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

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_Omeg...

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Detalles Bibliográficos
Autores principales: Yu, Jing-Rung, Wei, Chieh-Hui, Lai, Chi-Ju, Lee, Wen-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490999/
https://www.ncbi.nlm.nih.gov/pubmed/37682858
http://dx.doi.org/10.1371/journal.pone.0291119
Descripción
Sumario: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.