ARCH and GARCH Models: Volatility Forecasting

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Quantitative Risk Management: Volatility Modeling

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

Maximum Likelihood Theory & Applications

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Long Memory and ARCH: Time Series Math 342

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

Basics of Linear Regression

Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.

Principles of Finance: Risk and Return

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

Probabilistic Models for Linear Regression

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Regression: Simple and Multiple Linear

Covers simple and multiple linear regression, including least squares estimation and model diagnostics.

Linear Regression: Estimation and Inference

Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.

Elements of Statistics: Probability, Distributions, and Estimation

Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

Linear Regression Basics

Covers the basics of linear regression, including OLS, heteroskedasticity, autocorrelation, instrumental variables, Maximum Likelihood Estimation, time series analysis, and practical advice.