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Improving MATLAB® performance when solving financial optimization problems

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Improving MATLAB® performance when solving financial optimization problems



03 Nov 2011 (Updated )

Jorge Paloschi,PHD and Sri Krishnamurthy,CFA May 2011

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Optimization algorithms are commonly used in the financial industry with examples including Markowitz portfolio optimization, Asset-Liability management, credit-risk management, volatility surface estimation etc. Many optimization problems involve nonlinear objective functions and constraints. These problems can be computationally expensive, especially with numerically estimated gradients. We have seen many cases where optimizations were sped up by incorporating pre-computed analytical derivatives.
In the Wilmott Magazine May 2011 article, we illustrate how optimization problems can be sped up using this approach with MATLAB® and Symbolic Math Toolbox™.

A copy of the article is included in the submission

Required Products Curve Fitting Toolbox
Financial Toolbox
Optimization Toolbox
Symbolic Math Toolbox
MATLAB release MATLAB 7.12 (R2011a)
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31 May 2016 liu lei  
01 Sep 2016

Updated license

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