Predicting algorithm of strong falls of Dow Jones Industrial Average
In this work problem of Dow Jones falls forecasting is considered. Financial and seismic time series is similar in respect of statistic properties. Based on earthquake’s forecasting techniques predictive algorithm is developed using changing of empirical distribution function of detrended time series of closing prices at moment before crisis. The algorithm is able to forecast all of the index falls, which are classified like objects. Trading strategy is suggested to estimate practical applicability of algorithm’s results. Currently the algorithm is being checked by real time analysis. It has successfully predicted 3 objects in 2 years.
Mathematical modelling in actual problems of science and technics