How could Linear Regression predict stock price?

Case Study - Alibaba stock price prediction

 

Based upon bloomberg April 11th news, Charlie Munger unloaded his Alibaba Stake in Half

You may ask, is there any leading indicator to predict stock price movement?

The answer is that Linear Regression is considered as leading indicator for trend prediction

 

What is Linear Regression?

 

In statistics, linear regression is a linear approach for modeling the relationship between a scalar response and one or more explanatory variables. Linear regression has many practical uses. One use is for prediction, forecasting, linear regression can be used to fit a predictive model to an observed data set of values of the response and explanatory variables. After developing such a model, if additional values of the explanatory variables are collected without an accompanying response value, the fitted model can be used to make a prediction of the response.

 

To apply linear regression to stock trending prediction, Linear Regression Indicator plots the ending value of a Linear Regression Line for a specified number of bars; showing, statistically, where the price is expected to be. For example, a 20 period Linear Regression Indicator will equal the ending value of a Linear Regression line that covers 20 bars.

 

Leading Trend indicator, can be 5 days, 20 days or any days you would like to view the trend

 

Linear Regress is considered as one of most useful tool to find a way to identify price trends without the fallibility and bias off the human mind. 

 

How Linear Regression works?

 

• The interpretation of the Linear Regression Indicator is similar to that of a moving average although it does have an advantage when compared to a moving average.
• Instead of plotting an average of past price action, Linear Regression Line would expect the price to be, making the Linear Regression Indicator more responsive than a moving average.

 

How to calculate Linear Regression?

Linear Regression has been developed over many years for prediction, its standard calculation can be found https://en.wikipedia.org/wiki/Linear_regression

 

Case Study: Alibaba stock price prediction

Below is Alibaba stock price and linear regression based upon 5 days and 20 days extracted from Fidelity 

From above chart, we can find out that Linear Regression 5 days and 20 days both reflect the stock price, 5 days is more accurate that 20 days, based upon linear regression predication, very likely Alibaba stock price will drop further.