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Questions related to mathematical methods used for searching of optimal portfolio structures. Also related to questions on optimal structure of portfolios from both strategic and tactical point of view

1
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If you care most about selecting the assets, then I would suggest a (stochastic) Local Search. This is very much in the spirit of what Attack68 described, but very simple when it comes to search direc …
answered May 31 '19 by Enrico Schumann
2
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A problem very similar to yours is described -- including R code -- in a vignette of the NMOF package: http://cran.r-project.org/web/packages/NMOF/vignettes/LSselect.pdf For the Sharpe ratio, you sim …
answered Dec 13 '15 by Enrico Schumann
2
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There are many R code examples for portfolio selection and some for GARCH models in this book: @BOOK{Gilli2019, title = {Numerical Methods and Optimization in Finance}, publisher = {Els …
answered May 24 '20 by Enrico Schumann
5
votes
Following the comments and the edits to the question, I'll try to show how conditional Value-at-Risk (aka Expected Tail Loss) can be minimised for a portfolio. We start with the implementation sugges …
answered Apr 7 '20 by Enrico Schumann
1
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If you define VaR as a quantile of the portfolio's returns distribution about the mean of those returns, then the minimum-variance portfolio is what you look for: it minimises the volatility around th …
answered Dec 13 '19 by Enrico Schumann
2
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I doubt that there are papers that study exactly the set of constraints that you have listed. But there are papers that look, for instance, into specifications for risk and reward other than variance …
answered Oct 31 '17 by Enrico Schumann
2
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The third approach is the correct one. In general, one cannot aggregate partial moments of single assets into partial moments of the portfolio, as discussed for instance in this paper: @ARTICLE{Grootv …
answered Jan 5 '21 by Enrico Schumann
1
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You can handle this problem with scenario optimization: assume a matrix $R$ of returns, in which the rows are the scenarios and the columns are assets. For given portfolio weights $w$, you can compute …
answered Jan 5 '21 by Enrico Schumann
3
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For such a problem ("selecting n out of m") you can use optimisation heuristics. These algorithms work well even for large n and m, and they are flexible: you may as well select a portfolio that mini …
answered Dec 30 '13 by Enrico Schumann
2
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You could try a heuristic approach. The problem can be split into two nested optimisations: i) in the inner optimisation, given a set of selected assets, compute mean--variance efficient weights; ii) …
answered Mar 16 '17 by Enrico Schumann
2
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Regularisation means that you impose structure on your problem; structure that could not be recognised from the data sample alone. In the context of mean-variance optimisation, regularisation is most …
answered Mar 4 '19 by Enrico Schumann
4
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When returns follow an elliptical distribution (e.g. the Gaussian distribution), then minimising VaR and ES is equivalent to minimising variance. See https://people.math.ethz.ch/~embrecht/ftp/pitfalls …
answered Oct 30 '20 by Enrico Schumann
1
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An Empirical Analysis of Alternative Portfolio Selection Criteria and Risk-Reward Optimisation for Long-Run Investors: An Empirical Analysis look into alternative risk and reward specificatio …
answered Jan 13 '19 by Enrico Schumann
4
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I don't use fPortfolio but when I run your code example, I first get an error: ## Error in add.constraint() : could not find function "add.constraint" Nevertheless, after that, I can extract a soluti …
answered Aug 14 '21 by Enrico Schumann
1
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You need to factor borrowing costs into the scenarios (and the currently low interest rates help, so you may want to check with higher rates as well). Since you compute VaR from the scenarios, this w …
answered Feb 7 '19 by Enrico Schumann

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