This is why banks fail. Just kidding.... :-P Estimated Sharpe for a trade would be what you think the return should be (e.g. fair market value - current price)

This is why banks fail. Just kidding.... :-P Estimated Sharpe for a trade would be what you think the return should be (e.g. fair market value - current price) divided by the estimated future variance. This is what you estimate for VAR and compare to your risk tolerance. The eventual accuracy of the estimates will determine whether it's a ho-hum trade or a black swan that wipes you out. Black swans are essentially situations in which variance estimates were completely wrong (as opposed to return estimates). Variance is a function of a bunch of things (and correlated with every damn thing). Simply taking historical variance and assuming it will be the same in the future is the laziest possible solution. Black Swan events have woken people up to platykurtic Gaussians and the fact that many real life distributions aren't even Gaussian. This is why you use Monte Carlo, because it doesn't need to assume a kurtosis or even Gaussianity, but is more computationally intensive, but not terribly so, but also suffers from low sample number at the tails, so it's not that accurate in extreme situations either. An additional red flag is that, if you have to use MC, then you don't know the distribution underlying the process, and if you don't know that there might be other things you don't know. Crypto is one of the newest markets, so we understand a lot less about its extreme conditions and the tails are very uncertain. Even with Monte Carlo I wouldn't trust crypto Sharpes one iota. Sorry if you know all this stuff. Thought I should clarify where we probably actually agree but may be thinking of it differently.