I have a time series with prices (around 800 prices). I need to test if the mean is constant during all the series.
I think I should subdivide the series in groups, but what method do I have to use to check if the mean is constant if the distribution is not normal?
Best Answer
You may want to look at a nonparametric approach to this problem, since you cannot rely on normality. Break your sample into two groups, $x_1, dots, x_{400}$ and $x_{401}, dots, x_{800}$ and compare them in pairs ($x_1, x_{401}$), $dots$, ($x_{400}, x_{800}$).
You now have the framework of a two-sample test of equal means/medians. Under the null hypothesis of a constant mean, we should expect the mean/median of these two groups to be the same.
Since we expect the medians to be the same, some NP tests will assert that in the pair $(x_i, x_{i+400})$, the chance that $x_i$ is bigger is a random variable, Bernoulli distributed with probability $frac{1}{2}$. Two hypothesis tests proceed from this. Tests to look into would be: Wilcoxon Signed Rank Test and the Signed Test.
Similar Posts:
- Solved – Pairs Trading: What statistics to use for analysis of Cointegration using ADF Test
- Solved – method to check the homogeneity of variance of a single time series
- Solved – Kruskal-Wallis vs Jonckheere-Terpstra Test
- Solved – How to interpret Mann-Whitney’s statistical significance if median is equal
- Solved – How to interpret Mann-Whitney’s statistical significance if median is equal