Our interest in time series models stems from the need to assess how well empirical financial data fits various models.
Key concepts
- Strict and Weak Stationarity. A process is strictly stationary if it’s properties are unaffected by a change in the time origin. A process is weak stationary if the first and second moments exist and do not depend on time.
- Moving Average Processes and Autoregressive Models. Autocorrelation Function (ACF) , Lag Operators, Invertibility.
- Autoregressive Moving Average Processes (ARMA)
- Partial Autocorrelations. (PACF). Sample analogs, Significance testing, maximum Likelihood Estimation
- Forecasting with Time Series Models.