期刊文献+

中国银行间国债市场流动性黑洞的实证检验 被引量:3

Verification of Liquidity Black Holes in China's Inter-bank T-bond Market
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摘要 本文对我国银行间国债市场流动性黑洞进行了理论分析和实证检验。理论分析表明,虽然市场参与主体范围不断扩大,但实际参与交易的市场交易成员仍具有较高的同质性。通过建立债券收益与交易量双变量自回归模型,利用银行间国债市场逐笔交易面板数据,对银行间国债市场流动性黑洞进行实证检验。结果表明:债券收益率和交易变化量均呈正向自相关关系,交易量指令流的变化导致债券当期收益率的反向变化,滞后的收益率对当期交易产生负向影响,我国银行间国债市场部分债券存在流动性黑洞。 This paper theoretically analyzes and empirically tests China' s inter-bank T-bond market liquidity black holes. Theoretical analysis results show that, although the scope of market participants are continuously expanding, the actual members involved in the market transaction still appear highly homogeneous. With a bivariate autoregressive model between bond yields and trading volume, an empirical test on liquidity black holes on inter-bank T-bond market has been done with the transaction panel data. The regression results show that both bond yields and trading volume changes show a positive autocorrelation, instruction stream changes in trading volume cause current bond yields to change reversely, and lagged yields have negative influence on the current trading volume, which means that liquidity black holes exist in some of China's inter-bank T-bond market.
出处 《金融论坛》 CSSCI 北大核心 2010年第4期21-25,共5页 Finance Forum
关键词 银行间国债市场 流动性黑洞 双变量自回归模型 inter-bank T-bond market liquidity black holes bivariate autoregressive model
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参考文献3

  • 1Cohen, H. B., and Shin, H. S., 2002. Positive Feedback Trading in the US Treasury Market [J]. BIS Quarterly Review, (6):59-67.
  • 2Lee, M. C. C., and Ready, J. M., 1991. Inferring Trade Direction from Intraday Data[J]. The Journal of Finance, 46(2):722-736.
  • 3Hasbrouck, J., 1991. Measuring the Information Content of Stock Trades[J]. The Journal of Finance,46( 1 ) : 179-207.

同被引文献58

  • 1陈灯塔,周颖刚.理性恐慌,流动性黑洞和国有股减持之谜[J].经济学(季刊),2006,5(2):379-402. 被引量:11
  • 2潘婉彬,缪柏其,靳韬.银行间国债市场与交易所国债市场相关性研究[J].数理统计与管理,2007,26(3):528-534. 被引量:12
  • 3肖蔚.创新流动性管理:谨防由“过剩”掉入“黑洞”[J].武汉金融,2007(7):33-34. 被引量:1
  • 4Chordia, T., Roll, R., and Subrahmanyam, A., 2000. Commonality in Liquidity[ J ]. Journal of Financial Economics, (56) : 3-28.
  • 5Cohen, H.B. ,and Shin, H.S., 2002. Positive Feedback Trading in the US Treasury Market[J ]. BIS Quarterly Review, (6):59-67.
  • 6Engle, R.F., and Patton ,J.A., 2004.Impacts of Trades in an Error-correction Model of Quote Prices[ J ]. Journal of Finance Markets, (7):1-25.
  • 7Femando,S.C., Herring,J.R.,and Subrahmanyam,A., 2008. Common Liquidity Shocks and Market Collapse: Lessons from the Market for Perps[J].Journal of Banking and Finance, ( 1 ) : 1625-1635.
  • 8Hasbrouck,J., 1991. Measuring the Information Content of Stock Trades[J ]. The Journal of Finance,46( 1 ) : 179-207.
  • 9Instefjord, N., 1999. A Simple Model of Market Liquidity[J]. Economics Letters, (64):329-337.
  • 10Lee,M.C.C.,and Ready,J.M., 1991. Inferring Trade Direction from Intraday Data[J]. The Journal of Finance,46(2):722-736.

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