中国金融学术研究网
CHINA FINANCIAL RESEARCH NETWORK

资本市场--市场有效性
工作论文
2010-06-29 第3卷 第3期

编: 麻省理工学院斯隆管理学院金融学讲席教授,清华大学经管学院特聘教授。

执行主编: 杨之曙清华大学经济管理学院金融学副教授。


本期目录

China’s Stock Market Integration with a Leading Power and a Close Neighbor

Zheng Yi Southwestern University of Finance and EconomicsSchool of Finance
Chen Heng Fortune SGAM Fund Management Co.ShanghaiSenior Analyst
Wing-Keung Wong Hong Kong Baptist UniversityDepartment of Economics

流动性补偿、信息不对称与市场预期

郑振龙 厦门大学金融系
莫天瑜 厦门大学金融系

On the Conditional Default Probability in a Regulated Market: A Structural Approach

Lijun Bo Nankai UniversitySchool of Mathematical Sciences
Dan Tang Nankai UniversitySchool of Mathematical Sciences and TEDA Institute of Computational Finance
Yongjin Wang Nankai UniversitySchool of Business
Xuewei Yang Nankai UniversitySchool of Mathematical Sciences and TEDA Institute of Computational Finance

The impact of the securities transaction tax on the Chinese stock market

Su Yongyang Renmin University of ChinaEconomics and Finance


论文摘要

China’s Stock Market Integration with a Leading Power and a Close Neighbor

Zheng Yi Southwestern University of Finance and EconomicsSchool of Finance
Chen Heng Fortune SGAM Fund Management Co.ShanghaiSenior Analyst
Wing-Keung Wong Hong Kong Baptist UniversityDepartment of Economics

Current integration and co-movement among international stock markets has been boosted by increased globalization of the world economy, and profit-chasing capital surfing across borders. With a reputation as the fastest growing economy in the world, China’s stock market has continued gaining momentum during recent years and incurred growing attention from academicians, as well as practitioners. Taking into account economic and geographical considerations, the US and Hong Kong are considerably the most comparable stock markets to China. As the usual vector error correction model (VECM) could overlook the long memory feature of cointegration residual series, which can in turn exert bias on the resulting inferences, we chose to employ a fractionally integrated VECM (FIVECM) in this paper to investigate the long-term cointegration relations binding China’s stock market to the aforementioned stock markets. In addition, by augmenting the FIVECM with multivariate GARCH model, the return transmission and volatility spillover between market return series were revealed simultaneously. Our empirical results show that China’s stock market is fractionally cointegrated with the two markets, and it appears that China’s stock market has stronger ties with its neighboring Hong Kong market than with the world superpower, the US market.

流动性补偿、信息不对称与市场预期

郑振龙 厦门大学金融系
莫天瑜 厦门大学金融系

本文分别研究了在经济正常波动时期与金融危机时期,央票发行对央票交易成本 的影响。实证结论表明,央票交易成本中流动性成本显著高于信息不对称成本;在经济正常 波动期中,央票发行顺应市场预期,央票发行并未引起流动性成本和信息不对称成本的显著 变化;在金融危机时期,央票发行出乎市场预期,央票发行引起信息不对称成本显著增加, 指令流自相关系数显著降低。央票市场信息不对称成本主要来源于机构投资者对公开信息的 解读不同。

On the Conditional Default Probability in a Regulated Market: A Structural Approach

Lijun Bo Nankai UniversitySchool of Mathematical Sciences
Dan Tang Nankai UniversitySchool of Mathematical Sciences and TEDA Institute of Computational Finance
Yongjin Wang Nankai UniversitySchool of Business
Xuewei Yang Nankai UniversitySchool of Mathematical Sciences and TEDA Institute of Computational Finance

In this article, we consider a regulated market and explore the default events. By using a so-called reflected Ornstein-Uhlenbeck process with two-sided barriers to formulate the price dynamics, we derive the expression on the conditional default probability. In the cases of single observation and multiple observations, the conditional default probabilities are explicitly expressed in terms of the inverse Laplace transforms. Finally, we present a numerical simulation associated with the conditional default probability.

The impact of the securities transaction tax on the Chinese stock market

Su Yongyang Renmin University of ChinaEconomics and Finance

This paper analyzes the impact of changes in the securities transaction tax (STT) rate on the local A-shares market in China. We find that, on average, a 22-base-point- increase in the STT rate is associated with about a 28% drop in trading volume, while a 17-base-point- reduction in the STT rate is associated with about a 89% increase in trading volume in the Chinese A-shares market. Both the increases and reductions in the STT rate result in a significant increase in the market return volatility. Besides, the increases in the STT rate have mixed effects on market efficiency, either improving or curbing it. The reductions usually either make the market less efficient or have not effect on it. The empirical results together show that levying the STT on trading is not an effective tool to regulate stock market, at least in this emerging market.


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