Dynamic Generation of Investment Recommendations Using Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{journals/ijimai/MartinQI21,

• author = "Carlos Martin and David Quintana and Pedro Isasi",
• title = "Dynamic Generation of Investment Recommendations Using Grammatical Evolution",
• journal = "International Journal of Interactive Multimedia and Artificial Intelligence",
• year = "2021",
• volume = "6",
• number = "6",
• pages = "104--111",
• month = jun,
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Dynamic Strategy, Evolutionary Computation, Finance, Structural Change, Trading",
• ISSN = "1989-1660",
• bibdate = "2021-06-01",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/ijimai/ijimai6.html#MartinQI21",
• URL = "https://www.ijimai.org/journal/sites/default/files/2021-05/ijimai_6_6_11.pdf",
• DOI = "doi:10.9781/ijimai.2021.04.007",
• size = "8 pages",
• abstract = "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 optimised 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.",
• notes = "Department of Computer Science and Engineering, Universidad Carlos III de Madrid, Leganes (Spain)",

}

Genetic Programming entries for Carlos Martin David Quintana Montero Pedro Isasi Vinuela

Citations