Quantitative Risk Management: Volatility Modeling

Related lectures (31)

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

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

Covers risk and return tradeoffs in portfolios, diversification benefits, and the efficient frontier with multiple assets.

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

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

Introduces Maximum Likelihood Estimation in econometrics, covering principles, properties, applications, and specification tests.

Covers swaptions, moneyness, callable bonds, pricing formulas, and implied volatilities.

Delves into finance, emphasizing risk and return in investments, covering free cash flow, dividends, NPV, EBIT, and portfolio analysis.

Covers parametric estimation, seasonal modeling, Box-Jenkins methods, variance calculations, and dependence measures in time series analysis.

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.