Hi,
Any idea how to formulate a screen for stocks that are individually highly volatile (price/volume/dollar-volume), but have minimal correlation? This basically amounts to the most jumbled up portfolio that could be constructed.
Say I had universe of 100 securities, and wanted to pick 10 that meet the criteria above. Could someone outline an algorithm?
Grant
Hello Grant,
It's not what you want but Steven Sanderson and myself worked on this a few weeks ago. It looks at a universe of securities and calculates their Sharpe ratios. For the top N best Sharpe ratios it calculates all possible portfolios and invests in the one with the minimum sum of correlations.
P.
Hi Peter/Grant - sorry to revive an old thread, but a newbie question regarding why do I keep getting a AssertionError: 95 columns passed, passed data had 93 columns
There was a runtime error on line 134 when run in minute mode - is there an if workaround?
Grant: I find that network theory provides an elegant solution to the problem of uncorrelated basket selection and there's various research papers on this. If you're feeling adventurous, see here: https://github.com/PythonNetworks/PyData2014-Berlin I started to replicate some of this in the research platform (networkx is available, but other packages are still missing) but it's still ongoing research.
EDIT: Just saw that this thread is way old, it's still relevant though.
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