Venkatesh Rao ☀️
@vgr
Just came up with a principle that may already have a name: Correlation-Liquidity Tradeoff (CLTO): The correlatedness of a speculative asset to an underlying value thesis and its liquidity form a tradeoff curve. Private startup stock has high correlation low liquidity. Crypto tokens have low correlatedness high liquidity. Former requires IRR fictions. Latter can experience wild excursions based on factors having nothing to do with the thesis. Between them is a Pareto frontier Came up with this idea from a weird angle. I was actually thinking about how reward schedule tempo is slower than decision tempo, causing problems in reinforcement learning. Eg you are a novelist who writes 1000 words everyday but the reward schedule is every 40k words when you finish and ship a novel and get market feedback. Or a robot trying sequences of actions to accomplish a task. It only actually gets a reward when it finds a satisficing sequence. Agile iteration can increase feedback rate but not necessarily reward rate.
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rafa
@rafa
I think what’s interesting is that both edges aren’t market-efficient,,, so Carta is working to get startup liquidity for their equity,,, and crypto solutions via lockup periods and better distributions are trying to get higher correlations — implying then that there’s a sweet spot range that current solutions don’t quite satisfy
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rafa
@rafa
Follow up: I also think that every point on the curve suffers from grass is always greener — no matter what position it’s always going to have a “could have more liquidity” or “could have more correlation” want
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Venkatesh Rao ☀️
@vgr
The machinery is beyond my literacy level but I’d like to see this thesis fleshed out and thought through. Maybe as a Protocolized essay. Interested?
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