Adaptive Moving Averag

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04/13/2023 at 9:03 PM #213253 quote
Markscragg
Participant

New
I am trying to code a variation of Perry Kaufmans Adaptive Moving Average

The Equation is AMA= (ER*Close) + (1-ER)*AMA[1]

It Returns ‘Blank’

Can anyone help?
```
// parameter
// n = 10

Change = ABS(close - close[n])

calc = ABS(close-close[1])

volat = summation[n](calc)

ER = Change / volat

once AMA=Average[n]

AMA=(ER*Close)+(1-ER)*AMA[1]

//or

//V1=(1-ER)
//V2=AMA[1]
//V3=(V1*V2)
//AMA=(ER*Close)+V3

Return AMA
```
04/13/2023 at 10:00 PM #213254 quote
JS
Participant

Master
Hi,

This is how I know the Kaufman filter…
```
Period = MAX(10, 4)

FastPeriod = 7
SlowPeriod = 28

Fastest = 2 / (FastPeriod + 1)
Slowest = 2 / (SlowPeriod + 1)

IF BarIndex < Period THEN
KAMA = Close
ELSE
Num = ABS(Close - Close[Period])
Den = summation[Period](ABS(Close - Close[1]))
ER = Num / Den
Alpha = SQUARE(ER * (Fastest - Slowest) + Slowest)
KAMA = (Alpha * Close) + ((1 - Alpha) * KAMA[1])
ENDIF
Return KAMA
```
04/14/2023 at 9:40 AM #213279 quote

Markscragg
Participant

New

JS Thanks for the quick reply. However I was trying to code the following equation The Equation is AMA= (ER*Close) + (1-ER)*AMA[1] Where ER is the smoothing constantent dirived from Perry Kaufman I think the problem lies in the second part of the equation! Regards

04/14/2023 at 1:55 PM #213293 quote
Nicolas
Keymaster

Legend
Needs at least n data in order to calculate, so embed your code into a barindex count condition:
```
// parameter
n = 10

if barindex>n then 
Change = ABS(close - close[n])

calc = ABS(close-close[1])

volat = summation[n](calc)

ER = Change / volat

once AMA=Average[n]

AMA=(ER*Close)+(1-ER)*AMA[1]
endif 

Return AMA
```
04/17/2023 at 9:59 AM #213394 quote

Markscragg
Participant

New

Thank You Nicolas That seems to work I have been learning prorealcode for sometime now. Could you recommend any text that may help me I have studied the online manuels plus the Vivian Schmitt ebook but still need more help. Regards Mark
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