I have tested Python and pre-defined web implementations of the Black-Scholes options pricing model.

From these tests I've observed pricing differences between the model's output and real options prices (AAPL used for tests).

The difference is small for very near-term options such as weeklys, but once I extend out to 60+ days the price difference is huge.

This doesn't overly surprise me but I'd like to know why. My current thoughts are:

1. Uncertaintry of short-term interest rates
2. Uncertainty around future volatility
3. Supply/demand for different strikes

Can anyone please help explain this? Additional detail on how I can help account for these differences when simulating options prices would be extra helpful.

I have tested Python and pre-defined web implementations of the Black-Scholes options pricing model.

From these tests I've observed pricing differences between the model's output and real options prices (AAPL used for tests).

The difference is small for very near-term options such as weeklys, but once I extend out to 60+ days the price difference is huge.

This doesn't overly surprise me but I'd like to know why. My current thoughts are:

1. Uncertainty of short-term interest rates
2. Uncertainty around future volatility
3. Supply/demand for different strikes

Can anyone please help explain this? Additional detail on how I can help account for these differences when simulating options prices would be extra helpful.