期货市场高频量价预测有效性检验

Jingren Yuan, Yuhong Luo
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引用次数: 4

摘要

高频数据交易正成为国内外研究的热点之一。影响价格变动的因素有很多,包括价格、成交量和持仓等。利用SPIF高频数据构建不同变量,利用决策树模型对价格走势进行预测,预测准确率可达70%。研究发现,移动平均价格变动在价格预测中具有相当重要的作用,而交易量和持仓变化对价格预测的作用有限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Test on the Validity of Futures Market's High Frequency Volume and Price on Forecast
Trading via a high-frequency data is becoming one of the hottest researches field at home and abroad. There are many factors that influence price movements, including price, volume and positions, etc. Using high-frequency data of Share Price Index Futures (SPIF) to construct different variables, and then using decision tree model to forecast price movement and the prediction accuracy can reach 70%. The study has found that moving average price movements has considerable importance in the forecast, and trading volumes and position changes on the price forecasting plays limited role.
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