Stochastic processses

Related lectures (32)

Page 1 of 4

Covers the optional stopping theorem for martingales, providing a detailed proof and discussing its implications.

Explores the generation of multivariate Gaussian distributions and the challenges of factorizing covariance matrices.

Covers the Fourier transform, spectral densities, Wiener-Khinchin theorem, and stochastic processes.

Explores Brownian motion with drift, exit probabilities, and average exit times from intervals.

Explores three stopping theorems in martingales and Brownian motion.

Explores sub- and supermartingales, stopping times, and their applications in stochastic processes.

Covers Doob's decomposition theorem for submartingales and explores Brownian motion properties, quadratic variation, and continuous martingales.

Explores stopping times, the optional stopping theorem, F-measurable random variables, and martingales.

Discusses convergence, martingales, Brownian motion, joint laws, testing procedures, and stop times.

Explores Levy Flights and Brownian Motion, focusing on probability distributions and divergences in lag time.