Abstract:Based on the data of Shanghai A-share market and listed companies during the period of 2005 to 2011，this paper makes a comparative study between the effects of individual and institutional investor senti_x005fment，aiming to clarify their roles in the stock market． Previous studies have mostly studied the interactions of these two or the impacts of either on the market．Instead，we focus on both of them and go deeper into the stock level from a new perspective: quantifying the sensitivity of stock returns to investor sentiment changes by rolling regression． Based on the DSSW model，this study sets up a theoretical model which combines the interactions of individual and institutional investor sentiment．The results show that institutional sentiment can predict individual sentiment，while the converse is not true． Institutions are relatively rational and their sentiment can predict the market returns，while individual sentiment cannot．The findings further indicate that the sensitivity of stock returns to investor sentiment changes is comparatively higher for those stocks with higher market attentions．This phenomenon has showed the consistency between sensitivity of stock returns to individual sentiment changes and institutional sentiment changes．

Abstract:The Chinese stock markets have been designated as policy markets since they were founded． The macroeconomic information plays an important role in the changes of stock prices． This paper explores the effects of macroeconomic information on the stock price synchronicity at industry level in Chinese stock mar_x005fkets． The results show that macroeconomic information，such as Gross Domestic Product ( GDP) ，has significant impacts on the industrial stock price synchronicity of all industries except finance and insurance． The extent of stock price synchronicity varies among industries． Furthermore，the extent of synchronicity of each industry differs between bull and bear market，i． e． ，the synchronicity is higher in the bear market than it is in the bull market． These demonstrate that the synchronicity in Chinese stock markets is characterized by both industrial idiosyncrasy and market performance．

Abstract:Conditional Value-at-Ｒisk ( CVaＲ) model developed recently is a powerful mathematical tool to measure financial risk． By constructing on the risk optimization and risk hedging models based on the CVaＲ kernel estimator and designing an optimization algorithm to solve these models，this paper accomplishes the goal that financial risk estimation and risk management are implemented at the same time． These models are applied to Chinese A stock market，and the following conclusions are obtained: nonparametric kernel estima_x005ftion method can capture the tail feature of the risk factor distribution and give more accurate risk estimation results． The risk optimization model based on CVaＲ kernel estimator can find out the true minimum risk and corresponding portfolio． Compared with Variance-Covariance method and Cornish-Fisher expansion of CVaＲ， the risk hedging effect based on CVaＲ kernel estimator is the best．

Abstract:Selecting the trading information of corporate bonds with the credit rating of AAA and treasury bonds in China’s bond market on a monthly basis，and solving the Svensson ( 1995) model of term structure of interest rates through genetic algorithm，the paper gives more exact yield curves of both types of bonds and derives the credit spreads． After time series analysis of China’s bonds with different terms of maturity，it can be concluded that all the credit spread series have one unit root and show the characteristics of autoregressive and moving average． The Ｒ-squared of AＲMA model gives better fitness than the multiple linear regression model． The VAＲ model can fit the dynamic relationship among credit spreads well． Impulse response analysis implies that the shock from other series of credit spreads to one sequence of credit spread will result in severe fluctuations with low magnitude in the first 10 terms and the impact does not have long and continuous effect． The empirical results provide the basis of decisions for investors and regulators to some extent．

Abstract:Empirical findings suggest two violations of the Black-Scholes model: the volatility smile and the asymmetrical distribution for underlying asset returns．Although stochastic volatility models based on the no-ar_x005fbitrage theorem can explain these two phenomena，the alternative pricing method under general equilibrium framework has been seldom studied． The traditional equilibrium model incorporating the expected utility fails to differentiate the investor’s different risk preferences towards the diffusive uncertainty and the jump risk． However，with the fanning preference，the model is able to capture an additional risk premium，and generates a pronounced volatility smile． On the other hand，adopting the fanning effect results in a leptokurtic and leftskewed distribution．

Abstract:This paper builds an investor sentiment index by using data of Shanghai stock exchange，filters out its autocorrelation，and obtains the innovation of investor sentiments．We divide investor sentiments into posi_x005ftive and passive investor sentiment，and analyze the characteristics of investors’behavioral traits in different sentiment states．We then research the asymmetrical influence of positive and negative emotion on stock price behaviors by using Dummy Variable model，GARCH-model and RV-AR-model． The results show that in Chinese stock market，the models which consider different sentiment states have better fitting effects; positive investor sentiment has a significant impact on stock returns，but the effect of passive investor sentiment on stock returns is not significant since the rational component plays a leading role in the market when sentiment is low．Besides，the volatility of investor sentiment has a great explanation ability to the volatility of stock returns．

Abstract:Information disclosure is very important in financial crisis contagion．Based on the rational expectations model of asset pricing，many scholars have studied the impact of one-time information disclosure on contagion．Considering that information is always disclosed by stages，we develop a 3-period model to analyze the impacts of information disclosure level and information correlation between periods of contagion．The numerical simulation shows that i) gradual disclosure can aggravate contagion，and ii) when information is disclosed by stages，the more the information of period 0 is disclosed or the more the information correlation between periods is，the more serious the contagion will be．

Abstract:Over the past decade，financial markets have witnessed an explosion of algorithmic trading strategy which can help investors efficiently reduce transaction cost．In order to reduce the trading cost，investors usually break block orders into small pieces in high-frequency trading． However，the behavior of such order splitting may result in inevitable opportunity cost as well as timing risk．This paper establishes a new algorithmic trading strategy to minimize implicit trading costs，including the market impact，opportunity cost，timing risk and the price appreciation．We find the performance of our optimal algorithmic trading strategy is better than that of MIOC or VWAP strategies in all the cases of increased，decreased and U-shaped execution probability．The new algorithmic trading strategy established in this paper can effectively reduce the trading cost．