Technical Analysis indicators calibration using Cellular Automaton Algorithm for use in high-frequency trading

The present study was conducted with the aim of localizing technical analysis indicators in the Tehran Stock Exchange in order to predict stock price movement trends in implementing high frequency trading by the momentum method. In this study, calibration of exponential moving average, Bollinger Bands, Relative Strength Index (RSI), degree of difference, stochastic indicator and cash flow index was performed using cellular automata algorithm. The statistical population of this research consists of data obtained from transactions performed in the Tehran Stock Exchange during a three-year period from 7/23/2019 to 7/22/2019. According to the obtained results, there is a need to change the periodicity of the indicators calculations, so that the indicators of exponential moving average, Bollinger Bands, relative strength index, degree of difference, the stochastic indicator, the cash flow index have been changed from 14 to 2 days, 20 to 2 days, 14 to 13 days, 12 to 2 days, 14 to 4 days, and 14 to 20 days, respectively. As a result of the changes made, the increases in predictive power of the above indicators were achieved up to 1.35%, 36.90%, 1.89%, 30.52%, 64.20%, 0.24%, respectively.