Enhanced indexation via chance constraints
| Autor: | Maria Elena Bruni, Patrizia Beraldi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Numerical Analysis
Mathematical optimization 050208 finance 021103 operations research Computer science Investment strategy Strategy and Management 05 social sciences 0211 other engineering and technologies Probabilistic logic Computational intelligence 02 engineering and technology Management Science and Operations Research Expected value Set (abstract data type) Computational Theory and Mathematics Management of Technology and Innovation Modeling and Simulation 0502 economics and business Benchmark (computing) Portfolio Statistics Probability and Uncertainty Indexation |
| Zdroj: | Operational Research. 22:1553-1573 |
| ISSN: | 1866-1505 1109-2858 |
| Popis: | The enhanced index tracking (EIT) represents a popular investment strategy designed to create a portfolio of assets that outperforms a benchmark, while bearing a limited additional risk. This paper analyzes the EIT problem by the chance constraints (CC) paradigm and proposes a formulation where the return of the tracking portfolio is imposed to overcome the benchmark with a high probability value. Besides the CC-based formulation, where the eventual shortage is controlled in probabilistic terms, the paper introduces a model based on the Integrated version of the CC. Here the negative deviation of the portfolio performance from the benchmark is measured and the corresponding expected value is limited to be lower than a given threshold. Extensive computational experiments are carried out on different set of benchmark instances. Both the proposed formulations suggest investment strategies that track very closely the benchmark over the out-of-sample horizon and often achieve better performance. When compared with other existing strategies, the empirical analysis reveals that no optimization model clearly dominates the others, even though the formulation based on the traditional form of the CC seems to be very competitive. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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