湖南大学学报:社会科学版
湖南大學學報:社會科學版
호남대학학보:사회과학판
Journal of Hunan University(Social Sciences)
2013年
2期
48~54
,共null页
高频数据 量价关系 成交次数 平均交易头寸
高頻數據 量價關繫 成交次數 平均交易頭吋
고빈수거 량개관계 성교차수 평균교역두촌
high frequency data; price-volume relation; number of trades; average trade size
在混合分布假说理论的基础上,根据Jone等(1994)的研究成果将成交量划分为成交次数和平均交易头寸,并考虑已实现波动率的跳跃和非对称性特征,构造了量价关系的基础模型、连续和跳跃波动量价关系模型及量价关系非对称模型,并利用沪深300股指期货高频数据分别对各模型进行实证分析。研究发现沪深300股指期货成交量与价格波动之间表现明显的正相关关系,成交量、成交次数及平均交易头寸对连续和跳跃波动都有明显的正向影响,下偏已实现半方差较上偏已实现半方差包含更多的市场波动信息,平均交易头寸作为量价关系背后的主要驱动因子,可以更好地解释市场波动。
在混閤分佈假說理論的基礎上,根據Jone等(1994)的研究成果將成交量劃分為成交次數和平均交易頭吋,併攷慮已實現波動率的跳躍和非對稱性特徵,構造瞭量價關繫的基礎模型、連續和跳躍波動量價關繫模型及量價關繫非對稱模型,併利用滬深300股指期貨高頻數據分彆對各模型進行實證分析。研究髮現滬深300股指期貨成交量與價格波動之間錶現明顯的正相關關繫,成交量、成交次數及平均交易頭吋對連續和跳躍波動都有明顯的正嚮影響,下偏已實現半方差較上偏已實現半方差包含更多的市場波動信息,平均交易頭吋作為量價關繫揹後的主要驅動因子,可以更好地解釋市場波動。
재혼합분포가설이론적기출상,근거Jone등(1994)적연구성과장성교량화분위성교차수화평균교역두촌,병고필이실현파동솔적도약화비대칭성특정,구조료량개관계적기출모형、련속화도약파동량개관계모형급량개관계비대칭모형,병이용호심300고지기화고빈수거분별대각모형진행실증분석。연구발현호심300고지기화성교량여개격파동지간표현명현적정상관관계,성교량、성교차수급평균교역두촌대련속화도약파동도유명현적정향영향,하편이실현반방차교상편이실현반방차포함경다적시장파동신식,평균교역두촌작위량개관계배후적주요구동인자,가이경호지해석시장파동。
Building on the Mixture Distribution Hypothesis, this paper separates the trading volume into number of trades and average trade size in line with Jone, et al. (1994), constructs the basic volume-price relation model, the volume-price relation model with continuous and jump volatility, and the asymmetric model on the volume-price relation to account for the realized volatility and the asymmetric features, and uses high frequency data of the CSI 300 stock index futures to empirically validate these models. The findings show that there exists a significant positive correlation between the trading volumes of the CSI 300 stock index futures and the price volatility; the trading volume, the number of trades and the average trade size all have a positive effect on the continuous and the jump volatilities; the downside realized semi-variance includes more information on volatility than does the upside realized semi-variance; and the average trade size, introduced as the primary driving factor behind the volume-price relation, can better explain the volatility on the market.