Implementing Monte Carlo Method in R

by Chase DeHan

Some problems are difficult or impossible to solve with standard mathematical or statistical approaches - these can often be solved by using the Monte Carlo method. This course covers multiple Monte Carlo applications for ready use.

What you'll learn

Repeated sampling using the Monte Carlo method can be a much more efficient approach in solving difficult problems vs. standard mathematical or statistical practices. In this course, Implementing Monte Carlo Method in R, you’ll gain the ability to build your own Monte Carlo simulations using a variety of approaches and know which solution is most effective. First, you’ll explore the basics behind Monte Carlo and the fundamental functions in R. Next, you’ll discover some simple methods, followed by simulations on stock and commodities data for estimating return probabilities. Finally, you’ll learn how to use Monte Carlo methods on A/B tests. When you’re finished with this course, you’ll have the skills and knowledge of Monte Carlo methods needed to implement these methods yourself.

About the author

Chase is currently Lead Data Scientist at Tesorio and formerly was an Assistant Professor of Finance and Economics at the University of South Carolina Upstate. He holds a BS, MS, and PhD, all in Economics, from the University of Utah. Prior to graduate school, Chase served two combat tours to Iraq with the US Marine Corps and competed in the 2010 Winter Olympic Trials in Bobsled. Chase is passionate about building automated machine learning systems and is a regular speaker at academic and pra... more

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