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Are there techniques or models in finance that (unlike supervised learning where input data such as returns and volatility is estimated making the asset allocation data-driven) allow for portfolio optimization without using empirical data for an input?

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  • $\begingroup$ Yes, the simplest is to use hierarchical clustering to split your capital down each branch. With some intuition, however, partitional clustering can be even used like a relative valuation tool. $\endgroup$
    – Lisa Ann
    Jul 16 '20 at 6:52
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I quote a very famous paper from De Prado:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2708678

In general, unsupervised learning is a very powerful tool in asset allocation especially with regards to exploring deep unsupervised relations among different assets (i.e. sort of correlations).

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