R help - Feb 2009 - Non-linear optimisation

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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Hi,

I don't understand your Matlab code.  However, let me say this:

 - you could use "L-BFGS-B" algorithm in optim() or nlminb(), if you
only have box constraints

 - you could use ConstrOptim(), if you only have linear inequality constraints

 - you could use Rdonlp2 if you have more general equality/inequality
constraints

Best,
Ravi.

____________________________________________________________________

Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University

Ph. (410) 502-2619
email: rvaradhan at jhmi.edu


----- Original Message -----
From: ehxpieterse <eduard.pieterse at macquarie.com>
Date: Thursday, February 5, 2009 2:03 pm
Subject: [R]  Non-linear optimisation
To: r-help at r-project.org

>  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
>  
>  
>  -- 
>  View this message in context: 
>  Sent from the R help mailing list archive at Nabble.com.
>  
>  ______________________________________________
>  R-help at r-project.org mailing list
>  
>  PLEASE do read the posting guide 
>  and provide commented, minimal, self-contained, reproducible code.

Hi Ravi,

To give you some background:

The function compute_strategy_before_fees returns portfolio returns and
standard deviation. Our optimal portfolio will maximise the returns whilst
keeping the standard deviation at a certain level.

We have an input matrix C that the function uses to calculate the asset
weights in the portfolio over time. Problem is that I am a complete R novice
and would not know where to start in optimising this in R.

Could you please give some guidance on using the R functions?

Thanks,
Eduard 

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