The process starts with data cleaning and data preprocessing, and concludes with an analysis of forecasting and simulation results. Often, researchers look to ...
A data mining procedure to forecast daily stock market return is proposed.The raw data includes 60 financial and economic features over a 10-year period.
Oct 22, 2024 · The experimental results show that the proposed method generates more profits than other DRP methods on the America stock market. This stock ...
A comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 ETF based on 60 financial and economic features and ...
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A data mining procedure to forecast daily stock market return is proposed. The raw data includes 60 financial and economic features over a 10-year period.
In univariate analysis, dimensionality reduction technology. only the financial time series itself is considered as the input, Strictly speaking, the ...
Expert systems with applications , 2017, Vol.67(C), p.126-139 ,. Forecasting daily stock market return using dimensionality reduction Available Online ...
Jun 15, 2019 · Zhong & Enke (2017a) present a study of dimensionality reduction with an application to predict the daily return direction of the SPDR S&P 500 ...
We employ a semi-parametric method known as Boosted Regression Trees (BRT) to forecast stock returns and volatility at the monthly frequency.
Zhong & Enke (2017a) present a study of dimensionality reduction with an application to predict the daily return direction of the SPDR S&P 500 ETF (ticker.
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