Lectures related to Financial Time Series: Stylized Facts and Models

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

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

Explores risk and return in finance, covering securities' performance, rates of return, variance, volatility, and portfolio diversification.

Covers stylized facts in finance and reproducible research in scientific computing.

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

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

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

Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.

Explores ARCH and GARCH models, volatility clustering, time series, estimation, and filtering steps in financial and macroeconomic contexts.

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

Explores the tradeoff between risk and return in portfolios, the benefits of diversification, and the impact of correlation on portfolio risk.

Explores efficient portfolios, risk management, and the CAPM model in finance.

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

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

Explores portfolio optimization, efficient frontier, CAPM, and risk management in finance.

Covers GARCH processes for financial time series analysis.

Covers the analysis of heavy-tailed price returns and clustered volatility in financial data.

Explores linear filtering, spectral estimation, and second-order stationarity in time series analysis.

Explores the Black-Scholes formula for option pricing and risk-neutral pricing in financial economics.