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SSE Composite Index Prediction and Simulation System Multiple Regression and Time—Lag Cointegration Model

机译:SSE复合索引预测和仿真系统多元回归和时间滞后协整模型

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Stock index forecasting is an important task in economic field; it is difficult to accurately predict index trends using the traditional prediction methods which are based on price and the quality. Studies on this field were described in this paper: historical data and the influence of macroeconomic factors to stock price, fits the mathematical models of the principal component of the multi-lag regression and Sequence Cointegration and stock index predicts; At the same time the author has done the system simulation, results show that the mathematical model is very efficient and practical.
机译:股指预测是经济领域的重要任务;使用基于价格和质量的传统预测方法,难以准确预测指标趋势。本文描述了对该领域的研究:历史数据和宏观经济因素对股价的影响,适合多滞回归和序列协整的主要成分和股指预测的数学模型;同时作者已经完成了系统仿真,结果表明数学模型非常有效和实用。

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