Quadratic Regression
A quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola.
Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression.
Like the Linear Regression (LSMA) a Quadratic regression attempt to minimize the sum of squares (sum of the squared difference between a set of data and an estimator), this is why
those kinds of filters have low lag.
Here the difference between a Least Squared Moving Average (green) and a Quadratic Regression (red) of both period 500
Here it look like the Quadratic Regression have a best fit than the LSMA
Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression.
Like the Linear Regression (LSMA) a Quadratic regression attempt to minimize the sum of squares (sum of the squared difference between a set of data and an estimator), this is why
those kinds of filters have low lag.
Here the difference between a Least Squared Moving Average (green) and a Quadratic Regression (red) of both period 500
Here it look like the Quadratic Regression have a best fit than the LSMA
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You can also check out some of the indicators I made for luxalgo : www.tradingview.com/u/LuxAlgo/