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• W2557747163 abstract "We investigate the performance of complex trading rules in equity price direction prediction, over and above continuous-valued indicators and simple technical trading rules. Ten of the most popular technical analysis indicators are included in this research. We use Random Forest ensemble classifiers using minute-by-minute stock market data. Results show that our models have predictive power and yield better returns than the buy-and-hold strategy when disregarding transaction costs both in terms of number of stocks with profitable trades as well as overall returns. Moreover, our findings show that two-way and three-way combinations, i.e., complex trading rules, are important to “beat” the buy-and-hold strategy." @default.
• W2557747163 created "2016-12-08" @default.
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• W2557747163 date "2016-07-01" @default.
• W2557747163 modified "2023-10-12" @default.
• W2557747163 title "Equity price direction prediction for day trading: Ensemble classification using technical analysis indicators with interaction effects" @default.
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• W2557747163 doi "https://doi.org/10.1109/cec.2016.7744227" @default.
• W2557747163 hasPublicationYear "2016" @default.
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