The Study On Stock Trading Manipulation Behavior Judgment And Early-warning By Complex Network Approach

The existence of stock price manipulation has brought great harm to the stock market.On the one hand,its existence makes the stock price deviate from the real value of the stock,seriously harms the interests of ordinary investors,and weakens the enthusiasm of small and medium-sized investors to participate and investment confiden ce;On the other hand,the stock price man ipulation restricts the effective allocation of market resources,if it exists for a long time,it will gradually shrink the stock market,and ultimately will inevitably cause great losses to a country's economy.In addition,since the establishment of China's stock market,the case of stock price manipulation h,as been frequent,and most of them belong to the vicious manipulation behavior events.The relevant regulatory bodies are also constantly striving to improve the regulatory system,but with the strengthening of supervision,the traditional pattern of long-term manipulation behavior gradually disappeared,short-term manipulation behavior patterns continue to become the mainstream.The timing of the manipulation has changed from 1 years or more to the present 1-2 days,and the entire manipulation process is extremely short and ends in 1-2 days.Thus,it will pose a challenge and a threat to the ability of regulators to respond quickly.It is found that the existing index of stock price manipulation behavior identification and early warning index are basically financial transaction indicators(such as daily yield,volatility,turnover rate,etc.)and financial indicators.However,these indicators can only be calculated after the end of a trading day,so there is a serious lag in the existing discriminating methods.It simply can not immediately screen the stock market manipulation behavior,only applicable to the traditional long-term manipulation behavior,and does not apply to the current mainstream short-term manipulation behavior.In view of this,based on the existing research results,starting from the perspective of complex networks,this paper mainly studies from the following aspects:(1)Based on the China Securities Regulatory Commission found in 2015 in the Shanghai and Shenzhen A-share market trading stock manipulation cases as a sample,this paper used intraday pen tick transaction data,the stock buyers and sellers of the Commission declarations ID as a node,to the buyer and seller commissioned declarations whether the transaction for the connection to build a stock trading network.(2)Construct the model of stock trading manipulation behavior discrimination.Firstly,13 items,such as network density,number of nodes and number of connections,are screened by stepwise logistic regression method,which can describe the network parameters which are significantly different between the manipulated behavior stock and the non-manipulated behavior stock.Then,5 main explanatory factors are extracted by factor analysis method.Finally,based on the main factors extracted,the model of stock trading manipulation behavior discrimination is constructed.(3)To divide the community structure of the stock trading network constructed in the preceding article.In order to find the community structure hidden in the network topology,improve the accuracy of the early warning of stock price manipulation behavior.In this paper,from the perspective of Community structure,the Louvain algorithm,VOS clustering algorithm and GN algorithm are used to divide the built stock trading Network,and then compare which partitioning method works better.(4)The design of the early warning system of stock trading manipulation behavior is conceived.Aiming at the present situation that the cycle of manipulation behavior is getting shorter and the manipulation behavior is becoming more and more hidden,this paper selects the complex network parameters and the community structure parameters with high sensitivity as the early warning index,constructs the stock trading manipulation behavior Early Warning index by using the selected parameters,and divides the grade to the stock price manipulation behavior warning according to the comprehensive index score.It was eventually validated in one case.Through this article step by step research and analysis,in the end,mainly got the following three conclusions:(1)The model of stock trading manipulation behavior based on complex network parameter factors has a high accuracy rate.The empirical results show that the overall accuracy of the test in the sample of the discriminant model constructed in this paper is 86.60%,and the overall accuracy of the sample external test is 86.50%.The results of this paper can provide technical support for securities regulatory departments to effectively identify stock trading manipulation behavior,allocate regulatory resources rationally,and crack down on market manipulation.(2)In the division of the stock trading manipulation behavior Network,the algorithm suitable for dividing the network constructed in this paper is selected,and Vos clustering is the best compared with the division effects of VOS Clustering algorithm,Louvain algorithm and GN algorithm.In most cases,the division result of Louvain algorithm is better than the division result of GN algorithm.(3)The ring growth rate of the number of nodes,the ring growth rate of the number of elements,the growth rate of the maximum number of elements,the growth rate of the community number,the network density and the maximum group size(proportion)can be used as an early warning index of stock trading manipulation behavior.According to the research purpose of this paper,combined with the research contents and achievements of this paper,according to the various subjects in the stock market?the following countermeasures and suggestions are put forward respectively.