Linear regression (Linear Regression) is a statistical method to track market trends. Its results are usually similar to moving averages. But unlike the moving average, linear regression has a relatively small delay and is more sensitive to price changes.
Linear regression is a statistical analysis method that uses regression analysis in mathematical statistics to determine the quantitative relationship between two or more variables. It is widely used. The expression is y = w’x+e, where e is a normal distribution whose error follows a mean value of 0. In regression analysis, only one independent variable and one dependent variable are included, and the relationship between the two can be approximated by a straight line. This kind of regression analysis is called unary linear regression analysis.
The function of linear regression is to find the main trend of the market with a small delay (compared to the market price). When the price is the same as the trend of the linear regression indicator in a smaller range, it can also point out the divergence of the future trend.
- Linear regression can indicate whether there is a bull market/bear market in the current market.
- When the indicator crosses the price, the trend change can be determined. However, due to some delays in linear regression, it can only be used as a confirmation. Note: When the price changes consistently along the price, it means that the market trend will continue.