Time Series Analysis (TSA) in Python - Linear Models to GARCH
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Post Outline
- Motivation
- The Basics
- Stationarity
- Serial Correlation (Autocorrelation)
- Why do we care about Serial Correlation?
- White Noise and Random Walks
- Linear Models
- Log-Linear Models
- Autoregressive Models - AR(p)
- Moving Average Models - MA(q)
- Autoregressive Moving Average Models - ARMA(p, q)
- Autoregressive Integrated Moving Average Models - ARIMA(p, d, q)
- Autoregressive Conditionally Heterskedastic Models - ARCH(p)
- Generalized Autoregressive Conditionally Heterskedastic Models - GARCH(p, q)
- References
