Kendall Rank Correlation NET on SMA [Loxx] is an SMA that uses Kendall Rank Correlation to form a sort of noise elimination technology to smooth out trend shifts. You'll notice that the slope of the SMA line doesn't always match the color of the SMA line. This is behavior is expected and is the NET that removes noise from the SMA.
What is Kendall Rank Correlation? Also commonly known as “Kendall’s tau coefficient”. Kendall’s Tau coefficient and Spearman’s rank correlation coefficient assess statistical associations based on the ranks of the data. Kendall rank correlation (non-parametric) is an alternative to Pearson’s correlation (parametric) when the data you’re working with has failed one or more assumptions of the test. This is also the best alternative to Spearman correlation (non-parametric) when your sample size is small and has many tied ranks.
Kendall rank correlation is used to test the similarities in the ordering of data when it is ranked by quantities. Other types of correlation coefficients use the observations as the basis of the correlation, Kendall’s correlation coefficient uses pairs of observations and determines the strength of association based on the patter on concordance and discordance between the pairs.
Concordant: Ordered in the same way (consistency). A pair of observations is considered concordant if (x2 — x1) and (y2 — y1) have the same sign.
Discordant: Ordered differently (inconsistency). A pair of observations is considered concordant if (x2 — x1) and (y2 — y1) have opposite signs.
Kendall’s Tau coefficient of correlation is usually smaller values than Spearman’s rho correlation. The calculations are based on concordant and discordant pairs. Insensitive to error. P values are more accurate with smaller sample sizes.
진정한 TradingView 정신에 따라, 이 스크립트의 저자는 트레이더들이 이해하고 검증할 수 있도록 오픈 소스로 공개했습니다. 저자에게 박수를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 출판물에서 이 코드를 재사용하는 것은 하우스 룰에 의해 관리됩니다. 님은 즐겨찾기로 이 스크립트를 차트에서 쓸 수 있습니다.