ( as we are making a six day moving average )

 

The correct mathematic statement for this would be (41+42+40+38+39+36) / 6 

The next stage in creating a true moving average is to roll forward to the right by 1 number. So for the next value we will use Days  2, 3, 4, 5, 6, 7

 

 

The chart below is a graphic illustration of the daily stock price and six day average of it.

 

 

 

  • The 6 day moving average is clearly making a smoother indication of the stock price.

  • Note the delay (LAG) in the response time of the yellow average line. It turns up on 3 days later than the stock price

  • Moving averages can be used to smooth erratic data so as to be clearer to understand and interpret.

  • Note how the 6 day moving average is smoother than the 3 day moving average.

  • The more days ( periods ) used in the calculation the smoother they will become, and the more lag they will have.

 

Mathematical symbol for AVERAGE

 

 

 

 

Other types of moving average and formulas

 

 

 

 

  • A very advanced type of moving average is shown below. PLA Dynamical has over 1000 lines of computer code used to generate its output

 

 

PLA Dynamical is the fastest moving average on the planet ( If overshoot = True and Speed = 100)

 

  • PLA Dynamical shown below has a faster response time than other moving averages due to its complex algorithms

  • The formula has over 1000 lines of computer code to generate it.

 

PLA Dynamical response times compared to standard type MA type filters Tested at length 30

 

Filter   Length Speed Overshoot Response time to new price range
           
PLA Dynamical    30 100 True 3  Bars
PLA Dynamical    30 100 False 18 Bars
Weighted MA   30 - - 24 Bars
Triangular MA   30 - - 25 Bars
Exponential MA   30 - - 43 Bars
           
Filter   Length Speed Overshoot Response time to 1 standard deviation from mid point
           
PLA Dynamical    30 100 True 19 Bars
PLA Dynamical    30 100 False 23 Bars
Weighted MA   30 - - 25 Bars
Triangular MA   30 - - 27 Bars
Exponential MA   30 - - 61 Bars

 

 

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Precision Lagless Average Dynamical for NinjaTrader 7 conceptualized by Precision Trading systems in 2012  

Precision Lagless Average was originally created in 2009 by Precision Trading Systems to provide clear and concise DSP trading signals.

 

Since then some major refinements and modifications have taken place. The PLA Dynamical product now has 101 different gears ( speed settings ) also a brand new "overshoot enable-disable" feature has been incorporated.  The anti-reverse feature present in the 2009 version has been retained and improved and I have added a colour changing plot because so many customers asked for it. The original innovative algorithm still dwells within but now its has the added power of all the new features to compliment its performance, adding to its huge amount versatility.

 

 

 

 

 

 

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