Japanese Correlation CoefficientIntroduction 
This indicator was asked and named by a trading meetup participant in Sevilla. The original question was "How to estimate the correlation between the price and a line as easy as possible",  a question who got little attention. I previously proposed a correlation estimate using a modification of the standard score  (see at the end of the post)  for the estimation of a Savitzky-Golay moving average  (LSMA)  of order 1, however something faster could maybe be done and this is why i accepted the challenge. 
 Japanese Correlation 
Correlation is defined as the linear relationship between two variables  x  and  y ,  if x and y follow the same direction then the correlation increase else decrease. The correlation coefficient is always equal or below 1 and equal or above -1, it also have to be taken into account that this coefficient is quite smooth. Smoothing is not a problem, scaling however require more attention, high price > closing price > low price, therefore scaling can be done. First we smooth the closing/high/low price with a simple moving average of period  p/2 , then we take the difference of the smoothed close with the smoothed close  p/2  bars back, this result is then divided by the difference between the highest smoothed high's with the lowest smoothed low's over period  p/2 . 
Since we use information provided by candlesticks  (close/high/low)  i have been asked to publish this estimator with the name  Japanese correlation coefficient , this name don't imply the use of data from Japanese markets, "Japanese" is used because of the candlestick method coming from Japan.
 Comparison 
I compare this estimation with the correlation coefficient provided in pinescript by the correlation function. 
  
The estimation in orange with the original correlation coefficient using n as independent variable in blue with both length = 50.
  
comparison with length = 200.
 Conclusion 
I have shown that it is possible to roughly estimate the correlation coefficient between price and a linear function by using different price information. Correlation can be further estimated by using homogeneous bridge OHLC volatility estimators thus making able the use of different independent variables. I really hope you like this indicator and thanks to the meetup participant asking the question, i had a lot of fun making the indicator.
 An alternative method 
 
