STOCK PORTFOLIO OPTIMIZATION FOR SEVERAL RISK MEASURES WITH A MULTI-OBJECTIVE APPROACH USING DIFFERENTIAL EVOLUTION ALGORITHM
This thesis discusses two different risk measurement models, Mean Variance model and Mean Absolute Deviation model, that are solved using the Differential Evolution algorithm. The constraints used in single objective portfolio optimization problem are Buy-In threshold, Cardinality and Roundlot. Mult...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/45147 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | This thesis discusses two different risk measurement models, Mean Variance model and Mean Absolute Deviation model, that are solved using the Differential Evolution algorithm. The constraints used in single objective portfolio optimization problem are Buy-In threshold, Cardinality and Roundlot. Multi objective problem with risk measures of Mean Variance and Mean Absolute Deviation solved using weighted sum method on LQ45 and Hangseng stocks index. The results obtained show that the differential evolution algorithm is quite good at solving stock portfolio optimization problems both single objective and multi objective. |
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