> Can you tell me what is the performance and model accuracy trade off between Monte-Carlo option pricing vs. BSM vs. Binomial vs. Heston. I don't work in fina

> Can you tell me what is the performance and model accuracy trade off between Monte-Carlo option pricing vs. BSM vs. Binomial vs. Heston. I don't work in finance anymore, but Heston is not a pricing method per say. In the linked article, the OP assumes that the price of a bitcoin follows a lognormal distribution (i.e: dS_t = mudt + sigmadW_t), while Heston assumes a different diffusion process (dS_t = mudt + digma_tdW_t, and d(sigma_t) = kappa(thau - sigma_t)dt+ zetasqrt(sigma_t) dW'_t) [0]. I would say that Monte Carlo is in general slower and less accurate than the other methods you mentionned, but more flexible in the sense that it allows more complicated diffusion models or payoffs (e.g: option on the max or min of a basket of underlyings). [0]: https://en.wikipedia.org/wiki/Heston_model https://en.wikipedia.org/wiki/Heston_model