發(fā)布時(shí)間：2018-01-01 10:14

  本文關(guān)鍵詞：基于符號(hào)收益和跳躍變差的高頻波動(dòng)率模型　出處：《管理科學(xué)學(xué)報(bào)》2017年10期 　論文類型：期刊論文

  更多相關(guān)文章： 高頻波動(dòng)率模型 跳躍 已實(shí)現(xiàn)半變差 符號(hào)跳躍變差

【摘要】：基于符號(hào)收益率的視角,對(duì)現(xiàn)有的HAR-RV類及其跳躍擴(kuò)展模型進(jìn)行相應(yīng)分解,構(gòu)建新型的HAR-RV類波動(dòng)率模型.進(jìn)一步,結(jié)合符號(hào)收益和不同的跳躍識(shí)別檢驗(yàn)方法,提出了包含符號(hào)跳躍變差的HAR-RV類模型,并利用樣本外滾動(dòng)窗預(yù)測(cè)技術(shù)和"模型信度設(shè)定"(MCS)檢驗(yàn)法評(píng)價(jià)了各種新舊HAR-RV模型對(duì)我國滬深300股價(jià)指數(shù)波動(dòng)的預(yù)測(cè)能力.結(jié)果表明:基于C_TZ跳躍識(shí)別檢驗(yàn)的符號(hào)跳躍變差能顯著改善波動(dòng)率模型的短期預(yù)測(cè)能力,但在中長期波動(dòng)預(yù)測(cè)時(shí),符號(hào)跳躍變差未能明顯提升HAR-RV類模型的預(yù)測(cè)精度;新提出的HAR-S-RVTJ-TSJV模型和HAR-S-RV-TJ模型分別在對(duì)短期(未來1天)和中長期(未來5天和20天)的波動(dòng)預(yù)測(cè)檢驗(yàn)中,展現(xiàn)出了最高的預(yù)測(cè)精度.
[Abstract]:Based on the symbolic rate of return, the existing HAR-RV class and its jump extension model are decomposed accordingly, and a new HAR-RV volatility model is constructed. Combined with the sign income and the different test methods of jump recognition, the HAR-RV class model including the symbol jump variation is proposed. And using the prediction technology of rolling window outside the sample and "model reliability setting" MCSs). The new and old HAR-RV models are used to predict the fluctuation of Shanghai and Shenzhen 300 stock price index in China. The results show that:. The symbolic jump variation based on CSTZ Jump recognition test can significantly improve the short-term prediction ability of volatility model. However, in the medium and long term fluctuation prediction, the symbol jump variation can not obviously improve the prediction accuracy of HAR-RV model. The new HAR-S-RVTJ-TSJV model and the HAR-S-RV-TJ model are tested for short-term (next 1 day) and medium (5 and 20 days) volatility forecasting, respectively. It shows the highest prediction accuracy.
【作者單位】： 西南交通大學(xué)經(jīng)濟(jì)管理學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(71371157;71671145) 教育部人文社會(huì)科學(xué)基金規(guī)劃資助項(xiàng)目(15YJA790031;16YJA790062) 四川省科技青年基金資助項(xiàng)目(2015JQO010) 四川省社會(huì)科學(xué)高水平研究團(tuán)隊(duì)資助項(xiàng)目 中央高校基金科研業(yè)務(wù)費(fèi)專項(xiàng)資金資助項(xiàng)目(26816WCX02)
【分類號(hào)】：F832.51;O21
【正文快照】： 0引言對(duì)金融資產(chǎn)波動(dòng)率的描述和預(yù)測(cè)是現(xiàn)代金融學(xué)理論和實(shí)務(wù)界研究的熱點(diǎn)和難點(diǎn)問題.近十多年,隨著計(jì)算機(jī)技術(shù)的飛速發(fā)展和金融高頻數(shù)據(jù)獲取性逐漸增強(qiáng),基于日內(nèi)高頻數(shù)據(jù)的波動(dòng)率測(cè)度和預(yù)測(cè)受到了國內(nèi)外學(xué)者的廣泛關(guān)注.其中,具有代表性的是Andersen和Bollerslev[1-2]提出的已，

本文編號(hào)：1364068