This paper examines continuous-time models for the price and volatility processes of individual stocks and the S …

that generate large drawdowns, and we correctly predict conditional drawdowns. In addition, investment strategies based on …

Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data … to predict the regimes of six global economic indicators and find the time periods in the past during which these … country world index (ACWI) in the identified time periods to assign a weighted score for each stock factor and to calculate …

. Second, we estimate one-step Markov-switching models with time-varying transition probabilities using the diffusion indices …

linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an … heteroscedasticity-generalised extreme value distribution (SARIMA-MS-EGARCH-GEVD) estimates. A time series of the study is a five …-day financial time series exchange/Johannesburg stock exchange-all share index (FTSE/JSE-ALSI) for the period of 4 January 2010 to …