Rank Prediction for Portfolio Management Using Artificial Neural Networks

Jiyoon Bae, Ghudae Sim, Hyungbin Yun, Junhee Seok

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The rank of equities is often used to determine the investment portfolio instead of prices because ranking is in general believed to be robust. In this paper, we propose a rank prediction method for portfolio management using ANN. While an ANN requires a large dataset to train the model, the sample size is usually insufficient in stock market data. Therefore, the proposed method uses data augmentation and an ensemble ANN model. In the simulation study, the proposed method shows 13 percentage of performance improvement from the other methods to predict the profit rank of equities in South-East Asian market.

Original languageEnglish
Title of host publicationICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages15-17
Number of pages3
Volume2018-July
ISBN (Print)9781538646465
DOIs
Publication statusPublished - 2018 Aug 14
Event10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 - Prague, Czech Republic
Duration: 2018 Jul 32018 Jul 6

Other

Other10th International Conference on Ubiquitous and Future Networks, ICUFN 2018
CountryCzech Republic
CityPrague
Period18/7/318/7/6

Keywords

  • arfificial neural network
  • portfolio management
  • stock market prediction

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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  • Cite this

    Bae, J., Sim, G., Yun, H., & Seok, J. (2018). Rank Prediction for Portfolio Management Using Artificial Neural Networks. In ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks (Vol. 2018-July, pp. 15-17). [8436983] IEEE Computer Society. https://doi.org/10.1109/ICUFN.2018.8436983