On Mon, May 25, 2009 at 7:37 PM, Pierre GM <pgmdevlist@gmail.com> wrote:
On May 25, 2009, at 7:02 PM, josef.pktd@gmail.com wrote:
On Mon, May 25, 2009 at 6:36 PM, Pierre GM <pgmdevlist@gmail.com> wrote:
Sorry to jump in a conversation I haven't followed too deep in details, but I'm sure you're all aware of the scikits.timeseries package by now. This should at least help you manage the dates operations in a straightforward manner. I think that could be a nice extension to the package: after all, half of the core developers is a financial analyst...
The problem is, if the functions are enhanced in the current numpy, then scikits.timeseries is not (yet) available.
Mmh, I'm not following you here...
The original question was how we can enhance numpy.financial, eg. np.irr So we are restricted to use only what is available in numpy and in standard python.
Pierre, your not already hiding by chance any finance code in your timeseries scikit? :)
Ah, you should ask Matt, he's the financial analyst, I'm the hydrologist... Would moving_funcs.mov_average_expw do something you'd find useful ?
I looked at your moving functions, autocorrelation function and so on a while ago. That's were I learned how to use np.correlate or the scipy versions of it, and the filter functions. I've written the standard array versions for the moving functions and acf, ccf, in one of my experiments. If Skipper has enough time in his google summer of code, we would like to include some basic timeseries econometrics (ARMA, VAR, ...?) however most likely only for regularly spaced data.
Anyhow, if the pb you have are just to specify dates, I really think you should give the scikits a try. And send feedback, of course...
Skipper intends to write some examples to show how to work with the extensions to scipy.stats, which, I think, will include examples using time series, besides recarrays, and other array types. Is there a time line for including the timeseries scikits in numpy/scipy? With code that is intended for incorporation in numpy/scipy, we are restricted in our external dependencies. Josef