Dynamic Generation of Investment Recommendations Using Grammatical Evolution
Autor:
Martín, Carlos
; Quintana, David
; Isasi, Pedro
Fecha:
06/2021Palabra clave:
Revista / editorial:
International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)Tipo de Ítem:
articleDirección web:
https://www.ijimai.org/journal/bibcite/reference/2937Resumen:
The attainment of trading rules using Grammatical Evolution traditionally follows a static approach. A single rule is obtained and then used to generate investment recommendations over time. The main disadvantage of this approach is that it does not consider the need to adapt to the structural changes that are often associated with financial time series. We improve the canonical approach introducing an alternative that involves a dynamic selection mechanism that switches between an active rule and a candidate one optimized for the most recent market data available. The proposed solution seeks the flexibility required by structural changes while limiting the transaction costs commonly associated with constant model updates. The performance of the algorithm is compared with four alternatives: the standard static approach; a sliding window-based generation of trading rules that are used for a single time period, and two ensemble-based strategies. The experimental results, based on market data, show that the suggested approach beats the rest.
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Editor's Note
Golpe, Antonio A.; Isasi, Pedro; Martín-Álvarez, Juan-Manuel; Quintana, David (03/2022)Machine learning (ML) is generating new opportunities for innovative research in areas apparently unrelated such as, economics, business or/and finance. Specifically, it has also been widely used in applications related ... -
Editor's Note
Golpe, Antonio A.; Isasi, Pedro; Martín Álvarez, Juan M. ; Quintana, David (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 2022)Machine learning (ML) is generating new opportunities for innovative research in areas apparently unrelated such as, economics, business or/and finance [1]. Specifically, it has also been widely used in applications related ... -
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