When I came across your question, I decided to model the scenario myself. Here's what I did:
I chose NVDA’s daily pricing data from the beginning of 2020 until March as a case study, which I believe aptly illustrates the pattern you’re referring to—a drop in price following earnings.
Moving to the modelling phase, I didn't do any complex SDEs and instead opted for a basic outline using polynomial regression, with volatility represented by the standard deviation of rolling returns. A sequence of strike prices was established at 5-point intervals. Lacking historical options pricing data, I used the binomial pricing model to estimate the call option prices for these predetermined strikes.
On the 40th day, corresponding to February 11th, which marked the early stages of an upswing, I decided to engage in a bull call spread with long strike 65 and short one 75. And here's a payoff distribution throw all simulations.
This is a simplified example, and I'm someone relatively new to the world of options, my simulation was quite rudimentary and I even didn't include transaction costs, correct interest rate and etc. But, I hope it provides a glimpse into the mechanics of such a scenario.