ARCH and GARCH Models

Related lectures (31)

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Covers volatility modeling in risk management, including ARMA, ARCH, GARCH models, causal representation, and forecasting.

Delves into implied volatility, historical volatility, option pricing implications, and various volatility models in financial innovation.

Explores long memory in time series and Autoregressive Conditional Heteroskedasticity processes in financial data.

Covers stylized facts of asset returns, summary statistics, testing for normality, Q-Q plots, and efficient market hypothesis.

Explores forecasting in time series analysis, long memory processes, and ARCH models for volatility modeling.

Explores structural modelling in time series and introduces the Kalman filter for prediction and estimation.

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Explores financial time series, including ARMA and GARCH processes, emphasizing risk estimation.

Covers structural modeling, state space models, and the Kalman filter in time series analysis.

Explores time series models, emphasizing autoregressive processes, including white noise, AR(1), and MA(1), among others.