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时间序列分析方法在金融市场,尤其是股票指数、汇率、利率、期货等证券风险大小的度量、风险收益的计算与市场效率的检验中得到广泛应用。为了预测出下个阶段的期货价格的总体水平,进而帮助投资者提早的对自己的投资选择进行分配,将多元统计分析中的聚类分析方法和非平稳时间序列模型相结合,先将样本数据中的期货价格分类,求出每个类中的价格均值,进而对这些均值做ARIMA模型拟合和预测,预测出接下来的期货价格水平。
Time series analysis method is widely used in the financial market, especially the measurement of stock risk, such as stock index, exchange rate, interest rate and futures, risk return calculation and market efficiency test. In order to predict the overall level of the futures price in the next stage and to help investors allocate their investment choices earlier, the cluster analysis method in multivariate statistical analysis is combined with the non-stationary time series model. The sample data In the futures price classification, find the average price of each class, and then these mean ARIMA model fitting and forecasting, forecast the next futures price level.