To be fair, I said “not much doubt”, but let’s say you thought you had a high chance of -2% and a low chance of +2% depending on what happens across earnings or similar. On one hand, it’ll be hard to get enough data to be sure the odds really are say 4:1 in your favor or whatever, but on the other hand, if you keep putting on the bearish trades and more than 2 go against you before you’re making money, you know something’s probably wrong with your model.
I actually see that as using a bayesian approach to statistics. Maybe not as formal, but still utilizing some form of statistics there. I can't say for certain how you formulated your priors (E(u_t+1|earnings) = -2%) > E(u_t+1|earnings) = +2%), but again, though it may not be formal, I would think there was a lot of historical data already that went into those formulations (led you to those beliefs).
FWIW, I am a bigger proponent of bayesian approaches over frequentist, when it comes to trading and markets.
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