Simple Portfolio Optimization Methods

Myopic, Constant or Buy-and-Hold and Dynamic Strategies to calculate the optimal portfolio weight.
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Mise à jour 11 fév. 2012

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This package allows you to calculate simple portfolio weights using the myopic, buy-and-hold or dynamic strategies.

To demonstrate how to use the simple portfolio optimization techniques, multiple paths are simulated based on various horizons. This will give the user the flexibility to adapt the code to its own preferences. In this tutorial we replicate some of the features of the discrete time Bellman equation. See Li and Ng (2001) and Van Binsbergen (2007).

The following assumptions are relevant:
- A tradeoff is made between the returns and the risk free rate 'rf'
- Weights are restricted between 0 and 1.

To calculate the optimal portfolios we make use of the following three steps:
1. simulate 'n' sample paths of 'k' periods of the asset returns and predictor variables
2. set up a portfolio grid (done inside the functions)
3. calculate the optimal portfolio

References:

B.F. Diris. Portfolio Management. Econometric Institute, 2012. Lecture FEM21010.

D. Li and W-L. Ng, 2001, Optimal Dynamic Portfolio Selection: Multiperiod Mean-Variance Formulation, Mathematical Finance, Volume 10 (issue 3).

Brand and Van Binsbergen, 2007, Optimal Asset Allocation in Asset Liability Management, NBER Working Paper No. 12970.

Citation pour cette source

Semin Ibisevic (2026). Simple Portfolio Optimization Methods (https://fr.mathworks.com/matlabcentral/fileexchange/35039-simple-portfolio-optimization-methods), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2010a
Compatible avec toutes les versions
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Version Publié le Notes de version
1.0.0.0