What is the test for autocorrelation?
Durbin-Watson test
Autocorrelation is diagnosed using a correlogram (ACF plot) and can be tested using the Durbin-Watson test. The auto part of autocorrelation is from the Greek word for self, and autocorrelation means data that is correlated with itself, as opposed to being correlated with some other data.
When using the LM test for serial correlation what is the null hypothesis?
The null hypothesis is that there is no serial correlation of any order up to p. Because the test is based on the idea of Lagrange multiplier testing, it is sometimes referred to as an LM test for serial correlation. A similar assessment can be also carried out with the Durbin–Watson test and the Ljung–Box test.
Which is the best test for serial correlation?
A plot of residuals. Plot e t against t and look for clusters of successive residuals on one side of the zero line. You can also try adding a Lowess line, as in the image below. A Durbin-Watson test. A Lagrange Multiplier Test. Ljung Box Test. A correlogram. A pattern in the results is an indication for autocorrelation.
How to test the null hypothesis of no serial correlation?
The Durbin Watson tests the null hypothesis of no serial correlation against the alternative hypothesis of positive or negative serial correlation. The Durbin-Watson Statistic (DW) is approximated by: DW = 2(1−r) D W = 2 (1 − r)
How does serial correlation affect the F statistic?
However, a positive serial correlation inflates the F-statistic to test for the overall significance of the regression as the mean squared error (MSE) will tend to underestimate the population error variance. This increases Type I errors (the rejection of the null hypothesis when it is actually true).
How is the serial correlation of stock prices determined?
Serial correlation among these quants is determined using the Durbin-Watson test. The correlation can be either positive or negative. A stock price displaying positive serial correlation has a positive pattern. A security that has a negative serial correlation has a negative influence on itself over time.