CHINA FINANCIAL RESEARCH NETWORK
2009-04-21 第2卷 第3期
University of South CarolinaMoore School of Business
UWA Business SchoolThe University of Western Australia
Chongqing UniversitySchool of Economics and Business Management
Nankai UniversityDepartment of Finance
Kyonggi UniversityDepartment of Business Administration
Gang Xiao University of South CarolinaMoore School of Business
This paper explores whether the pricing of the option-type derivative is affected by some of fundamental characteristics, such as size and liquidity of the derivative itself and the underlying asset, which are not involved in the standard pricing theory. Considering the unique status of warrants in China due to the relatively more flexible trading mechanism, I empirically examine the pricing of Chinese covered warrants to develop this study. Empirical results show that market prices of Chinese warrants are significantly higher than theoretical prices predicted by traditional pricing models such as Black-Scholes, Jump-Diffusion, and CEV model. For call warrants, about 25 percent of the market price can not be explained by pricing models, and this figure rises to over 60 percent for put warrants. Further regression tests show that both size and liquidity of warrants and underlying stocks significantly affect warrant pricing errors. The way in which the size and liquidity affect the pricing error depends on the type of warrants. In addition, it is evident that movements of put warrant prices in China do not follow movements of stock prices. To explain the above pricing puzzles,the concept of functional asset pricing is proposed. According to this concept, these pricing puzzles just reflect the existence of functional value of financial instruments that has long been neglected by traditional pricing models. In fact, Due to the high level of liquidity and popularity, the Chinese warrant may well function as a good tool for obtaining short-term profits. The pricing of Chinese warrants by the market may correctly re°ect the value of this function, and thus is rational in essence.
Mei-Hsiu Chen UWA Business SchoolThe University of Western Australia
In recent times, the prices of internationally-traded commodities have reached record highs and are expected to continue growing in the foreseeable future. This phenomenon is partially driven by strong demand from a small number of emerging economies, such as China and India. This paper places the recent commodity price boom in historical context, drawing on an investigation of the long-term time-series properties, and presents unique features for 33 individual commodity prices. Using a new methodology for examining cross-sectional variation of commodity returns and its components, we find strong evidence that the prices of world primary commodities are extremely volatile. In addition, prices are roughly 30 percent more volatile under floating than under fixed exchange rate regimes. Finally, using the capital asset pricing model as a loose framework, we find that global macroeconomic risk components have become relatively more important in explaining commodity price volatility.
Peng Xuan-hua Chongqing UniversitySchool of Economics and Business Management
In this paper, we propose a new approach to test the presence of GARCH Effects of China stock market. Our method is based on Maximal Overlap Discrect Wavelet Transform (MODWT)that provides a natural platform to investigate the volatility behavior at different time scales without losing any information.The empirical results show that GARCH effects are more significant at short time horizons as compared to long. Furthermore, when compared the modeling results of GARCH-t with that of EGARCH-t, it yields very higher effectiveness to capture the leverage effect of financial time series at relavant time scales.
Qingbin Meng Nankai UniversityDepartment of Finance
This paper studies the dividend problem when the asset of the company is driven by a diffusion process and the dividend barrier follows a Markov process. The explicit expressions for dividends is derived and a numerical example is given.
Gyu-Hyen Moon Kyonggi UniversityDepartment of Business Administration
The paper examines the short-run spillover effect of daily stock returns and volatilities between the S&P 500 in the U.S. and Shanghai SSE composite in China. First, we find that a structural break happened in the SSE stock return mean in December 2005. Second, analyzing modified GARCH (1,1)-M models, we find evidence of a symmetric and asymmetric volatility spillover effect from the U.S. to the China stock market in the post-break period. Third, the symmetric volatility spillover effect from China to the U.S. is also observed in the post-break period.
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