HF Strategies protected from quants
Interested in hearing views on which strats in the future that humans will retain an edge in. I'm thinking merger arb (and other event-driven), distressed sovereign debt analysis and discretionary global macro.
Interested in hearing views on which strats in the future that humans will retain an edge in. I'm thinking merger arb (and other event-driven), distressed sovereign debt analysis and discretionary global macro.
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Traditional long/short equity remains pretty well protected... it is pretty low return on investment for most quants to automate discretionary strategies, there are systematic strategies that lend themselves much better to automation, which is where most of the quantitative talent is focused on.
You just picked the most likely candidate for least protected...?
Should clarify my point, I agree long/short equity is the least protected, I was just trying to point out that even the most likely candidate for being competed out is not at much risk.
Too many people panic about losing their edge to quants, when the reality is quant equity is quite different from discretionary long/short and there is plenty of room for both. Just look at how low the absolute correlations are on the returns of major multi-managers running traditional long/short vs. major quant equity shops.
I think you probably hit the nail on the head with distressed credit and discretionary global macro. The most likely candidate is probably the l/s space because there's just simply too much covariance between equities (even cross-industry) to be resistant to mean reverting algo trading and other strategies that I'm not nearly smart enough to understand. I think any platform that plays in an activist/distressed credit/global macro strategy space will be quant resistant because there's simply too much human element to the terms negotiated in those deals. I can kind of see a world where global macro becomes subject to increased quantitative presence when ML (and our understanding of it, if it's not already there) is at a place that allows for live time multi-media information aggregation which is subsequently used as inputs for an algo that trades correlated equities. Sounds kind of dystopian but also pretty sick.
Edit: Any thoughts regarding the global macro bit? Is this already a thing/in the works? Broadly interested in the extent to which AI/ML can be instituted into the traditional HF/AM space.
Would be shocked if a weaker form of your hypothesised global macro system doesn’t already exist, e.g. using curated NLP models to pull out sentiment data as well as the raw numbers regarding monetary policy from central bank statements/news reports etc. At that point you also grab your equities fundamentals/sentiment/whatever other relevant alternative data you can get your hands on along with good ‘ole exchange data, and use it to power an equities l/s statarb system.
If you’ve designed the system well enough it will be able to pick up on historical events which are correlated to price movement (idk maybe country X and Y increasing interest rates often leads to equity Z underperforming relative to its sector) but I don’t think we’re anywhere near your dystopia where there exists a machine general intelligence capable of formulating novel theses by combining information from multiple news sources as well as people.
If you have to ask/ponder this you do not belong in a hedge fund environment. The top HFs keep adapting and changing, no one keeps with the same strategy to survive. This is why L/S guys have private arms now, why quant funds moved to some global macro with the possible upcoming inflation cycle. Quant funds have got their arse handed to them the last 2-3 years and are learning they need to adapt as well.
The reason merger arb funds dont exist anymore aint technology its cause they didnt adapt and died out.
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Not following you here, and disagree with what you are saying. What you are saying about complex models and ability to automate is just wrong.
Seconded
You're the expert, not me, so care to explain how you do predictions/classifications on very little data? Obviously without going into too much detail.
I tried to clarify the comment
This is patently false. There are quant funds crushing it w/ 1mo+ average hold times. Quant funds arn't restricted to a certain frequency and many trade much slower than most would expect. Remember, you can only scale so much with 1d hold times, and there are a lot of BIG quant funds (both by AUM and GMV).
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