2/ Some examples off the top of my head: - MV=PQ - CAPM/Black-Scholes (Long Term Capital Management a prime example) - Recent Budish equations in modeling 51% attacks - Cardano's "provably secure"
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3/ Don't be fooled by white papers with lots of math. Don't be intimidated by them either. The more complex they are in trying to model reality, the higher the chance of them being wrong.
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4/ Math, to be useful, has to be grounded in reality. And equations often make a lot of implicit assumptions. Mathematical modeling could be useful, but always always question the assumptions.
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Objectivity of math pushes us to seek refuge in false precision that has short term gratification vs being directionally right which is unsexy.
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And this "false precision" gets more pronounced the further you move away from basic sciences, like Physics/Chemistry. This includes the majority of social sciences: Economics, Sociology etc. Any equation from these realms should be taken with a bowl of salt.

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Dude, stop being so anti social sciences and anti humanities. These tech bros always preaching STEM.....https://twitter.com/sarthakgh/status/1009611426275577856?s=21 …
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I actually love social sciences !
The possibilities are so complex that it's like an endless adventure. Take the Game Theory aspect of Bitcoin for example. The incentive structure is soooo simple yet the system it spawns is incredible... -
I think we've only scratched the surface in terms of Bitcoin's Game Theory. Budish paper might be wrong but it really opens up interesting questionshttps://medium.com/@hugonguyen/a-review-of-budishs-51-attack-theories-what-is-the-fair-price-of-an-old-asic-59a7dcf9ff94 …
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Bottom line: love social sciences as much as you want. Just don't be deluded by equations.
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