On Oct 28, 2015, at 5:32 PM, frank pampush <[address removed]> wrote:

Hi, Rex,

The stock programming exercise sounds like an interesting challenge!  Count me in.

 

I’m not interested in a book club per se, but as luck would have it, I’m going through APM as we speak.  It’s quite good, IMHO.

 

Best regards,
Frank

 

____________________________________________________________
Francis X. (Frank) Pampush, PhD, CFA | Director | Economics | Navigant
30 S. Wacker Drive | Suite 3100 | Chicago, IL 60606

[masked] Office |[masked] Mobile
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From: [address removed] [mailto:[address removed]] On Behalf Of rex macey
Sent: Wednesday, October 28,[masked]:51 PM
To: [address removed]
Subject: [R-Users-Atlanta] R / Machine Learning / Finance

 

if (you are interested in collaborating on a machine learning / stock picking project using R == T |  # note the or operator
    "you are interested in an R book club meetup"  ==  T) {
            continue reading
} else {
            delete this email
}

I am looking for people interested EITHER in collaborating on a machine learning stock picking project or participating in a book club (I'll do both, but respondents may only be interested in one).  

Book Club
I'll start with the book club.  My thought is to have a handful of people read and discuss a book related to R and machine learning.  I propose the first book be Applied Predictive Modeling by Max Kuhn author of the caret package.  If you are interested, please reply with the area most convenient for you.   

ML Stock Picking Project aka The Stock Market Winners Project

The inspiration for this project is the 1988 article "The Anatomy of a Stock Market Winner" by Marc Reinganum published in the Financial Analysts Journal.  The goal is to improve upon it using machine learning techniques.  Many stock screens have been created based on the idea that stocks with certain characteristics should outperform.  For example, people might screen for stocks with low price-to-book ratios and see how stocks that pass the screen perform.  In contrast Reinganum first identified stocks which had doubled over a 12 month period, and then searched for common characteristics among those.  He identified nine.  The goal is to apply the power to today's computer along with techniques such as random forests to find characteristics of winning (and losing) stocks.

The good news is that I have a survivorship bias free data source that goes back to 2003 with extensive fundamental and technical data on over 8500 companies.   As I've begun the project, I've frequently wished for a collaborator which led to my sending this email.   For example, I am currently trying to decide how to impute missing data. 

By way of background, I recently retired from a 30+year career in finance and have had an interest in R and machine learning.  My programming is limited to college (COBOL / FORTRAN, assembly) and some on-the-job VBA.   I've taken MOOCs on machine learning and R and am comfortable with R.  I went to the R/Finance conference in Chicago the last 2 years.  This is my way of saying that I have far more finance/investing experience than programming ability.  I do not have any commercial / business expectations for this project.  If you're interested in finding out more, just reply.

Rex Macey




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