Data Recovery

It appears you may have used Coursicle on this device and then cleared your cookies. You can recover your data by answering these questions.

User ID:

Your account no longer exists

Your user ID no longer exists. Please refresh the page. If the issue persists, please contact us at support@coursicle.com.

Dismiss

QSTMF 840 - Data Analysis and Financial Econometrics

Description
Grad Prereq: QST MF793 This is the second course of the econometrics sequence in the Mathematical Finance program. The course quickly reviews OLS, GLS, the Maximum Likelihood principle (MLE). Then, the core of the course concentrates on Bayesian Inference, now an unavoidable mainstay of Financial Econometrics. After learning the principles of Bayesian Inference, we study their implementation for key models in finance, especially related to portfolio design and volatility forecasting. We also briefly discuss the Lasso and Ridge methods, and contrast them with the Bayesian approach Over the last twenty years, radical developments in simulation methods, such as Markov Chain Monte Carlo (MCMC) have extended the capabilities of Bayesian methods. Therefore, after studying direct Monte Carlo simulation methods, the course covers non-trivial methods of simulation such as Markov Chain Monte Carlo (MCMC), applying them to implement models such as stochastic volatility. (Mathematical Finance courses are reserved for students enrolled in the Mathematical Finance program.)
Credits
3
Recent Professors
Open Seat Checker
Schedule Planner
Recent Semesters
Spring 2021, Spring 2020, Spring 2019
Offered
Th
Avg. Sections
2