Abstract We address the calibration issues of weighted-indexed semi-Markov chain (WISMC) model applied to high-frequency financial data. Specifically, we propose automate discretization price returns and volatility index by using four different approaches, two based on statistical quantities, namely, quantile sigma discretization, derived application popular machine learning algorithms, namely ...