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为准确地把握波罗的海干散货运价指数(BDI)的变化趋势,选用一阶对数差分方法,对近期BDI日收益率序列的基本统计量特征进行了分析,验证了BDI日收益率序列的“尖峰厚尾”及波动的集聚性等特征,并进一步运用GARCH(1,1)模型,分析了其波动的持续性和滞后性.在此基础上,基于GARCH模型构造了预测的方法步骤,经优化调整滞后期对BDI日收益率进行了预测,最后,通过将BDI对数日收益率序列还原为指数序列,对BDI进行了预测,实证分析结果验证了模型及方法的适用性和有效性.
In order to accurately grasp the changing trend of the Baltic Dry-Bulk Freight Index (BDI), the first-order logarithmic difference method was used to analyze the basic statistical characteristics of the recent BDI daily return series and verify the BDI daily return series “Peak thick tail ” and the volatility of the aggregation and other characteristics, and further the use of GARCH (1,1) model, the analysis of the volatility of the continuity and lag .Above based on the GARCH model constructed a prediction method Step, the daily return rate of BDI is predicted by optimizing and adjusting the lag period. Finally, the BDI is predicted by restoring the logarithmic daily return series of BDI to exponential sequence. The results of empirical analysis verify the applicability of the model and method and Effectiveness.