This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen’s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ‘irrational’ and ‘speculative’. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China’s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

We use Hong Kong stock market data for 1982-2001 to test the persistence of the size and value premia and the robustness of the Fama-French (FF) three-factor model in explaining the variation in stock returns. We document a statistically significant and persistent size effect or size premium that is robust even for non-January months but is heightened in January. We also find that the reversal of the size effect in January reported by Chui and Wei (1998) is unique to their study period, while the general reversal of the size effect reported by Lam (2002) may be due to a sample dominated by firms with low to medium book equity-to-market ratios. The book to market effect or value premium is weaker than the size effect and less consistent than in Fama and French (1993) and Drew and Veeraraghavan (2003). Our results also support the explanation that the size and value premia are rewards for risk bearing consistent with the efficient market hypothesis. We further find a large improvement in explanatory power provided by the French and Fama model relative to the CAPM but that the FF model is mis-specified for the Hong Kong market.

To brief a transaction volume-price probability wave equation, a new advance in econophysics; To introduce a notion of trading conditioning for the first time in terms of operant conditioning in psychology; To measure the intensity of market crowd’s trading conditioning by transaction volume probability; To test correlation between the rate of mean return and the change in the intensity of trading conditioning subject to the return, using high frequency data in China stock market; To study market crowd’s learning and psychological behavior by correlation analysis, and explain their behavioral“anomalies”by trading conditioning.

This study employs the Gerneralised Autoregressive Conditional Heteroskedasticity (GARCH) model to investigate the sensitivity of Chinese bank stock returns to market, interest rate and foreign exchange rate risks. Daily data are used to model these risks over the period 2007 to 2010. The results suggest that market risk is an important factor of Chinese bank stock returns, along with foreign exchange risk. However, interest rates risk tends to be insignificant factors in Chinese bank equity pricing process over the period considered.

In order to examine the new RMB exchange rate regime rigorously, we employ the STARTZ model to investigate the behavior of RMB NEER from June 1, 2006 to May 30, 2008, We find that a managed float with a target central parity and without an explicit band best describes the daily movement of the exchange rate between RMB and a basket of currencies. We also find some peculiar attributes of the RMB NEER such as small conditional variance and stronger effects of government interventions in foreign exchange market.

This paper consists of two parts. In the first part, through the calculation of “binomial correlation measure”, we suggest that from the perspective of default correlation it would be better to use structural approach rather than reduced form approach for pricing derivatives with two counterparties and its CVA calculation unless default intensities follow jump-diffusion process in latter one. In the second part, we derive the pricing model for CDS with counterparty risk and its CVA calculation by Black-Cox first passage time model in structural approach. Different from most of the previous paper our recovery is based on the CDS with counterparty risk, so the pricing model is a boundary-value problem of fully-nonlinear PDE. To solve it, we introduce an approximation problem by penalty model in reduced form approach by assuming an incentive function. Also finite element method and iteration approach are used. The numerical results show the convergence of approximation problem, iteration problem and finite element method, a comparison between CVA with different recovery rules and also the impact of wrong-way risk and right-way risk on CVA.

Insurance was one of industries that were opened very first after China’s accession to the WTO in 2001. During 2002 to 2005, there was a peak of the foreign insurers’ entry, with the rapid growth of their market share. However, in recent years, the foreign insurers found themselves not able to grow as fast as they have expected, which was described as their “Seven Year Itch” in China. Several cases of equity transactions have taken place in 2009-2010, mainly involved with the foreign insurers reducing their shareholdings. This was regarded as the sign of foreign insurers changing their strategies in Chinese market. In this paper we found strong evidence to show that the current performance of foreign insurers in China was relatively worse than that in the other major insurance markets. From the comparison of the regulatory environment and market performance, we can say for sure that regulation restrictions should be at least one of the major reasons for the current situation. Also we found that the “50-50” shareholding structure which was adopted initially by many life foreign insurers could be blamed for the slow growth recently. And poor bancassurance business performance could explain the shareholding reductions recently for some of the foreign life insurers.

This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen’s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ‘irrational’ and ‘speculative’. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China’s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

Building on the important study by Allen, Qian and Qian (2005) and Ayyagari, Demirgüc-Kunt and Maksimovic (2010), I examine whether third party guarantors play an effective role in assessing loan risk. Using a proprietary database of third party loan guarantees in China, I find strong evidence that guarantors and banks disagree on pricing loan risk, and that banks can better predict loan defaults than guarantors. I also find that the probability of loan default is affected by the capability of guarantor officers. My findings question the contribution of soft information in the improvement of credit scoring and support the view that informal finance should be limited. This paper also supports the implications of studies on human capital in financial intermediation.

Using a unique dataset from Chinese stock market, we present the facts that the investors with different levels of experiences tend to time their first purchases differently when trading the IPO stocks. First, we demonstrate that experienced investors are less likely to buy IPO stocks on the first day while inexperienced investors are more likely to do so. Then we find that those investors who buy on the first non-hit day can obtain higher return relative to those investors who buy the same stock on the first day. In sum, more experienced individual investors do learn from their experiences to be more patient and observe/analyze the target stock for longer time before purchase than the green hand. Moreover, their experiences can indeed help improve the performance.