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Is it possible to factor (e.g. GRI) sustainability criteria into the portfolio fitness function? https://news.ycombinator.com/item?id=21922558

My concern is that - like any other portfolio optimization algorithm - blindly optimizing on fundamentals and short term returns will lead to investing in firms who just dump external costs onto people in the present and future; so, screening with sustainability criteria is important to me.

From https://news.ycombinator.com/item?id=19111911 :

> awesome-quant lists a bunch of other tools for algos and superalgos: https://github.com/wilsonfreitas/awesome-quant



This is perfect. Thank you for sharing this.

I might start implementing some of these but would love for someone else to add a few PRs as well. The code is pretty modular especially if we want to add new strategies.


(Sustainable) Index ETFs in the stocks.txt universe would likely be less sensitive to single performers' effects in unbalanced portfolios.

> pyfolio.tears.create_interesting_times_tear_sheet measures algorithmic trading algorithm performance during "stress events" https://github.com/quantopian/pyfolio/blob/03568e0f328783a6a...


Does the code have any factor investing features at all right now? I was just reading about alpha lens, another project focused on performance attribution of factors. To avoid reinventing the wheel, are there any other libraries that can be leveraged to add factors - so portfolios are constructed to go long and/or short a certain factor like sustainability or etc.

[1] https://github.com/quantopian/alphalens


I will try to modify it such that it's easy to add factors. Thanks for sharing this.




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