Introduction to Computational Finance and Financial Econometrics – Data Camp

In this course, you’ll make use of R to analyze financial data, estimate statistical models, and construct optimized portfolios. You will learn how to build probability models for assets returns, the way you should apply statistical techniques to evaluate if asset returns are normally distributed, how to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and the usage of optimization methods to construct efficient portfolios.

Course Program:

• Lab 1 – Return calculations
• Lab 2 – Random variables and probability distributions
• Lab 3 – Bivariate distributions
• Lab 4 – Simulating time series data
• Lab 5 – Analyzing stock returns
• Lab 6 – Constant expected return model
• Lab 7 – Introduction to portfolio theory
• Lab 8 – Computing efficient portfolios using matrix algebra

Duration

About 7 Hours

• This course is for everyone interested in finance. There are no hard requirements, but having a good mathematical basis, and an interest in financial markets is recommended.

• Eric Zivot (University of Washington)