风险管理KMV模型Matlab计算—-实例分析
2009-06-10 | 12:33分类: Optimization, Quant, matlab | 标签: KMV matlab |
编写自己编写的 KMVOptSearch
添加两个KMV模型文档 2009-6-5
http://www.business./gpennacc/MoodysKMV.pdf
http://www./Chapter_Pages/Data/Chicago/Kurbat_Paper.PDF
2009-8-14
程序内容将作为 金融数量分析的一节进行仔细讲解
6.2 KMV模型方程组的求解 77
6.2.1KMV模型简介 77
6.2.2KMV模型计算方法 78
6.2.3KMV模型计算程序 78
风险管理KMV模型Matlab计算—-实例分析
%test KMV
%r: risk-free rate
r=0.0425;
%T: Time to expiration
T=1;%输入 月数
%DP:Defaut point
%SD: short debt, LD: long debt
SD=1228109081;%输入
LD=30750000;%输入
%计算违约点
%DP=SD+0.5*LD;
DP=1.187*SD+1.367*LD;
%D:Debt maket value
D=DP;%债务的市场价值,可以修改
%theta: volatility
%PriceTheta: volatility of stock price
PriceTheta=0.1789;%(输入)
%EquityTheta: volatility of Theta value
EquityTheta=PriceTheta*sqrt(12);
%AssetTheta: volatility of asset
%E:Equit maket value
E=172330000;
%Va: Value of asset
%to compute the Va and AssetTheta
[Va,AssetTheta]=KMVOptSearch(E,D,r,T,EquityTheta)
%计算违约距离
DD=(Va-DP)/(Va*AssetTheta)
%计算违约率
EDF=normcdf(-DD)
运行testKMV
用文档中结果验证程序正确性,运算结果与文档中一致
Optimization terminated: first-order optimality is less than options.TolFun.
Va =
1.6362e+009
AssetTheta =
0.0689
DD =
1.2111
EDF =
0.1129
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