A Method to Predict the Relative Performance of Stocks Using Financial Meta-indicators.

Christyan Inácio de Almeida,Leandro Nunes de Castro

DCAI(2022)

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摘要
There is still no consensus among researchers as to which financial indicators are the most relevant, predictive, and useful for the construction of a strategy and investment planning of portfolio allocation. The purpose of this study is to introduce a predictive method of the relative performance of stocks based on meta-indicators. This paper investigates the fundamental indicators that best explain companies' stock returns and proposes a method for the construction of meta-indicators and prediction of stocks that perform above a specific benchmark. The relative performance is assessed using as reference the Exchange-Traded Fund (ETF) BOVA11. The proposed method presented results with up to 78% precision in its capacity of predicting those assets with performance superior to that of the benchmark. Furthermore, those assets recommended by the method resulted in growth rates around 30 p.p. superior to that of the benchmark over specific time frames.
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关键词
Stock prediction,Portfolio allocation,Machine learning,Meta-indicators,Fundamental analysis
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