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1 vote
1 answer
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How do I reformulate this max GMV ratio constraint in convex way?

Assuming I have N stocks. I want to have the following constraint in my optimization problem setup. $|x_i| \le \alpha \sum_{j}^N |x_j|$ where $\alpha$ is known, say 0.6. The intuition here is the GMV ...
inf's user avatar
  • 51
-3 votes
1 answer
173 views

sharpe ratio, convert into convex function, not understand that constraint, [duplicate]

I am reading about tranforming sharpe ratio into convex problem After some following, its converted into min xTxy s.t. (u-rf e)x = 1 ...
andy's user avatar
  • 1
2 votes
0 answers
201 views

Can genetic algorithm help in portfolio optimisation when convexity is not verifiable

I have the following portfolio cost function to maximise: $$ w^T\mu-\frac{1}{2}\gamma w^T\Sigma w+\frac{1}{6}\gamma^2 w^TM_3(w\otimes w), $$ which considers the co-skewness ($M_3$ tensor), $γ$ is the ...
Luigi87's user avatar
  • 326
7 votes
1 answer
3k views

Sharpe Maximization under Quadratic Constraints

When doing Sharpe optimization $$ \max_x \frac{\mu^T x}{\sqrt{x^T Q x}} $$ there is a common trick (section 5.2) used to put the problem in convex form. You add a variable $\kappa$ such that $x = ...
rhaskett's user avatar
  • 1,641
4 votes
2 answers
196 views

When would dedicated portfolios do better than 'immunized' portfolios?

We just learned about cash-matching through dedicated portfolios (using risk free bonds) in my class that concerned mathematical programming. However, in an aside one of the notes said: It should be ...
Supp's user avatar
  • 41