In finance, T-test could be viewed as one of the most used statistical hypothesis tests in which the test statistic follows a student's t distribution if the null hypothesis is supported. We know that the mean for a standard normal distribution is zero. In the following program, we generate 1,000 random numbers from a standard distribution. Then, we conduct two tests: test whether the mean is 0.5
, and test whether the mean is zero:
>>>from scipy import stats >>>np.random.seed(1235) >>>x = stats.norm.rvs(size=10000) >>>print("T-value P-value (two-tail)") >>>print(stats.ttest_1samp(x,5.0)) >>>print(stats.ttest_1samp(x,0)) T-value P-value (two-tail) (array(-495.266783341032), 0.0) (array(-0.26310321925083124), 0.79247644375164772) >>>
For the first test, in which we test whether the time series has a mean of 0.5
, we reject the null hypothesis since the T-value is 495.2
and the P-value is 0
. For the second...