Documentation of the functions

[tngn]

Thanks for pythonizing the code.
I read the paper as well as this project's Home pag and the LetsBeRational.py source file, which details functions such as:
def implied_volatility_from_a_transformed_rational_guess(price, F, K, T, q):

From other documents and papers i was able to guess variables such as F,K,T, but unable to guess what input/argument q is. The same issue for def normalised_black(x, s, q): what are x,s?

Could anyone in the know give some explanations, and/or examples of how to use these functions?

[lbrichards]

q is the binary flag which appears as theta in Let's be Rational. The following code is found in py_vollib/helpers/init.py

CALL = 'c'
PUT = 'p'
binary_flag = {CALL:1,PUT:-1}

x is log moneyness (ln(F/K)), as defined in Let's Be Rational, Equation 2.1.

s denotes the sigma in Equation 2.2, which means "implied volatility times the square root of time till expiration (in years)"

Functions such as normalised_black() and implied_volatility_from_a_transformed_rational_guess() are more about internal implementation rather than the client programmer's API. For the latter, I recommend you look at py_vollib.Black, py_vollib.Black.greeks., etc. The doctests and unit tests contain lots of examples.