The ARIMA model is a statistical tool used to analyze time series data to understand trends or predict future outcomes, often applied in financial markets. ARIMA combines autoregressive and moving ...

Time Series Methods Time series models assume the future value of a variable to be a linear function of past values. If the model is a function of past values for a finite number of periods, it is an ...

Parks Method (Autoregressive Model) Parks (1967) considered the first-order autoregressive model in which the random errors uit , i = 1, 2, ... , N, t = 1, 2, ... , T, have the structure where The ...

Yang Bai, Jian Huang, Rui Li, Jinhong You, SEMIPARAMETRIC LONGITUDINAL MODEL WITH IRREGULAR TIME AUTOREGRESSIVE ERROR PROCESS, Statistica Sinica, Vol. 25, No. 2 (April 2015), pp. 507-527 ...

This paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model.

We propose a multiplicative component conditional autoregressive range (MCCARR) model to capture the "long-memory" effect in volatility. We show both theoretically and empirically that the MCCARR ...