CHINA FINANCIAL RESEARCH NETWORK
2011-03-31 第3卷 第13期
University of Southern QueenslandSchool of Accounting,Economics & Finance
Singapore Management UniversityDepartment of Finance
University of Rhode Island College of Busines
Washington UniversityOlin School of Business
Tsinghua UniversityDepartment of Finance
Chandrasekhar Krishnamurti University of Southern QueenslandSchool of Accounting,Economics & Finance
We find that the asymmetric volatility phenomenon is reversed in the Shanghai Stock Exchange during bull markets. That is, volatility increases more with good news than with bad news. This evidence is inconsistent with the US markets (Wu 2001, and Bae, Kim and Nelson 2007). Further examination of this phenomenon reveals that the positive impact of good news on volatility is driven by return chasing behaviour of investors in large stocks during bull markets. We also find that volatility increases after stock price declines in bear markets especially for small stocks. This increase in volatility of small stocks after bad news in bear markets is partly driven by liquidity. After controlling for liquidity shifts, there are no significant patterns in the volatility of small stocks during bear markets. We posit that institutional and behavioural factors are the major driving forces of observed volatility patterns in Chinese stock market.
Fuwei Jiang Singapore Management UniversityDepartment of Finance
We analyze return predictability for the Chinese stock market, including the aggregate market portfolio and the components of the aggregate market, such as portfolios sorted on industry, size, book-to-market and ownership concentration. Considering a variety of economic variables as predictors, both in-sample and out-of-sample tests highlight significant predictability in the aggregate market portfolio of the Chinese stock market and substantial differences in return predictability across components. Among industry portfolios, Finance and insurance, Real estate, and Service exhibit the most predictability, while portfolios of small-cap and low ownership concentration firms also display considerable predictability. Two key findings provide economic explanations for component predictability: (i) based on a novel out-of-sample decomposition, time-varying macroeconomic risk premiums captured by the conditional CAPM model largely account for component predictability; (ii) industry concentration and market capitalization significantly explain differences in return predictability across industries, consistent with the information-flow frictions emphasized by Hong, Torous, and Valkanov (2007).
Shaw Chen University of Rhode Island College of Busines
This study examines the effect of corporate asset growth on stock returns using data on nine equity markets in Asia. For the period from 1981 to 2007, we find a pervasive negative relation between asset growth and subsequent stock returns. We further examine the determinants of this asset growth effect across markets. The negative relation between asset growth and stock returns is weaker in markets where firms’ assets growth rates are more homogeneous, and in markets where firms rely more on internal financing and bank financing for growth. On the other hand, corporate governance, investor protection, and legal origin do not influence the magnitude of the asset growth effect in the Asian markets.
Guofu Zhou Washington UniversityOlin School of Business
In this paper, we extend the long-run risks model of Bansal and Yaron (BY, 2004) to allow both a long- and a short-run volatility component in consumption growth, long-run risks, and dividend growth. Our two volatility model better captures macroeconomic volatility than a single volatility model, and can reconcile simultaneously the large negative market variance risk premium, di?ering predictability in excess returns, consumption, dividends, and stock market volatility, all of which are di±cult to explain previously by the BY model.
Sanguo Luo Tsinghua UniversityDepartment of Finance
Stock valuation is fundamentally important to finance. The current absolute and relative valuations do not wok in some common circumstances. This paper finds a new valuation method with the criterion of required payback period. The new method is a brand new way in valuation paralleling to the discounted cash flow method. This paper further derives the models of theoretical P/E, P/B and P/S based on the new method. These new valuation models are theoretical sound and flexible for valuing various stocks and market bubbles. They can also bridge the gap between the relative and absolute valuations.
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