Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets

This research represents some thoughts on the accurate characterization of the stock market indexes trends in the conditions of the nonlinear capital flows at the stock exchanges in the global capital markets. We make our original research proposal that the nonlinear capital flows in the process of the electronic trading can originate the nonlinear changes of the stock market indexes at the stock exchanges in the global capital markets. We suggest that the econophysics techniques can be used to precisely characterize the nonlinearities in the finances. We performed the research of the nonlinearities in Matlab, researching: 1) the ideal dependence of the stock market index over the time, 2) the linear dependence of the stock market index over the time, 3) the quadratic dependence of the stock market index over the time, 2) the exponential dependence of the stock market index over the time. We researched the following indexes: 1) The Dow Jones Industrial Average (DJIA) index; 2) The Standard and Poor’s 500 (S&P 500) index; 3) The NYSE Composite index; 4) The Hong Kong Hang Seng index; 5) The Shanghai Composite index; 6) The Financial Times Securities Exchange (FTSE100) index; 7) The Deutscher Aktienindex (DAX) index; 8) The Nikkei 225 Stock Average index over the certain time periods. The selected time periods were: 6 months; 12 months; 24 months. We assumed that, in every considered case, there are the complex changes of the company valuation, foreign exchange rates, interest rates, prices of strategic commodities over the specified time period. We found that there are the nonlinearities in the characteristic dependences of the stock exchanges indexes on the time. Our research results are in a good agreement with the research findings in Abhyankar, Copeland, Wong (1995, 1997), however the multiple evidences of quantum chaos were found in the researched stock market indexes dependences for the first time.