matlab计算期权隐含波动率的代码
时间: 2023-08-04 11:04:29 浏览: 223
计算期权隐含波动率的代码可以用MATLAB的Financial Toolbox中的blsimpv函数。blsimpv函数是根据Black-Scholes模型计算期权的隐含波动率的。
以下是一个示例代码:
```matlab
% 假设期权信息如下:
S = 100; % 标的资产价格
K = 100; % 行权价格
r = 0.05; % 无风险利率
T = 1; % 到期时间
MarketPrice = 10; % 期权市场价格
% 使用blsimpv函数计算隐含波动率
iv = blsimpv(S, K, r, T, MarketPrice);
% 显示计算结果
fprintf('隐含波动率为 %.4f\n', iv);
```
blsimpv函数的参数含义如下:
- S:标的资产价格
- K:行权价格
- r:无风险利率
- T:到期时间
- MarketPrice:期权市场价格
- iv:隐含波动率
相关问题
matlab计算期权隐含波动率的代码并画出波动率微笑图
计算期权隐含波动率的代码:
```matlab
function [iv, K] = implied_volatility(S, K, r, T, C, type)
% S: underlying asset price
% K: strike price
% r: risk-free interest rate
% T: time to maturity (in years)
% C: call option price
% type: 'call' or 'put'
tol = 1e-6;
max_iter = 100;
% Define the objective function
if strcmp(type, 'call')
obj_fun = @(sigma) (bsprice(S, K, r, T, sigma, type) - C)^2;
elseif strcmp(type, 'put')
obj_fun = @(sigma) (bsprice(S, K, r, T, sigma, type) - C)^2;
end
% Use fminbnd to find the implied volatility
[iv, ~, exitflag] = fminbnd(obj_fun, tol, 1, optimset('MaxIter', max_iter));
if exitflag ~= 1
warning('Implied volatility not found');
end
end
function [price, delta, gamma, vega, theta] = bsprice(S, K, r, T, sigma, type)
% S: underlying asset price
% K: strike price
% r: risk-free interest rate
% T: time to maturity (in years)
% sigma: volatility
% type: 'call' or 'put'
d1 = (log(S/K) + (r + 0.5*sigma^2)*T) / (sigma*sqrt(T));
d2 = d1 - sigma*sqrt(T);
if strcmp(type, 'call')
price = normcdf(d1)*S - normcdf(d2)*K*exp(-r*T);
delta = normcdf(d1);
gamma = normpdf(d1) / (S*sigma*sqrt(T));
vega = S*normpdf(d1)*sqrt(T);
theta = (-S*normpdf(d1)*sigma/(2*sqrt(T)) - r*K*exp(-r*T)*normcdf(d2)) / 365;
elseif strcmp(type, 'put')
price = normcdf(-d2)*K*exp(-r*T) - normcdf(-d1)*S;
delta = normcdf(d1) - 1;
gamma = normpdf(d1) / (S*sigma*sqrt(T));
vega = S*normpdf(d1)*sqrt(T);
theta = (-S*normpdf(d1)*sigma/(2*sqrt(T)) + r*K*exp(-r*T)*normcdf(-d2)) / 365;
end
end
```
其中,bsprice函数计算了Black-Scholes期权定价公式中的期权价格、希腊字母(delta、gamma、vega和theta),implied_volatility函数使用fminbnd函数寻找隐含波动率。
绘制波动率微笑图的代码:
```matlab
S = 100; % underlying asset price
K = [80:5:120]; % strike prices
r = 0.05; % risk-free interest rate
T = 1; % time to maturity (in years)
C = [20.54 16.06 12.36 9.36 7.05 5.30 4.03 3.11 2.46 1.99 1.68]; % call option prices
P = [1.39 3.10 5.15 7.13 9.08 10.98 12.76 14.34 15.68 16.78 17.63]; % put option prices
% Calculate implied volatilities for call options
iv_call = zeros(size(K));
for i = 1:length(K)
iv_call(i) = implied_volatility(S, K(i), r, T, C(i), 'call');
end
% Calculate implied volatilities for put options
iv_put = zeros(size(K));
for i = 1:length(K)
iv_put(i) = implied_volatility(S, K(i), r, T, P(i), 'put');
end
% Plot implied volatilities as a function of strike price
plot(K, iv_call, 'b-', K, iv_put, 'r-');
xlabel('Strike price');
ylabel('Implied volatility');
title('Volatility smile');
legend('Call options', 'Put options');
```
其中,我们假设有11个不同的行权价,对应的看涨期权和看跌期权的价格分别为C和P。我们使用implied_volatility函数计算每个行权价对应的隐含波动率,并绘制出波动率微笑图。
求隐含波动率MATLAB代码
在MATLAB中计算隐含波动率通常涉及到期权定价模型,如Black-Scholes模型。这里提供一个简化版的黑斯利-欧普特(Heston)模型的示例,该模型考虑了波动性的波动性,这会影响隐含波动率的估计。以下是一个基本的MATLAB代码片段:
```matlab
function implied_vol = heston_implied_vol(callPrice, strike, maturity, spot, riskFreeRate, sigma0, theta, kappa, rho, volVol)
% 参数定义
r = riskFreeRate;
T = maturity;
% Heston模型参数
S = spot; % 股票价格
v0 = sigma0^2; % 初始波动率平方
delta = sqrt(v0);
nu = kappa * (v0 - theta); % 稳定化项
d1 = (log(S / strike) + (r + 0.5 * v0) * T) ./ (delta * sqrt(T));
% 遍历寻找隐含波动率
tol = 1e-6; % 容忍误差
minVol = 0.01; % 最小波动率边界
maxVol = 1; % 最大波动率边界
implied_vol = fzero(@(vol)(blackScholes_call(callPrice, strike, maturity, S, r, vol) - callPrice), [minVol, maxVol], 'InitialGuess', delta);
end
% Black-Scholes公式计算欧式看涨期权价格
function bs_call = blackScholes_call(callPrice, K, T, S, r, sigma)
d2 = (log(S / K) + (r - 0.5 * sigma^2) * T) ./ (sigma * sqrt(T));
bs_call = callPrice * normcdf(d2) - exp(-r * T) * S * normcdf(d2 + sigma * sqrt(T));
end
```
这个函数`heston_implied_vol`接受实际期权价格、执行价格、到期时间、股票价格等输入,并尝试通过二分法找到满足Black-Scholes公式的价格的隐含波动率。
请注意,这只是一个简化的例子,实际使用时可能需要进一步处理边界条件、收敛性问题以及更复杂的金融工程库支持。另外,这个代码假设你已经安装了Financial Instruments Toolbox或类似的支持金融建模的工具箱。
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