I want to understand this code.
rm = r(:,1); % index returns rm_0 = rm - mean(rm); rf = r(:,2); % security returns rf_0 = rf - mean(rf); [p,h] = dcc_gjrgarch(r); % p is the conditional correlations % and h is the conditional variances sm = sqrt(h(:,1)); sf = sqrt(h(:,2)); rho = squeeze(p(1,2,:)); c = quantile(rm_0,a); z = sqrt(1 - rho.^2); u = rm_0 ./ sm; x = ((rf_0 ./ sf) - (rho .* u)) ./ z; r0_n = 4 / (3 * length(rm_0)); r0_s = min([std(rm_0 ./ sm) (iqr(rm_0 ./ sm) ./ 1.349)]); h = r0_s * r0_n ^0.2; f = normcdf(((c ./ sm) - u) ./ h); f_sum = sum(f); k1 = sum(u .* f) ./ f_sum; k2 = sum(x .* f) ./ f_sum; mes = -1 .* min((sf .* rho .* k1) + (sf .* z .* k2),0);""
Shakeel Sajjad
This code is calculating the minimum expected shortfall (MES) of a two-asset portfolio. The first part of the code creates variables for the returns of each asset (rm and rf) and subtracts the mean from each of them.
The dcc_gjrgarch function is then used to calculate the conditional correlations (p) and the conditional variances (h).
The variances are used to calculate the standard deviations (sm and sf) and the correlations are used to calculate the correlation coefficient (rho).
The next step is to calculate the quantile (c) and the standard deviation of the difference between the asset returns (z).
The u and x variables are then created by dividing the two asset returns by the standard deviations. The r0_n and r0_s variables are calculated by using the standard deviation of the asset returns and the interquartile range. The h variable is then calculated by multiplying the two.
The f variable is then created by calculating the cumulative normal distribution of the asset returns. The f_sum variable is then created by summing the f variable, and the k1 and k2 variables are then calculated by summing the u and x variables divided by the f_sum variable.
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