vollib.ref_python.black package
Subpackages
Submodules
vollib.ref_python.black.implied_volatility module
vollib.ref_python.black.implied_volatility
A library for option pricing, implied volatility, and greek calculation. vollib is based on lets_be_rational, a Python wrapper for LetsBeRational by Peter Jaeckel as described below.
- copyright:
© 2017 Gammon Capital LLC
- license:
MIT, see LICENSE for more details.
vollib.ref_python is a pure python version of vollib without any dependence on LetsBeRational. It is provided purely as a reference implementation for sanity checking. It is not recommended for industrial use.
- vollib.ref_python.black.implied_volatility.implied_volatility(price, F, K, r, t, flag)[source]
Returns the Black delta of an option.
- Parameters:
price (float)
F (float) – underlying futures price
K (float) – strike price
r (float) – annual risk-free interest rate
t (float) – time to expiration in years
flag (str) – ‘c’ or ‘p’ for call or put.
- Returns:
float
>>> F = 101.0 >>> K = 102.0 >>> t = .5 >>> r = .01 >>> flag = 'p' >>> sigma_in = 0.2
>>> price = black(flag, F, K, t, r, sigma_in) >>> expected_price = 6.20451158097 >>> abs(expected_price - price) < 0.00001 True
>>> sigma_out = implied_volatility(price, F, K, r, t, flag) >>> sigma_in == sigma_out or abs(sigma_in - sigma_out) < 0.00001 True
>>> F = 100 >>> K = 100 >>> sigma = .2 >>> flag = 'c' >>> t = .5 >>> r = .02
>>> discounted_call_price = black(flag, F, K, t, r, sigma) >>> iv = implied_volatility(discounted_call_price, F, K, r, t, flag)
>>> expected_discounted_call_price = 5.5811067246 >>> expected_iv = 0.2 >>> abs(expected_discounted_call_price - discounted_call_price) < 0.00001 True >>> abs(expected_iv - iv) < 0.00001 True
Module contents
vollib.ref_python.black
A library for option pricing, implied volatility, and greek calculation. vollib is based on lets_be_rational, a Python wrapper for LetsBeRational by Peter Jaeckel as described below.
- copyright:
© 2017 Gammon Capital LLC
- license:
MIT, see LICENSE for more details.
vollib.ref_python is a pure python version of vollib without any dependence on LetsBeRational. It is provided purely as a reference implementation for sanity checking. It is not recommended for industrial use.
- vollib.ref_python.black.N(x, *args, **kwds)
From John C. Hull, “Options, Futures and Other Derivatives,” 7th edition, Chapter 16.8, page 342
- vollib.ref_python.black.black(flag, F, K, t, r, sigma)[source]
Calculate the (discounted) Black option price.
- Parameters:
F (float) – underlying futures price
K (float) – strike price
sigma (float) – annualized standard deviation, or volatility
t (float) – time to expiration in years
>>> F = 100 >>> K = 100 >>> sigma = .2 >>> flag = 'c' >>> r = .02 >>> t = .5
>>> expected = 5.5811067246048118 >>> actual = black(flag, F, K, t, r, sigma) >>> abs(expected - actual) < 1e-12 True
- vollib.ref_python.black.black_call(F, K, t, r, sigma)[source]
Calculate the price of a call using Black. (Python implementation for reference.)
- Parameters:
F (float) – underlying futures price
K (float) – strike price
sigma (float) – annualized standard deviation, or volatility
t (float) – time to expiration in years
r (float) – risk-free interest rate
Hull, page 343, example 16.7
>>> F = 620 >>> K = 600 >>> r = .05 >>> sigma = .2 >>> t = 0.5 >>> calculated_value = black_call(F, K, t, r, sigma) >>> #44.1868533121 >>> text_book_value = 44.19 >>> abs(calculated_value - text_book_value) < .01 True
- vollib.ref_python.black.black_put(F, K, t, r, sigma)[source]
Calculate the price of a put using Black. (Python implementation for reference.)
- Parameters:
F (float) – underlying futures price
K (float) – strike price
sigma (float) – annualized standard deviation, or volatility
t (float) – time to expiration in years
r (float) – risk-free interest rate
Hull, page 338, example 16.6
>>> F = 20 >>> K = 20 >>> r = .09 >>> sigma = .25 >>> t = 4/12.0 >>> calculated_value = black_put(F, K, t, r, sigma) >>> # 1.11664145656 >>> text_book_value = 1.12 >>> abs(calculated_value - text_book_value) < .01 True
- vollib.ref_python.black.d1(F, K, t, r, sigma)[source]
Calculate the d1 component of the Black PDE.
- Parameters:
F (float) – underlying futures price
K (float) – strike price
sigma (float) – annualized standard deviation, or volatility
t (float) – time to expiration in years
r (float) – risk-free interest rate
Doctest using Hull, page 343, example 16.6
>>> F = 20 >>> K = 20 >>> r = .09 >>> t = 4/12.0 >>> sigma = 0.25
>>> calculated_value = d1(F, K, t, r, sigma) >>> #0.0721687836487 >>> text_book_value = 0.07216 >>> abs(calculated_value - text_book_value) < .00001 True
- vollib.ref_python.black.d2(F, K, t, r, sigma)[source]
Calculate the d2 component of the Black PDE.
- Parameters:
F (float) – underlying futures price
K (float) – strike price
sigma (float) – annualized standard deviation, or volatility
t (float) – time to expiration in years
r (float) – risk-free interest rate
Hull, page 343, example 16.6
>>> F = 20 >>> K = 20 >>> r = .09 >>> t = 4/12.0 >>> sigma = 0.25
>>> calculated_value = d2(F, K, t, r, sigma) >>> #-0.0721687836487 >>> text_book_value = -0.07216 >>> abs(calculated_value - text_book_value) < .00001 True