高頻股指期現(xiàn)貨市場(chǎng)波動(dòng)跳躍及跳躍溢出檢驗(yàn)——基于集合經(jīng)驗(yàn)?zāi)Ｊ椒纸夂托〔ń翟?/H1>
發(fā)布時(shí)間：2018-04-23 22:02
本文選題：EEMD + 小波分析��； 參考：《系統(tǒng)科學(xué)與數(shù)學(xué)》2017年06期
【摘要】：選用EEMD+小波軟閾值降噪法對(duì)金融高頻數(shù)據(jù)進(jìn)行降噪處理,然后利用仿真數(shù)據(jù)和實(shí)證方法驗(yàn)證了該方法的有效性,最后把降噪后的數(shù)據(jù)進(jìn)行跳躍和跳躍溢出檢驗(yàn).研究表明:1)EEMD+小波降噪方法可以較好的降低金融高頻數(shù)據(jù)的噪音.2)大部分情況下CSI300股指期現(xiàn)貨市場(chǎng)對(duì)信息的反應(yīng)不充分,期指更容易出現(xiàn)信息反映過度,兩市場(chǎng)間有共同跳躍,跳躍溢出顯著.3)通常認(rèn)為噪音的存在使得期指對(duì)新信息的沖擊更敏感,跳躍頻率、幅度更大,會(huì)領(lǐng)先于現(xiàn)貨市場(chǎng)發(fā)生跳躍,降噪后兩市場(chǎng)的跳躍特征無明顯變化,所以噪音不是股指期現(xiàn)貨市場(chǎng)具有這些跳躍特征的唯一因素.
[Abstract]:The EEMD+ wavelet soft threshold denoising method is used to denoise the financial high frequency data. Then the effectiveness of the method is verified by the simulation data and the empirical method. Finally, the data after the noise reduction is tested by jumping and jumping spillover. The research shows that: 1) the EEMD+ wavelet denoising method can reduce the noise.2 of the financial high frequency data better). In some cases, in the CSI300 stock market, the spot market is not fully responsive to information, it is easier to show excessive information, two markets have a joint jump, jump spillover.3.) the noise is usually considered to be more sensitive to the impact of the new information, jumping frequency, and greater amplitude, leading to a jump in the spot market and noise reduction. There is no obvious change in the jump characteristics of the last two markets, so noise is not the only factor that has the characteristics of these jumps in the stock index spot market.
【作者單位】： 新疆財(cái)經(jīng)大學(xué)金融學(xué)院;新疆財(cái)經(jīng)大學(xué)應(yīng)用經(jīng)濟(jì)學(xué)博士后流動(dòng)站;中央財(cái)經(jīng)大學(xué)金融學(xué)院;
【基金】：國(guó)家自然科學(xué)基金面上項(xiàng)目(71471182);國(guó)家自然科學(xué)基金項(xiàng)目(71661028,71401188) 中央財(cái)經(jīng)大學(xué)青年科研創(chuàng)新團(tuán)隊(duì) 中國(guó)博士后第61批面上項(xiàng)目 新疆財(cái)經(jīng)大學(xué)校級(jí)(2015XYB018) 新疆自治區(qū)普通高校人文社科重點(diǎn)研究基地社會(huì)經(jīng)濟(jì)統(tǒng)計(jì)研究中心招標(biāo)(050315C05)資助課題
【分類號(hào)】：F224;F832.51;F724.5
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，
本文編號(hào)：1793815
本文鏈接：http://sikaile.net/jingjilunwen/huobiyinxinglunwen/1793815.html
本文選題：EEMD + 小波分析��； 參考：《系統(tǒng)科學(xué)與數(shù)學(xué)》2017年06期
【摘要】：選用EEMD+小波軟閾值降噪法對(duì)金融高頻數(shù)據(jù)進(jìn)行降噪處理,然后利用仿真數(shù)據(jù)和實(shí)證方法驗(yàn)證了該方法的有效性,最后把降噪后的數(shù)據(jù)進(jìn)行跳躍和跳躍溢出檢驗(yàn).研究表明:1)EEMD+小波降噪方法可以較好的降低金融高頻數(shù)據(jù)的噪音.2)大部分情況下CSI300股指期現(xiàn)貨市場(chǎng)對(duì)信息的反應(yīng)不充分,期指更容易出現(xiàn)信息反映過度,兩市場(chǎng)間有共同跳躍,跳躍溢出顯著.3)通常認(rèn)為噪音的存在使得期指對(duì)新信息的沖擊更敏感,跳躍頻率、幅度更大,會(huì)領(lǐng)先于現(xiàn)貨市場(chǎng)發(fā)生跳躍,降噪后兩市場(chǎng)的跳躍特征無明顯變化,所以噪音不是股指期現(xiàn)貨市場(chǎng)具有這些跳躍特征的唯一因素.
[Abstract]:The EEMD+ wavelet soft threshold denoising method is used to denoise the financial high frequency data. Then the effectiveness of the method is verified by the simulation data and the empirical method. Finally, the data after the noise reduction is tested by jumping and jumping spillover. The research shows that: 1) the EEMD+ wavelet denoising method can reduce the noise.2 of the financial high frequency data better). In some cases, in the CSI300 stock market, the spot market is not fully responsive to information, it is easier to show excessive information, two markets have a joint jump, jump spillover.3.) the noise is usually considered to be more sensitive to the impact of the new information, jumping frequency, and greater amplitude, leading to a jump in the spot market and noise reduction. There is no obvious change in the jump characteristics of the last two markets, so noise is not the only factor that has the characteristics of these jumps in the stock index spot market.
【作者單位】： 新疆財(cái)經(jīng)大學(xué)金融學(xué)院;新疆財(cái)經(jīng)大學(xué)應(yīng)用經(jīng)濟(jì)學(xué)博士后流動(dòng)站;中央財(cái)經(jīng)大學(xué)金融學(xué)院;
【基金】：國(guó)家自然科學(xué)基金面上項(xiàng)目(71471182);國(guó)家自然科學(xué)基金項(xiàng)目(71661028,71401188) 中央財(cái)經(jīng)大學(xué)青年科研創(chuàng)新團(tuán)隊(duì) 中國(guó)博士后第61批面上項(xiàng)目 新疆財(cái)經(jīng)大學(xué)校級(jí)(2015XYB018) 新疆自治區(qū)普通高校人文社科重點(diǎn)研究基地社會(huì)經(jīng)濟(jì)統(tǒng)計(jì)研究中心招標(biāo)(050315C05)資助課題
【分類號(hào)】：F224;F832.51;F724.5
【相似文獻(xiàn)】
相關(guān)期刊論文 前1條
1 朱乾龍;張成;唐敏;郭路;;中國(guó)A股市場(chǎng)有效性的實(shí)證研究——基于小波降噪技術(shù)的分析[J];統(tǒng)計(jì)教育;2010年05期
相關(guān)博士學(xué)位論文 前1條
1 朱莉;股指期現(xiàn)貨市場(chǎng)溢出效應(yīng)研究[D];中央財(cái)經(jīng)大學(xué);2016年
，本文編號(hào)：1793815
本文鏈接：http://sikaile.net/jingjilunwen/huobiyinxinglunwen/1793815.html
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