http://web4.cs.ucl.ac.uk/staff/C.Bracegirdle/BayesianConditionalCointegration.php
I was wondering if anyone would be brave enough to tackle the above paper.
It seems like he is using the expectation maximization to solve the problem.
I was wondering if the algorithm could be implemented as part of pymc3 but this is far to advanced for me.
Thoughts or comments :)....
After spending past 6 months reading research papers on mean reversion and implementing spread strategies on stationary series, I learnt that cointegration does not work out of sample. In sample they all give a nice stationary looking mean reverting series but they seldom work out of sample. I would be interested to know if anyone else had luck with cointegration.
So the above paper is generally an academic exercise.
I had an intuition that it might hold more promise as it uses a sort of Bayesian update.
This could theoretically be developed as an online model update.
Hence changing as new data becomes available.
But I am probably way of the mark on this.
Thoughts...
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