Extending the Omega model with momentum and reversal strategies to intraday trading.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 13 02 2023
accepted: 22 08 2023
medline: 11 9 2023
pubmed: 8 9 2023
entrez: 8 9 2023
Statut: epublish

Résumé

This study develops the Omega model integrated with momentum and reversal strategies using high-frequency data on the component stocks of the S&P 500 Index and the NASDAQ 100. The Omega model based on the momentum strategy (M_Omega), the reversal strategy (R_Omega), and both strategies (M_R_Omega) are designed to simulate trading over three periods. The portfolio is rebalanced every transaction day to optimize asset allocation by incorporating intraday winners or losers' information and trading cost. The study finds that the proposed models generate positive returns (net of trading costs), in spite of fact that intraday trading frequently erodes profits. The M_Omega and R_Omega models produce a higher return than that of the S&P 500 index or NASDAQ 100 index, considering the intraday trading cost. The performance of the Omega model integrated with the momentum or reversal strategy is more profitable in a volatile market or period. The M_Omega and R_Omega reach the highest final market value from 2020 to 2021, when COVID 19 pandemic emerged. The rebalancing of the momentum or reversal strategy is suitable for the short term but not recommended in the long term for intraday trading as the trading costs become increasingly significant over time.

Identifiants

pubmed: 37682858
doi: 10.1371/journal.pone.0291119
pii: PONE-D-23-04264
pmc: PMC10490999
doi:

Substances chimiques

Pyrimethamine Z3614QOX8W
Sulfadiazine 0N7609K889

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0291119

Informations de copyright

Copyright: © 2023 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

PLoS One. 2015 Sep 14;10(9):e0137892
pubmed: 26368537

Auteurs

Jing-Rung Yu (JR)

Department of Information Management, National Chi Nan University, Nantou, Taiwan.

Chieh-Hui Wei (CH)

Department of Information Management, National Chi Nan University, Nantou, Taiwan.

Chi-Ju Lai (CJ)

Department of Information Management, National Chi Nan University, Nantou, Taiwan.

Wen-Yi Lee (WY)

Department of Information Management, National Taipei University of Business, Taipei, Taiwan.

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Classifications MeSH