OPEN-SOURCE SCRIPT
업데이트됨 Centered Moving Average

The Centered moving averages tries to resolve the problem that simple moving average are still not able to handle significant trends when forecasting.
When computing a running moving average in a centered way, placing the average in the middle time period makes sense.
If we average an even number of terms, we need to smooth the smoothed values.
Try to describe it with an example:
The following table shows the results using a centered moving average of 4.
nterim Steps
Period Value SMA Centered
1 9
1.5
2 8
2.5 9.5
3 9 9.5
3.5 9.5
4 12 10.0
4.5 10.5
5 9 10.750
5.5 11.0
6 12
6.5
7 11
This is the final table:
Period Value Centered MA
1 9
2 8
3 9 9.5
4 12 10.0
5 9 10.75
6 12
7 11
With this script we are able to process and display the centered moving average as described above.
In addition to this, however, the script is also able to estimate the potential projection of future data based on the available data by replicating where necessary the data of the last bar until the number of data necessary for the calculation of the required centered moving average is reached.
If for example I have 20 daily closings and I look for the moving average centered at 10, I receive the first data on the fifth day and the last data on the fourteenth day, so I have 5 days left uncovered, to remedy this I have to give the last value to the uncovered data the closing price of the last day.
The deviations work like the bollinger bands but must refer to the centered moving average.
When computing a running moving average in a centered way, placing the average in the middle time period makes sense.
If we average an even number of terms, we need to smooth the smoothed values.
Try to describe it with an example:
The following table shows the results using a centered moving average of 4.
nterim Steps
Period Value SMA Centered
1 9
1.5
2 8
2.5 9.5
3 9 9.5
3.5 9.5
4 12 10.0
4.5 10.5
5 9 10.750
5.5 11.0
6 12
6.5
7 11
This is the final table:
Period Value Centered MA
1 9
2 8
3 9 9.5
4 12 10.0
5 9 10.75
6 12
7 11
With this script we are able to process and display the centered moving average as described above.
In addition to this, however, the script is also able to estimate the potential projection of future data based on the available data by replicating where necessary the data of the last bar until the number of data necessary for the calculation of the required centered moving average is reached.
If for example I have 20 daily closings and I look for the moving average centered at 10, I receive the first data on the fifth day and the last data on the fourteenth day, so I have 5 days left uncovered, to remedy this I have to give the last value to the uncovered data the closing price of the last day.
The deviations work like the bollinger bands but must refer to the centered moving average.
릴리즈 노트
after some tests I found problems in calculating the projection of the centered mean, so I proceeded to rewrite the implementation by introducing the bands based on the required standard deviation오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.