我國燃油期貨市場的波動率預測模型
發(fā)布時間:2018-08-30 20:44
【摘要】:準確描述和預測石油及其相關產(chǎn)品的價格波動對各國政府能源政策的制定以及能源風險管理工作意義重大。文章以上海期貨交易所燃油期貨的15分鐘高頻價格數(shù)據(jù)為例,實證計算了三類代表性波動率模型:已實現(xiàn)波動率模型、隨機波動模型以及GARCH族模型對我國燃油期貨價格波動的預測值,同時,采用多種損失函數(shù)對比了三類波動率模型。實證結果表明,基于高頻數(shù)據(jù)的已實現(xiàn)波動率模型對我國燃油期貨市場具有最好的波動預測精度。而就基于日數(shù)據(jù)的模型而言,隨機波動模型要明顯強于GARCH族模型。
[Abstract]:Accurately describing and predicting the price fluctuation of petroleum and its related products is of great significance to the formulation of energy policy and energy risk management. Taking the 15-minute high frequency price data of fuel futures in Shanghai Futures Exchange as an example, this paper empirically calculates three kinds of representative volatility models: realized volatility model. The stochastic volatility model and the GARCH family model are used to predict the volatility of fuel futures in China. At the same time, three kinds of volatility models are compared by using a variety of loss functions. The empirical results show that the realized volatility model based on high frequency data has the best volatility prediction accuracy for China's fuel futures market. For the model based on daily data, the stochastic volatility model is stronger than the GARCH family model.
【作者單位】: 西南交通大學經(jīng)濟管理學院;
【基金】:國家自然科學基金資助項目(71071131)
【分類號】:F224;F426.22;F724.5
本文編號:2214240
[Abstract]:Accurately describing and predicting the price fluctuation of petroleum and its related products is of great significance to the formulation of energy policy and energy risk management. Taking the 15-minute high frequency price data of fuel futures in Shanghai Futures Exchange as an example, this paper empirically calculates three kinds of representative volatility models: realized volatility model. The stochastic volatility model and the GARCH family model are used to predict the volatility of fuel futures in China. At the same time, three kinds of volatility models are compared by using a variety of loss functions. The empirical results show that the realized volatility model based on high frequency data has the best volatility prediction accuracy for China's fuel futures market. For the model based on daily data, the stochastic volatility model is stronger than the GARCH family model.
【作者單位】: 西南交通大學經(jīng)濟管理學院;
【基金】:國家自然科學基金資助項目(71071131)
【分類號】:F224;F426.22;F724.5
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