原文链接：http://www.cnblogs.com/wn19910213/p/5103819.html

 1 from math import log,sqrt,exp
 2 from scipy import stats
 3 
 4 def bsm_call_value(S0,K,T,r,sigma):
 5     S0 = float(S0)
 6     d1 = (log(S0 / K) + (r + 0.5 * sigma ** 2) * T) / (sigma * sqrt(T))
 7     d2 = (log(S0 / K) + (r - 0.5 * sigma ** 2) * T) / (sigma * sqrt(T))
 8     value = (S0 * stats.norm.cdf(d1,0.0,1.0) - K * exp(-r * T) * stats.norm.cdf(d2,0.0,1.0))
 9     print value
10     return value
11 
12 def bsm_vega(S0,K,T,r,sigma):
13     S0 = float(S0)
14     d1 = (log(S0 / K) + (r + 0.5 * sigma ** 2) * T) / (sigma * sqrt(T))
15     vega = S0 * stats.norm.cdf(d1,0.0,1.0) * sqrt(T)
16     return vega
17 
18 def bsm_call_imp_vol(S0,K,T,r,C0,sigma_est,it = 100):
19     for i in range(it):
20         sigma_est -= ((bsm_call_value(S0,K,T,r,sigma_est) - C0) / bsm_vega(S0,K,T,r,sigma_est))
21     print sigma_est
22     return sigma_est
23 
24 S0 = 100
25 K = 105
26 T = 1.0
27 r = 0.05
28 sigma = 0.2
29 bsm_call_value(S0,K,T,r,sigma)

 

转载于:https://www.cnblogs.com/wn19910213/p/5103819.html