Risk management KMV model Matlab computing-instance analysis

Add two KMV Model Documents

Http://www.business.uiuc.edu/gpennacc/MoodysKMV.pdf

Http://www.prmia.org/Chapter_Pages/Data/Chicago/Kurbat_Paper.PDF

Risk management KMV model Matlab computing-instance analysis

% Test KMV
% R: risk-free rate
R = 0.0425;

% T: Time to expiration
T = 1; % enter the number of months

% DP: defaut point
% SD: Short debt, LD: Long Debt
SD = 1228109081; % Input
LD = 30750000; % Input
% Calculate default point
% Dp = sd + 0.5 * LD;
Dp = 1.187 * sd + 1.367 * LD;
% D: debt maket Value
D = DP; % market value of debt, which can be modified

% Theta: Volatility
% Pricetheta: Volatility of Stock Price
Pricetheta = 0.1789; % (input)
% 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)

% Calculates the default distance
Dd = (va-DP)/(VA * assettheta)
% Calculate Default Rate
EDF = normcf (-dd)

 

RUN testkmv
verify the Program with the results in the document. The calculation results are consistent with those in the Document.
optimization terminated: first-order optimality is less than options. tolfun.
Va =
1.6362e + 009
assettheta =
0.0689
dd =
1.2111
EDF =
0.1129
>>< br> the kmvoptsearch function is not provided, and the function is sold for 800 RMB, email Contact ariszheng@Gmail.com