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by Daniel Hanson


Last time, we used the discretization of a Brownian Motion process with a Monte Carlo method to simulate the returns of a single security, with the (rather strong) assumption of a fixed drift term and fixed volatility.  We will return to this topic in a future article, as it relates to basic option pricing methods, which we will then expand upon.

In case you missed them, here are some articles from May of particular interest to R users:  

Karl Broman's hipsteR guide lists some new(ish) features of R that early adopters may have missed.

I saw this video from the Bottle Boys the other day, and I've had Billie Jean stuck in my head ever since:


Billie Jean seems to be a popular song to harmonize to! That's all for now — enjoy your weekend, and we'll be back on Monday.

"A growing body of evidence that indicates that the most meaningful way to access predictive analytics and enhance the reputation of Data Science is through open source analytics, which greatly hinges upon the free open source programming language R", according to Dataversity in the recent article "The Relevance of Open Source (Advanced) Analytics". The article also includes several business use cases for R.

It was a great honour to be able to present to the China R Users Conference in Beijing last month, and share various applications of R that I've encountered recently. I was really invigorated by the enthusiasm of the many R users at the conference, and everyone was very warm and friendly. Here's a photo I took from the stage, so you can see how many people were there (and you can't even see the balcony in this photo):

Check out this tweet:

Spreadsheets remain an important way for people to share and work with data. Among other providers, Google has provided the ability to create online spreadsheets and other documents.

Back in 2009, David Smith posted a blog entry on how to use R, and specifically the XML package to import data from a Google Spreadsheet. Once you marked your Google sheet as exported, it took about two lines of code to import your data into a data frame.