Lectures related to Price Returns Analysis

Covers the concept of multiperiod binomial pricing and the Black-Scholes formula.

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

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

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

Covers the theory of sampling, focusing on statistics for mathematicians.

Covers ECDF, quantiles, mean, median, and box plots for dataset analysis.

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

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Explores mean-variance efficient portfolios, factor models, and market efficiency in investment management.

Investigates how birth month influences athlete success, analyzing Japanese athletes' dataset to explore trends in birthdates and occupations.

Covers continuous random variables, probability density functions, and distributions, with practical examples.

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

Discusses vectors of random variables and empirical distributions, including their properties and significance in statistics.

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

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

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

Explores joint random variables, conditional density, and independence in probability and statistics.