摘要
The metal futures price fluctuation prediction model was constructed based on symbolic high-frequency time series using high-frequency data on the Shanghai Copper Futures Exchange from July 2014 to September 2018,and the sample was divided into 194 histogram time series employing symbolic time series.The next cycle was then predicted using the K-NN algorithm and exponential smoothing,respectively.The results show that the trend of the histogram of the copper futures earnings prediction is gentler than that of the actual histogram,the overall situation of the prediction results is better,and the overall fluctuation of the one-week earnings of the copper futures predicted and the actual volatility are largely the same.This shows that the results predicted by the K-NN algorithm are more accurate than those predicted by the exponential smoothing method.Based on the predicted one-week price fluctuations of copper futures,regulators and investors in China’s copper futures market can timely adjust their regulatory policies and investment strategies to control risks.
构建高频尺度下的基于符号时间序列的金属期货价格波动预测模型,并选取上海铜期货交易所2014年7月到2018年9月的高频数据,采用符号时间序列方法将样本分为194个直方图时间序列,分别使用K-NN算法与指数平滑法预测下一个周期。结果显示,铜期货的收益预测得出的直方图走势比实际的直方图走势较为平缓,预测结果的整体情况较好,并且预测铜期货所得一周收益的整体波动与实际波动值在很大程度上一致。这表明用K-NN算法预测所得的结果比指数平滑法预测的结果更加精确。根据预测得到的铜期货一周的价格整体波动情况,中国铜期货市场的监管者及投资者可以及时调整其监管政策和投资策略以控制风险。
基金
Projects(71633006,7184207,7184210)supported by the National Natural Science Foundation of China
Project(2019CX016)supported by the Annual Innovation-driven Project in Central South University,China。
