首页|Studies from Guizhou Normal University in the Area of Machine Learning Reported (More Is Better? the Impact of Predictor Choice On the Ine Oil Futures Volatilit y Forecasting)
Studies from Guizhou Normal University in the Area of Machine Learning Reported (More Is Better? the Impact of Predictor Choice On the Ine Oil Futures Volatilit y Forecasting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in Guizhou, Peop le's Republic of China, by NewsRx journalists, research stated, "This paper aims to address the predictor choice issue in forecasting volatility of INE oil futu res by a comprehensive comparative study with a large number of predictive varia bles and applying machine learning models along with their interpretability tool s. The main finding is that the selection of predictors is crucial for improving volatility forecasting accuracy, but it is not always the case that including m ore predictive variables leads to better forecasting results, even for machine l earning models." The news reporters obtained a quote from the research from Guizhou Normal Univer sity, "Specifically, this paper has five major findings: (1) A few variables can significantly improve forecasting accuracy independently, but their contributio n is limited. (2) Increasing the number of predictors from specific categories ( market sentiment indicators, crude oil futures prices from other exchanges, and energy market indicators) helps to enhance forecasting accuracy. (3) Lowfrequenc y variables have a weak effect on improving the daily volatility. (4) Ensemble t ree models perform better than traditional machine learning models based on vari able selection with dynamic parameter optimization, even without much parameter tuning. The above findings still hold true under a series of robustness tests an d economic value assessments."
GuizhouPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningGuizhou Normal University
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