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Borsgade
The folks over at AQR recently wrote a piece on how to use machine learning in stock portfolio construction. Specifically stock portfolio selection and timing. The article is quite technical but do provide some food for thought for less sophisticated investors on how AI can be implemented in an investment strategy.
Here are the key takeaways:
In each case, complex models generated substantially higher Sharpe ratios compared to simple linear models, with improvements ranging from 50-100%.
More complex models can better identify true nonlinear relationships and, thus, produce better stock selection strategy performance. […] Our results indicate performance improvements relative to a simple, linear approach in the range of 50-100%, suggesting that machine learning can help to build better stock selection portfolios.
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