Test
发布于: 22 分钟前
LaTeX 测试
BSM(τ,x,K,r,σ)=xN(d+(τ,x))−e−rτKN(d−(τ,x))(4.11)
C++测试
#include <iostream>
using namespace std;
int main()
{
cout << "Hello, InfoQ" << endl;
return 0;
}
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Python 测试
import math
import numpy as np
from scipy.stats import norm
//定义以下简写变量
//K: strikePrice
//T: maturity
//S_t: spotPrice
//vol: volatility
//r: riskFreeRate
//定义d1和d2
def d1f(K, T, S_t, vol, r) :
return math.pow(vol * np.sqrt(T), -1) * \
(np.log(S_t / K) + (r + 0.5 * math.pow(vol, 2) * np.sqrt(T)))
def d2f(K, T, S_t, vol, r) :
return d1f(K, T, S_t, vol, r) - vol * np.sqrt(T)
//定义看涨-看跌期权计算公式
def blackScholesCallPrice(K, T, S_t, vol, r) :
d1 = d1f(K, T, S_t, vol, r)
d2 = d2f(K, T, S_t, vol, r)
callPrice = norm.cdf(d1) * S_t - norm.cdf(d2) * K * np.exp(-r * T)
return callPrice
def blackScholesPutPrice(K, T, S_t, vol, r) :
d1 = d1f(K, T, S_t, vol, r)
d2 = d2f(K, T, S_t, vol, r)
putPrice = norm.cdf(-d2) * K * np.exp(-r * T) - norm.cdf(-d1) * S_t
return putPrice
//定义看涨-看跌期权平价测试公式
def callPutParity(K, T, S_t, r) :
return S_t - np.exp(-r * T) * K
//对给定变量进行测试
K = 100.0
S_t = 110.0
vol = 0.1
r = 0.03
T = 0.5
call = blackScholesCallPrice(K, T, S_t, vol, r)
put = blackScholesPutPrice(K, T, S_t, vol, r)
callPutParity_ = callPutParity(K, T, S_t, r)
print("The call option price is: {0}".format(call))
print("The put option price is: {0}".format(put))
print("Call price - put price is: {0}".format(call - put))
print("The Call-Put-Parity is: {0}".format(callPutParity_))
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测试写作内容常用语言及代码高亮,够 50 个字了吧?不够的话我再写,还不够?再继续打几个字。还不够?是的,继续继续继续。哈哈哈哈哈
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发布于: 22 分钟前阅读数: 2
bobcatzoo
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