Empirical Researches In Security Market

Since 1950s, the researches in financial market have made great progress. At the same time, with the developing of the computer science, it makes possible for financial researchers to study the market by using the high frequency data. The Chinese financial market is newly built, and differs from other mature markets, which makes it necessary to take a close sight on the research of the Chinese financial market. In this thesis, we made a further study of the microstructure of the market by applying the methods in econophysics and econometrics. Besides, we also discuss the new methods in recent financial market research field, and we propose an utility based sequential investing theory, based on with a rotation strategy is also proposed.In the study of the microstructure of the financial market, we first give our attention on the bid-ask spreads on the Chinese stock market. By using a Lomb analysis, a daily periodicity in the spread time series is confirmed, and it is recognized as an L-shaped pattern, which is different from the U-shaped pattern discovered on the other market. The intraday spread of individual stocks relaxes as a power law within the first hour of the continuous double auction from 9:30 AM to 10:30 AM with exponentsβSHSE= 0.20±0.067 for the Shanghai Stock Market andβSZSE=0.19±0.069 for the Shenzhen Stock Market. The power-law relaxation exponentβof individual stocks is roughly normally distributed. There is evidence showing the accumulation of information widening the spread is an endogenous process.Second, we focus on the behavior of traders on canceling the orders on the order-driven market by using the ultra-high frequency data provided by the Shenzhen Stock Exchange. We investigate the dynamics of order cancelation by studying the statistical properties of inter-cancelation durations, defined as the waiting times between consecutive order cancelations of 22 liquid stocks traded on the Shenzhen Stock Exchange of China in year 2003. Three types of cancelations are considered, including cancelation of any limit orders, of buy limit orders and of sell limit orders. We find that the distributions of the inter-cancelation durations of individual stocks can be well modeled by Weibulls for each type of cancelation, and the distributions of rescaled durations of each type of cancelations exhibit a scaling behavior for different stocks. Complex intra-day patterns are also unveiled in the inter-cancelation durations. The detrended fluctuation analysis (DFA) and the multifractal DFA show that the intercancelation durations possess long-term memory and multifractal nature, which are not influenced by the intra-day patterns. No clear crossover phenomenon is observed in the detrended fluctuation functions with respect to the time scale. These findings indicate that the cancelation of limit orders is a non-Poisson process, which has potential worth in the construction of order-driven market models. However, in the second part of the analysis of the cancelations based on event time, we derive the different results. The distribution densities of the cancelation intervals no longer show a scaling behavior, and the behavior of cancel well obeys a truncated Poisson distribution, which well serves the study of building the models in event study.Third, we make a research on the aggressive of the market traders. By analyzing the order book data, we get the conclusion as followings:(1) the depth of the order book (including the depth of the buy side and the sell side) has a positive affect on the orders, i.e. when there is an increment on the depth of the order book, both the buy order and the sell order will get more aggressive. However, the influence is proved to be tiny. (2) bid-ask spread has a negative relationship with the order aggressive, which means that most market traders are cost averters, who are much willing to take risk than taking the high transection cost. (3) high frequency buy order submitting has a positive relationship with the buy order aggressive, while the low frequency sell order submitting force the traders submit aggressive sell orders. (4) unstable price movements make the traders much more patient.In the discussion of the newly designed methods for the research of the financial market, a visibility graph approach is first introduced. We investigate the visibility graphs extracted from fractional Brownian motions and multifractal random walks, and find that the degree distribu-tions exhibit power-law behaviors, in which the power-law exponent a is a linear function of the Hurst index H of the time series. We also find that the degree distribution of the visibility graph is mainly determined by the temporal correlation of the original time series with minor influence from the possible multifractal nature. As an example, we study the visibility graphs constructed from three Chinese stock market indexes and unveil that the degree distributions have power-law tails, where the tail exponents of the visibility graphs and the Hurst indexes of the indexes are close to the a-H linear relationship.Second, we talk about a return estimating process proposed by Levy and Roll. Here, we present a series of tests and applications. We apply first the Levy-Roll procedure to the 25 Fama-French portfolios sorted by size and book-to-market value. We check the consistency of the Levy-Roll approach by investigating how the adjusted stock returns of specific stocks are modified when varying the basket of stocks they belong to. We test the dynamic performance of the Levy-Roll procedure over the period from January 1992 to December 2009. Finally, we show how to exploit the method for better portfolio allocations.Third, we propose an utility based sequential investing theory. Under the hypothesis of the theory, we find that the utility of the market traders is mainly depended on the mix of market increasing probabilityβand the efficiency of the trading strategy taken by the traders. We show that only whenβ+α≥1, the market traders can derive the positive utility through transactions. Besides, we also show that by taking more than 2 assets into analysis, the trader will get much greater utility than by taking only 1 asset, and the utility increase with the number of asset to be analyzed. But there is a limitation of the utility, it equals to 2 times of the utility of 1 asset analysis. Under our utility based sequential investing theory, we propose a rotation strategy and a series of criterion for testing the investing strategy. In the empirical test of the strategy, the rotation strategy can get higher cumulative returns than both of the single chosen stocks. In the simulation test of the strategy, the rotation strategy also performs relatively good.