Chinese stock-oriented informed trading probability calculation method

Abstract

The invention discloses a Chinese stock-oriented informed trading probability calculation method. The method comprises the following steps of: aiming at features of the Chinese stock market, importingnew variables and constructing a Chinese stock market-oriented extension model for informed trading probability calculation; re-deducing a maximum likelihood function for parameter estimation and anextension formula for calculating informed trading probabilities according to the extension model; by adoption of a genetic algorithm, taking the deduced maximum likelihood function as a fitness function and accelerating operation of the genetic algorithm by using parallel equipment so as to obtain an optimal estimation result of a parameter; and calculating an extended informed trading probability according to the optimal parameter obtained by the genetic algorithm so as to obtain a generalized informed trading probability value suitable for Chinese conditions. According to the method, factors that investors consider to be located in bad situations in games when no message exists and the like are considered, so that information asymmetric condition of the Chinese stock market can be measured more accurately; and the parallel genetic algorithm is used for carrying out calculation, so that the calculation process can be accelerated.

Description

technical field [0001] The invention relates to the technical field of stock research, in particular to a method for calculating the probability of informed trading for Chinese stocks. Background technique [0002] 1) Informed trading probability for Chinese stock market [0003] In the Chinese stock market, where there is a lot of room for improvement in insider trading supervision and relatively high short-selling restrictions, information acquisition will become a decisive factor for stock trading profits. At this time, on the one hand, when investors have no news, they will think that they are in a disadvantaged position in the game. At this time, "no news is bad news". Investors in this situation will be more inclined to sell stocks to avoid losses. On the other hand, under the condition of "no news is bad news", the proportion of evasive investors' stocks sold in the total sold stocks will increase with the increase of information asymmetry. As "no news" investors, s...

AI Technical Summary

Problems solved by technology

An optimization process involved in maximum likelihood estimation (seeking the maximum or minimum value), for different objective functions, different optimization algorithms need to be selected, and it is difficult to achieve the ideal convergence effect (only local optimal and slow)

The above-mentioned problems are also involved in the process of maximum likelihood estimation of the probability of informed trading. At present, no optimization algorithm designed for the objective function of the probability of informed trading has been found, and the default optimization algorithm of mathematics / statistical software such as Matlab is generally used.

[0007] Secondly, for the calculation of the probability of informed trading, for different stocks, different time intervals (such as scales of months, days, hours, etc.) are used, and the values ​​of the probability of informed trading at different times are different. Therefore, if you need to construct a The probability of informed trading of a single stock or even all listed stocks at all times, the amount of calculation is extremely huge, and the current implementation method cannot meet the actual calculation needs

Images