【摘要】：以滬深300股指期貨仿真交易的5分鐘高頻數(shù)據(jù)為例,運(yùn)用滾動(dòng)時(shí)間窗的樣本外預(yù)測(cè)和具有Bootstrap特性的SPA檢驗(yàn)法,全面對(duì)比了基于日收益數(shù)據(jù)的歷史波動(dòng)率(historical volatility)模型和基于高頻數(shù)據(jù)的已實(shí)現(xiàn)波動(dòng)率(realized volatility)模型對(duì)波動(dòng)率的刻畫(huà)和預(yù)測(cè)能力.主要實(shí)證結(jié)果顯示,已實(shí)現(xiàn)波動(dòng)率模型以及加入附加解釋變量的擴(kuò)展隨機(jī)波動(dòng)模型是預(yù)測(cè)精度較高的波動(dòng)模型,而在學(xué)術(shù)界和實(shí)務(wù)界常用的GARCH及其擴(kuò)展模型對(duì)滬深300股指期貨的波動(dòng)率預(yù)測(cè)能力最弱.
[Abstract]:Taking the 5-minute high-frequency data of Shanghai-Shenzhen 300 stock index futures as an example, this paper uses the out-of-sample prediction of rolling time window and the SPA test method with Bootstrap characteristics. In this paper, historical volatility (historical volatility) model based on daily income data and realized volatility (realized volatility) model based on high frequency data are comprehensively compared to describe and predict volatility. The main empirical results show that the realized volatility model and the extended stochastic fluctuation model with additional explanatory variables are the volatility models with high prediction accuracy. However, GARCH and its extended model, which are commonly used in academic and practical circles, have the weakest ability to predict volatility of Shanghai-Shenzhen 300 stock index futures.
【作者單位】： 西南交通大學(xué)經(jīng)濟(jì)管理學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(70501025;70771097;70771095) 教育部新世紀(jì)優(yōu)秀人才支持計(jì)劃資助項(xiàng)目(NCET-08-0826) 教育部創(chuàng)新團(tuán)隊(duì)發(fā)展計(jì)劃資助項(xiàng)目(PCSIRT0860)
【分類(lèi)號(hào)】：F224;F832.51

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