[R] Normality tests

[Tobias Verbeke]

Hi Alexandre,

Alexandre Christie wrote:
> 
> I am new to R, and I am writing to seek your advice on how best to use it to run
> R's various normality tests in an automated way.
> 
> In a nutshell, my situation is as follows. I work in an investment bank, and my
> team and I are concerned that the assumption we make in our models that the
> returns of assets are normally distributed may not be justified for certain
> asset classes. We are keen to check this statistically.
> 
> To this end, we have an Excel document which contains historical data on the
> returns of the asset classes we want to investigate, and we would like to run
> R's multiple normality tests on these data to check whether any asset classes
> are flagged up as being statistically non-normal.
> 
> I see from the R documentation that there are several R commands to test for
> this, but is it possible to progamme a tool which can (i) convert the Excel data
> into a format which R can read, then (ii) run all the relevant tests from R,
> then (iii) compare the results (such as the p-values) with a user-defined
> benchmark, and (iv) output a file which shows for each asset class, which tests
> reveal that the null hypothesis of normality is rejected?

The short answer is `yes, this is perfectly possible' by putting all
the pieces in an R script file and sourcing it or processing it in
batch mode.

ad (i): there are several ways of accessing Excel files.
	Using RODBC is one of them. Section 8 of the R
	Data Import / Export gives an overview of all options.
	


ad (ii): this is a matter of conducting the tests and storing
	the test results in appropriate data structure

ad (iii): straightforward

ad (iv): you did not specify

> 
> My team and I would be very grateful for your advice on this.
> 
> Yours sincerely,
> 
> Alex.
> 
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