A quant trading question I’ve never found a good answer to — how to decide between spending time improving an existing strategy (high certainty, low return on effort) vs starting something entirely new (uncertain but potentially high return on effort).
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I take a modular/alpha factory approach. A novel signal can usually be combined with existing risk, entry, execution etc. - if compute resources aren't a constraint you can test a lot of ideas continuously and quickly this way.
I do that for eg all strategies that fit within a framework (eg futures trading with up to a 1 minute rebalance). But what about stuff that fits outside the framework, eg should I start looking at equities, or crypto, or NDFs?
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Negative Rate Stablecoin CDPs is all u should be concerning yourself with Find me a stray that consistently outperforms 50% Apr on USDC and I’ll quit DeFi
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*strategy
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Is your example a matter of applying the same framework to a different universe, instead of an entirely different framework (i.e event-driven time series vs periodical rebalancing cross sectional stuffs)?
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I hope to be able to do the latter.
My hunch is having a different framework/approach can create more truly uncorrelated strategies, because there are only so many ways to slice and dice using an existing framework. - Show replies
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I mean I admit I try to take a "markets are markets" first principles approach and then watch what goes wrong on a paper account and mold asset-specific approaches based on that feedback
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Growing AUM is pretty much always the priority as it results in more profits vs squeezing extra 1-2% annualized from strats
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