Intro to Computational Finance with R

Learn how to calculate, analyze and plot simple and continuously compounded returns in R.

Learn how to work with probability distributions in R in the context of return and value-at-risk calculations.

Explore bivariate probability distributions in R.

Learn how to use R to simulate autoregressive and moving average processes.

Learn how to analyze stock returns with the R packages PerformanceAnalytics, zoo and tseries.

Estimate parameters of the constant expected return (CER) model, compute standard errors and confidence intervals and test various hypotheses about the parameters and assumptions of the model. Perform bootstrapping of CER model estimates.

Compute portfolios that consist of Boeing and Microsoft, T-bills and Boeing, T-bills and Microsoft and T-bills and combinations of Boeing and Microsoft. Use R functions to compute the global minimum variance portfolio and the tangency portfolio.

Using the monthly closing price data on four Northwest stocks, you will estimate expected returns, variances and covariances to be used as inputs to the Markowitz algorithm. You will compute the global minimum variance portfolio, efficient portfolios, and the tangency portfolio for short-sales allowed and for short-sales not allowed.