Merton Structural Credit Model (Matrixwise Solver)

버전 (2.9 KB) 작성자: Mark Whirdy
Matrixwise Calculation Firm Asset Value, Volatility, Debt Value, Spread, Default Prob, Exp-Recovery
다운로드 수: 1.8K
업데이트 날짜: 2013/5/14

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Calculates the Value of Firm Assets, Volatility of Firm Assets,
Debt-Value, Credit-Spread, Default Probability and Recovery Rate as per
Merton's Structural Credit Model. The value and volatility of firm assets
are found by Bivariate Newton Root-Finding Method of the Merton
Simultaneous Equations. The Newton Method is carried out matrixwise
(i.e. fully vectorised) in a 3d Jacobian so that bivariate ranges of
(E_t,sig_E,K,T) values may simultaneously calculated. (See Examples)

Function requires mtimesx.m available on the Matlab File Exchange at

A_t: Value of Firm's Assets [A_t = Call(K,sig_A,A_t,t,T,r)]
sig_A: Volatility of Firm's Assets
D_t: Value of Firm Debt [D_t = pv(K) - Put(K,sig_A,A_t,t,T,r)]
s: Credit Spread
p: Default Probability
R: Expected Recovery
d: Black-Scholes Parameter Anonymous Function

E_t: Value of Equity
sig_E: Equity Volatility
K: Debt Barrier
t: Estimation Time (Years)
T: Maturity Time (Years)
r: Risk-free-Rate

Example 1
T = 5;
t = 0;
K = 500;
sig_E = 0.5;
r = 0.05;
E_t = 1200;
[A_t,sig_A,D_t,s,p,R,d1] = calcMertonModel(E_t,sig_E,K,t,T,r);

Example 2: Variates (sig_E,E_t)
t = 0; r = 0.05;
sig_E = (0.05:0.05:0.8)'; E_t = (100:100:2000)';
[sig_E,E_t] = meshgrid(sig_E,E_t);
K = repmat(600,size(sig_E)); T = repmat(5,size(sig_E));
[A_t,sig_A,D_t,s,p,R,d1] = calcMertonModel(E_t,sig_E,K,t,T,r);

Example 3: Variates (K,T)
t = 0; r = 0.05;
K = (100:100:4000)'; T = (0.1:0.1:10)';
[K,T] = meshgrid(K,T);
sig_E = repmat(0.4,size(K)); E_t = repmat(1300,size(K));
[A_t,sig_A,D_t,s,p,R,d1] = calcMertonModel(E_t,sig_E,K,t,T,r);

인용 양식

Mark Whirdy (2024). Merton Structural Credit Model (Matrixwise Solver) (, MATLAB Central File Exchange. 검색됨 .

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버전 게시됨 릴리스 정보

Removed fsolve dependency (Optim Toolbox) for efficiency increase (even in scalar inputs case)

Full Code re-factorization to facilitate matrixwise calculation of bivariate ranges of {E_t,sig_E,K,T} values using 3d Newton Jacobian solution.

Added the Black-Scholes Parameter Anonymous Function Handle as an Output to allow for further analysis (sensitivity, greeks etc)

d = @(z,A_t,sig_A,T,t,K,r)((1/(sig_A*sqrt(T-t)))*(log(A_t/K) + (r + (z)*0.5*sig_A^2)*(T-t)));

z = +1/-1

Minor code refactoring, code returns the Black-Scholes Parameter to allow for further sensitivity analysis & calculation of greeks

d = @(z,A_t,sig_A,T,t,K,r)
z=+1/-1 for Call/Put

Added Expected-Recovery calclulation

[A_t,sig_A,D_t,s,p,R] = calcMertonModel(E_t,sig_E,K,t,T,r);