Do you want to do some quick, in depth technical analysis of stock prices?
After I left CERN to work as consultant and to earn an MBA, I was engaged in many exciting projects in the finance sector, analyzing financial data, such as stock prices, exchange rates and so on. Obviously there are a lot of available models to fit, analyze and predict these types of data. For instance, basic time series model arima(p,d,q), Garch model, and multivariate time series model such as VARX model, state space models.
Although it is a little hard to propose a new and effective model in a short time, I believe that it is also meaningful to apply the existing models and methods to play the financial data. Probably some valuable conclusions will be found. For those of you who wish to have data to experiment with financial models, I put together a web application written in R:
Recently Tableau released an exciting new feature: R integration via RServe. Tableau with R seems to bring my data science toolbox to the next level! In this tutorial I’m going to walk you through the installation and connecting Tableau with RServe. I will also give you an example of calling an R function with a parameter from Tableau to visualize the results in Tableau.
1. Install and start R and RServe
You can download base R from r-project.org. Next, invoke R from the terminal to install and run the RServe package:
[Update 26 Jun 2016]: Tableau 8.1 screenshots were updated with Tableau 10.0 (Beta) screenshots due to my upcoming Advanced Analytics session at TC16, which is going to reference back to this blog post.
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