农产品期货市场波动率的预测以及预测精度评价研究

项目名称： 农产品期货市场波动率的预测以及预测精度评价研究

项目编号： No.71203067

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 宏观管理与政策

项目作者： 杨科

作者单位： 华南农业大学

项目金额： 19万元

中文摘要： 农产品期货在价格发现和风险防范过程中扮演重要角色，科学准确地预测其波动率对充分实现其避险等多重功能是决定性的，而目前对农产品期货市场波动率的预测研究尚较少。 本项目拟：(1)基于高频数据的非参数核估计和尺度变换估计农产品期货市场波动率，拟检验波动率的长记忆性、结构突变和不对称性，作为建模的基础；（2）构建新型的ARFIMA模型预测农产品期货市场波动率，改进现有模型忽略结构突变的不足，拟采用MCMC方法估计模型参数，克服以往单纯依赖MLE和GMM估计的缺陷；（3）实证评价模型的预测性能，拟基于Bootstrap构建稳健的预测精度评价方法，改进现有评价方法不严谨的缺陷。 本项目的实现，将丰富农产品期货市场波动率预测的研究，为农业生产者、投资者和农产品消费者获得准确的远期价格信息，资产定价者和套利者有效地规避风险以及金融监管部门提高农产品期货市场的风险监管水平提供理论依据。

中文关键词： 农产品期货；已实现波动率预测；高频数据；预测精度评价；MCMC

英文摘要： Agricultural futures play an important role in price discovery and risk coverage, and scientifically and accurately predicting its volatility play a key role in full realization of its hedging and other multiple functions, but the research on the volatility prediction of agricultural futures market is very little at present. The project is to (1)estimate the the volatility of agricultural futures markets by kernel-based estimators and scale transform based on the high-frequency data, and test the possibility of structural breaks, long memory and asymmetry in the daily realized volatility series as the basis of modeling.(2) propose a new ARFIMA model to predict the volatility of agricultural futures market. The new model will corret the shortage of the current models which ignored the characteristic of structural breaks for volatility, and the new model is estimated by MCMC method which overcome the shortcomings that the previous studies rely solely on MLE and GMM.(3) propose a robust prediction accuracy evaluation method based on Bootstrap method to evaluate and compare the prediction accuracy of various volatility forecasting model. The new method will overcome the shortcomings that the previous studies about prediction accuracy evaluation is not rigorous enough. The realization of the project, will extend the

英文关键词： Agricultural Futures；Realized Volatility Forecast；High-Frequency Data；Prediction Accuracy Evaluation；MCMC