STATS 245P
Time Series Analysis
Statistical models for time series. Topics include linear models for trends; stationary time-series; non-stationary time series; forecasting and Kalman filtering; time-series smoothing; seasonal models; ARCH, GARCH and stochastic volatility models; multivariate time series; vector autoregressive models; spectral analysis; case studies.
Topics
- linear models for trends
- stationary time-series
- non-stationary time series
- forecasting and Kalman filtering
- time-series smoothing
- seasonal models
- ARCH
- GARCH and stochastic volatility models
- multivariate time series
- vector autoregressive models
- spectral analysis
- case studies
Topics explicitly listed in official catalogue description
Prerequisites & course information
Statistical models for time series. Topics include linear models for trends; stationary time-series; non-stationary time series; forecasting and Kalman filtering; time-series smoothing; seasonal models; ARCH, GARCH and stochastic volatility models; multivariate time series; vector autoregressive models; spectral analysis; case studies.
Sources
- Course catalogue ↗2026-2027