Quantamental seems to be a growing sector in the money mgmt business. I've been paying very careful attention to it recently. I've seen cases from adding "fundamental" data with "quantitative" data to run some financial economics models. I've also seen variety of machine learning methodologies. I've also seen a mix of financial economics and machine learning methodologies. I've also heard that there are certain regulatory limitations on what can be done.
So I wanted to ask two things.
1) What are the biggest trends in Quantamental? In what ways are people mixing fundamental with quantitative?
2) What are some regulatory hurdles when trying to push out-of-box ideas as an actual way to manage money, manage index funds, etc...?
Hi Milton Friedchickenman, the silence is deafening, sorry about that.... Any of the threads below helpful?
If those topics were completely useless, don't blame me, blame my programmers...
I cannot speak to quantamental investing, but in public AM the big trend recently has been quantitative factors. I.E. the fund will invest in stocks (or bonds) that exhibit a certain set of characteristics like value or a strong balance sheet. (commonly called "quality") Some of the major players are even getting into factor timing, trying to bet on factors that they think will outperform in the short-run.
As to regulatory hurdles, there are few to none. You can structure it as a conventional 40-act mutual fund in the US, but can run into tax problems if the turnover is too high. Frequently these are structured as ETFs to take advantage of the ETF creation/redemption tax efficiency. Generally the options are to turn your model into an index, or make it transparent active. ANT ETFs have some turnover problems most of the time.
Obviously, this is greatly simplified. Talk to your legal and compliance departments to go through all the details. There are a number of hurdles you need to jump like getting exemptive relief from the SEC and whatnot.
alt data for fundamental funds, credit card/web traffic data. Regulatory hurdles include privacy and governance
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