VAMA Volume Adjusted Moving Average Function

This indicator is a live analysis adaptation of Richard Arms' Volume Adjusted Moving Average coded as a single function. VAMA utilizes a period length that is based on volume increments rather than time. Settings are provided for using as a pair of fast and slow moving averages.

SampleN - N volume bars used as sample to calculate average volume , 0 equals all bars.

VAMA Source - Price used for volume weighted calculations.

VAMA Length - Specified number of volume ratio buckets to be reached.

VAMA VI Fct - Size of volume ratio buckets.

VAMA Strict - Must meet desired volume requirements, even if number of bars has to exceed VAMA Length to do it.

Please see previous published example here for more details on VAMA's usage and inability to redraw the past on time based charts.

NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
版本注释: Revision 1

Removed function's local ‎reliance on global input nvb by changing it to use local _nvb instead, added cosmetic space, revised comment, no calculations are affected from previous version.

Previous lines:
    tvb = 0, tvb := _nvb == 0 ? ‎nz(tvb[1]) + 1 : nvb                           // total ‎volume bars in sample            
    tvs = nvb == 0 ? cum(‎volume) : sum(‎volume,nvb)                             // total ‎volume in sample

Revised lines:
    tvb = 0, tvb := _nvb == 0 ? ‎nz(tvb[1]) + 1 : _nvb                          // total ‎volume bars used in sample            
    tvs = _nvb == 0 ? cum(‎volume) : sum(‎volume, _nvb)                          // total ‎volume in sample
从常用脚本中删除 添加到常用脚本
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Thanks for sharing and including the very thorough and helpful notes!
+1 回复
allanster wroclai
@wroclai, thanks and good to see you!
+1 回复
very interesting script, thanks a lot.
+1 回复
@rhanna, thanks for your interest and taking the time to comment, appreciated.
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Thankyou so much Sir .you make everything ready for us.our duty is just to
thankyou sir

how do i learn this coding
+1 回复
allanster Adeel953
@Adeel953, I appreciate your interest, @PineCoders has a great collection of resources for learning here:
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Thanks for ypur job!
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allanster gianfranco60
@gianfranco60, you are welcome, thanks for your interest and comments!
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Thank you for the posting allanster!

I love this simple easy understanding indicator. That crossover signals is so precise, much better than EMA
+1 回复
@ICEKI, this version is identical to "Current" and "Subset" modes in the previous version I published, but it is much more efficient in it's resource usage. This version's code is also more portable and friendly for experimentation. Hope you find useful.
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