A Multiobjective Optimization Approach for Market Timing
| Autor: | Ismail Mohamed, Fernando E. B. Otero |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Operations research
Computer science Financial market Particle swarm optimization 0102 computer and information sciences 02 engineering and technology Market timing computer.software_genre 01 natural sciences Multi-objective optimization Profit (economics) Domain (software engineering) 010201 computation theory & mathematics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Q335 Algorithmic trading Crucial point computer |
| Zdroj: | GECCO |
| Popis: | The introduction of electronic exchanges was a crucial point in history as it heralded the arrival of algorithmic trading. Designers of such systems face a number of issues, one of which is deciding when to buy or sell a given security on a financial market. Although Genetic Algorithms (GA) have been the most widely used to tackle this issue, Particle Swarm Optimization (PSO) has seen much lower adoption within the domain. In two previous works, the authors adapted PSO algorithms to tackle market timing and address the shortcomings of the previous approaches both with GA and PSO. The majority of work done to date on market timing tackled it as a single objective optimization problem, which limits its suitability to live trading as designers of such strategies will realistically pursue multiple objectives such as maximizing profits, minimizing exposure to risk and using the shortest strategies to improve execution speed. In this paper, we adapt both a GA and PSO to tackle market timing as a multiobjective optimization problem and provide an in depth discussion of our results and avenues of future research. |
| Databáze: | OpenAIRE |
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