def rho(flag, S, K, t, r, sigma):
"""Return Black-Scholes rho of an option.
:param S: underlying asset price
:type S: float
:param K: strike price
:type K: float
:param sigma: annualized standard deviation, or volatility
:type sigma: float
:param t: time to expiration in years
:type t: float
:param r: risk-free interest rate
:type r: float
:param flag: 'c' or 'p' for call or put.
:type flag: str
The text book analytical formula does not multiply by .01,
but in practice rho is defined as the change in price
for each 1 percent change in r, hence we multiply by 0.01.
Example 17.7, page 368, Hull:
>>> S = 49
>>> K = 50
>>> r = .05
>>> t = 0.3846
>>> sigma = 0.2
>>> flag = 'c'
>>> rho_calc = rho(flag, S, K, t, r, sigma)
>>> # 0.089065740988
>>> rho_text_book = 0.0891
>>> abs(rho_calc - rho_text_book) < .0001
True
"""
d_2 = d2(S, K, t, r, sigma)
e_to_the_minus_rt = numpy.exp(-r*t)
if flag == 'c':
return t*K*e_to_the_minus_rt * cnd(d_2) * .01
else:
return -t*K*e_to_the_minus_rt * cnd(-d_2) * .01
def theta(flag, S, K, t, r, sigma):
"""Return Black-Scholes theta of an option.
:param S: underlying asset price
:type S: float
:param K: strike price
:type K: float
:param sigma: annualized standard deviation, or volatility
:type sigma: float
:param t: time to expiration in years
:type t: float
:param r: risk-free interest rate
:type r: float
:param flag: 'c' or 'p' for call or put.
:type flag: str
The text book analytical formula does not divide by 365,
but in practice theta is defined as the change in price
for each day change in t, hence we divide by 365.
Example 17.2, page 359, Hull:
>>> S = 49
>>> K = 50
>>> r = .05
>>> t = 0.3846
>>> sigma = 0.2
>>> flag = 'c'
>>> annual_theta_calc = theta(flag, S, K, t, r, sigma) * 365
>>> # -4.30538996455
>>> annual_theta_text_book = -4.31
>>> abs(annual_theta_calc - annual_theta_text_book) < .01
True
Using the same inputs with a put.
>>> S = 49
>>> K = 50
>>> r = .05
>>> t = 0.3846
>>> sigma = 0.2
>>> flag = 'p'
>>> annual_theta_calc = theta(flag, S, K, t, r, sigma) * 365
>>> # -1.8530056722
>>> annual_theta_reference = -1.8530056722
>>> abs(annual_theta_calc - annual_theta_reference) < .000001
True
"""
two_sqrt_t = 2 * numpy.sqrt(t)
D1 = d1(S, K, t, r, sigma)
D2 = d2(S, K, t, r, sigma)
first_term = (-S * pdf(D1) * sigma) / two_sqrt_t
if flag == 'c':
second_term = r * K * numpy.exp(-r*t) * cnd(D2)
return (first_term - second_term)/365.0
if flag == 'p':
second_term = r * K * numpy.exp(-r*t) * cnd(-D2)
return (first_term + second_term)/365.0