Monthly Archives: June 2013

Strategy 1 Extended (Part 1)

June 26, 2013
By
Strategy 1 Extended (Part 1)

Like I said in my previous post, there are two ways I could think of, off the top of my head, to implement a 2-day or 5-day extension to the previous strategy. One way would be just a simple extension … Continue reading →

Read more »

Trading Strategy 1: What goes up, goes up…

June 26, 2013
By
Trading Strategy 1: What goes up, goes up…

As I said earlier, my main task at my internship is to hunt for profitable strategies. As you can imagine, strategies can range from the exceedingly simple and easy to implement, to the crazily complex. Let’s start out with one … Continue reading →

Read more »

Looking out for volatility

June 26, 2013
By
Looking out for volatility

Let’s do an easy experiment. Lets caluclate the 25-day rolling volatility of the S&P 500 from 2007 onwards. 1-Get the data: getSymbols(‘SPY’,from=’2007/01/01′) 2-Run the volatility function from the package TTR (comes along with quantmod): vol=volatility(SPY,n=25,N=252,calc=’close’) #n=25 means we want 25 … Continue reading →

Read more »

Using R: Two plots of principal component analysis

June 26, 2013
By
Using R: Two plots of principal component analysis

PCA is a very common method for exploration and reduction of high-dimensional data. It works by making linear combinations of the variables that are orthogonal, and is thus a way to change basis to better see patterns in data. You either do spectral decomposition of the correlation matrix or singular value decomposition of the data

Read more »

Technical(and not technical) strategy testing

June 25, 2013
By
Technical(and not technical) strategy testing

I got "hooked" on OOP approach of R in particular reference classes. And after my last little project on option scenario analysis I reconstructed my messy technical strategy testing code.Now to begin I would like to reason why I have done this while there exists a nice "blotter" and "quantstrat" packages.First of all "quantstrat" is faster than blotter, which...

Read more »

Natural language processing tutorial

June 25, 2013
By
Natural language processing tutorial

Introduction This will serve as an introduction to natural language processing. I adapted it from slides for a recent talk at Boston Python. We will go from tokenization to feature extraction to creating a model using a machine learning algorithm. The goal is to provide a reasonable baseline on top of which more complex natural language processing can be...

Read more »

My talk at Boston Python

June 25, 2013
By

I just gave a talk at Boston Python about natural language processing in general, and edX ease and discern in specific. You can find the presentation source here, and the web version of it here. There is a video of it here. Nelle Varoquaux and Micha...

Read more »

rClr: low level access to .NET from R

June 25, 2013
By
rClr: low level access to .NET from R

rClr is a package to access arbitrary .NET code seamlessly. The "CLR" acronym part of the package name stands for Common Language Runtime. C# and R being languages I regularly use, I have felt the need for better interoperability between these for a fe...

Read more »

Split violin plots

June 25, 2013
By
Split violin plots

(This article was first published on Ecology in silico, and kindly contributed to R-bloggers) Violin plots are useful for comparing distributions. When data are grouped by a factor with two levels (e.g. males and females), you can split the violins in half to see the difference between groups. Consider a 2 x 2 factorial experiment: treatments A and B...

Read more »

Sample size calculations equivalent to Stata functions

June 25, 2013
By

<p>Loading ...</p>

Read more »

Sponsors

Mango solutions



RStudio homepage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training

datasociety

http://www.eoda.de





ODSC

ODSC

CRC R books series





Six Sigma Online Training









Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)