系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2013年
5期
1099~1106
,共null页
信息披露 EKOP模型 信息性交易 流动性交易 信息性交易概率
信息披露 EKOP模型 信息性交易 流動性交易 信息性交易概率
신식피로 EKOP모형 신식성교역 류동성교역 신식성교역개솔
information disclosure; EKOP model; informed trading; liquidity trading; PIN
利用扩展后的EKOP模型,从金融市场微观结构的视角,以沪市A股2005至2009年年报与次年一季度报在同一天发布的402只股票为样本,分别计算了公告前后样本股票的信息性交易概率(AdjPIN)以及信息性和流动性交易者的交易强度,发现相对于公告前,信息性交易者和流动性交易者在公告后的交易强度都有提高,样本股票的信息性交易概率也有升高;通过对样本股票公告前后日均交易量变化的回归分析发现,相对于信息性交易者,流动性交易者公告前后的交易强度变化较大,是样本股票交易量变化的主要影响因素.
利用擴展後的EKOP模型,從金融市場微觀結構的視角,以滬市A股2005至2009年年報與次年一季度報在同一天髮佈的402隻股票為樣本,分彆計算瞭公告前後樣本股票的信息性交易概率(AdjPIN)以及信息性和流動性交易者的交易彊度,髮現相對于公告前,信息性交易者和流動性交易者在公告後的交易彊度都有提高,樣本股票的信息性交易概率也有升高;通過對樣本股票公告前後日均交易量變化的迴歸分析髮現,相對于信息性交易者,流動性交易者公告前後的交易彊度變化較大,是樣本股票交易量變化的主要影響因素.
이용확전후적EKOP모형,종금융시장미관결구적시각,이호시A고2005지2009년년보여차년일계도보재동일천발포적402지고표위양본,분별계산료공고전후양본고표적신식성교역개솔(AdjPIN)이급신식성화류동성교역자적교역강도,발현상대우공고전,신식성교역자화류동성교역자재공고후적교역강도도유제고,양본고표적신식성교역개솔야유승고;통과대양본고표공고전후일균교역량변화적회귀분석발현,상대우신식성교역자,류동성교역자공고전후적교역강도변화교대,시양본고표교역량변화적주요영향인소.
Based on the extended EKOP model developed by Duarte and Young, this paper selected a sample of 402 listed companies in Shanghai Stock Exchange (SSE) whose annual reports from 2005 to 2009 were disclosed on the same day of next year's first quarter reports respectively. Using the buy and sell data of 60 trading days, this paper estimated the probability of informed trading (referred as PIN) and the trading intensities of informed and liquidity traders by numerically maximizing the log likelihood function of the extended EKOP model. The results indicate that PIN and both of the informed and liquidity trading intensities undergo an increase after the disclosure on average. The increase of the informed and liquidity trading intensities is in consistency with the idea that information disclosure increases liquidity in stock markets. The increase of PIN indicates that information disclosure does not reduce the degree of information asymmetry among different traders, of which one possible cause is that institutional traders can make better use of the disclosed information than individual traders. Furthermore, this paper conducted a series of regression analysis and found that the change of the liquidity trading intensity before and after the disclosure, which is greater than that of the informed trading, is the main influencing factor of the change of the sample stocks' trading volume.