# [R] Non-linear optimisation

ehxpieterse eduard.pieterse at macquarie.com
Thu Feb 5 18:28:00 CET 2009

```Hi there,

I have a piece of Matlab code I use to optimise a trding strategy. If there
are any Matlab/R specialists out there, I would appreciate your help in
doing the exact same optimisation in R.

I suspect I would use nlm() in R but am not sure where to define my
constraints.

I have attached my Matlab code below for reference.

Many thanks.

Constraints
function [c,ceq]=TriskellConstraints(X)
global objFunc_vol;
[a,b] = objFunc_vol(X);
c(1) = b-6.5;
c(2) = std(X(:))-6.5;
ceq = [];
end

Optimise
global objFunc_vol
objFunc_vol = @(C) compute_strategy_before_fees(prices, C, floor, cap,
m_ret_reb, prices_TR, hedge_fund, vg, euribor, last_reb_date, Maturity,
fixed_fees, var_fees);

objFunc_vol(C);

objFunc = @(C) compute_strategy_before_fees(prices, C, floor, cap,
m_ret_reb, prices_TR, hedge_fund, vg, euribor, last_reb_date, Maturity,
fixed_fees, var_fees);

objFunc(C);

options = optimset('MaxIter',10000000,'MaxFunEvals',10000000);

tic;

% OPTIMISE

%M =
fmincon(objFunc,C,[],[],[],[],repmat(-20,12,9),repmat(20,12,9), at TriskellConstraints,options);
M =
fmincon(objFunc_vol,C,[],[],[],[],repmat(-20,12,9),repmat(20,12,9), at TriskellConstraints,options);
[Z, ZZ] = compute_strategy_after_fees(prices, C, floor, cap, m_ret_reb,
prices_TR, Hedge_Fund, vg, euribor, last_reb_date, Maturity, fixed_fees,
var_fees, dates, variation_cap_property, eurusd);
[Y, YY] = compute_strategy_after_fees(prices, M, floor, cap, m_ret_reb,
prices_TR, Hedge_Fund, vg, euribor, last_reb_date, Maturity, fixed_fees,
var_fees, dates, variation_cap_property, eurusd);

timespent = toc/60; %converts to minutes

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