Identifying Actionable Serial Correlations in Financial Markets

Financial markets are complex systems where information processing occurs at multiple levels. One signature of this is the existence recurrent sequences. In paper, we developed a procedure for finding these sequences and process statistical significance testing to identify most meaningful ones. To do so, downloaded daily closing prices Dow Jones Industrial Average component stocks, as well various assets like stock market indices, United States government bonds, precious metals, commodities, oil gas, foreign exchange. We mapped each financial instrument letter their upward movements words, before frequencies words against null model obtained by reshuffling empirical time series. then leaders followers from statistically significant in different cross sections instruments, interpret actionable trends that can be traded upon.