Empirical Study On Liquidity Of Shanghai Stock Markets

Liquidity is the quality of an asset being readily convertible into other assets at a reasonable price and transaction costs. A functioning security market must have sufficient liquidity for the transfer of asset by investors. Liquidity is a hot subfield of market microstructure theory. Based on the transaction-level data for shang hai stock market, We try to make some efforts in this direction. The main outcomes and conclusions as follows:In part one we introduce the background and significance of our research,In part two we reviewed the previous literatures which are about the definition as well as four dimensions of the liquidity. Then according to transaction cost, we introduced various liquidity measures, the first category of liquidity proxies is more trading based-direct transaction cost, the second group focuses on the price impact of trades-indirect transaction cost.In part three, we conducted a comparison study focusing on the performance of widespread used liquidity measure. With the development of the global stock market, more and more studies focus on liquidity. Liquidity plays an increasingly important role in empirical asset pricing, market efficiency, and corporate finance. Identifying high quality proxies for liquidity based on daily data only(not intraday data)would permit liquidity to be studied over relatively long timeframes and across many markets. In the exploration of the best measures,Based on the high-frequency data for Shang Hai stock from2005to2008, we compare many liquidity proxies calculated from low-frequency data to sophisticated benchmarks of liquidity calculated from CSMAR high-frequency dataset using cross-sectional correlations, time-series correlations,and panel model. We find Illiq_Zero is the best low-frequency liquidity proxy. It shows the highest cross-sectional correlations with the effective bid-ask spread and the price impact of lambda and it improve the R2at least5percentage.In part four, our primary objective is to investigate the role of liquidity (proxied by Illiq_Zero)as an additional in asset pricing. Investors face liquidity risk when they transfer ownership of their securities. Therefore, investors consider liquidity to be an important factor when making their investment decisions. According to liquidity premium theory, expected return and liquidity should have a significant negative relation. We address the question of whether liquidity is an important variable to capture the shared time-series variation in stock returns by investigating whether the effect of liquidity stock return remains after controlling for the well-known stock return factors using Shang Hai stock data from2001to2010. These well-documented factors are beta, size, and book-to-market ratio factors. We adjust the stock returns by the augmented Fama-French factor model and adopt a time-series regression approach by employing portfolios. Our results show that liquidity is an important factor pricing returns in Shang Hai after taking well-documented asset pricing factors into consideration. We also check the robustness of liquidity and model by investigating higher moment coskewness for possible missing factors, up-and down-market for a conditional market effect, through these, we find that the best model in Shang Hai security market is a liquidity four-factor model that includes market excess return, size, book-to market ratio, and the liquidity factor.Part five concludes the paper.