Recent Links for 09/21/2007

Newbie - converting csv files to arrays in NumPy Great message thread on how to convert csv files to numpy arrays.

Cookbook/InputOutput - Numpy and Scipy File processing examples using numpy, scipy, and matplotlib. How to read/write a numpy array from/to ascii/binary files.

Numpy Example List Examples of Numpy functions such as fromfile(), hsplit(), recarray(), shuffle(), sort(), split(), sqrt(), std(), tofile(), unique(), var(), vsplit(), where(), zeros(), empty(), and many more.

Introducing Plists: An Erlang module for doing list operations in parallel Could you spawn a trading system process for each stock of a given day's trading (a list)? What if you had 20,000 stocks for a given day? Can plists/erlang handle 20,000 processes without hitting memory constraints?

Recent Links for 09/19/2007

130/30 Strategy Backtested Disagree with comparison of 130/30 to non-leveraged benchmark/strategy. Also, the additional longs didn't improve the long portion of the 130/30 returns compared to the long-only strategy returns. Am I missing something?

Recent Links for 09/18/2007

Chapter 22. Struct and Array Modules Overview of the python struct and array modules

Building Skills in Programming Nice python tutorial.

Python Grimoire Nice python cookbook.

Recent Links for 09/17/2007

• One year ago I was a stock market analyst [Part 1]
  Very interesting how he was able to process 9,000 stocks in less than a minute.


• Goldblog - Python - Stock Quote Module
  Interesting python stock quote utility.


• Goldblog - Investment Advice
  Excellent investment advice. Keep it simple.


• NumPy for Numeric/numarray users
  Cheatsheet for NumPy Python users

Recent Links 09/17/2007

Goldblog - Investment Advice

• Excellent investment advice.  Keep it simple...
  
  • 
    There are 2 simple questions you must first answer:
    
    1. What is the time-frame in which you need access to your money? (next week? next year? 10 years? retirement?)
    
    2. How much risk and volatility are you comfortable with?
    
  • 
    The Answer:
    Asset Allocation... not fundamental analysis, not technical analysis, not market
    trending, not tips from brokers and analysts ... but straight up asset
    allocation.
    
    
  
  
  
  
  
  
  
  
   - post by taylortree

Recent Links for 09/15/2007

Links for 2007-09-15 [del.icio.us]

Posted: 16 Sep 2007 12:00 AM CDT

• Practical Common Lisp
  Excellent way to get started with Common Lisp.


• 9 Things You Simply Must Do
  Friend of mine sent me this great post on Dr. Cloud's 9 principles commonly practiced by successful people. My favorites?
  

Principle #2: Pull the Tooth - face your fears...don't put off today what you can do today.


Principle #4: Do Something

• ONLamp.com -- An Introduction to Erlang
  Great coverage of the Erlang language.


• Python Cheat Sheet
  Simple little python cheat sheet.

Recent Links 09/15/2007

Practical Common Lisp

• Great coverage on Common Lisp.
   - post by taylortree

Recent Links 09/06/2007

Quantmod - Quantitative Financial Modelling Framework for R

• Offers R language modules to...
  
  • calculate periodic returns
  • retrieve historic quotes from Yahoo, Google, FRED
  • there's even a tradeModel that looks interesting
  • and well documented.
    
  
  
  - post by taylortree

Recent Links 09/05/2007

Speed up R, Python, and MATLAB - Going Parallel

• Reduce runtime of Python, R, and MATLAB applications by 85%?  Process 10-100X  larger datasets?  With just a few code changes?  Not quite sure how...but something to explore in the future.  Their success story on speeding up MATLAB code for Monte Carlo Analysis looks pretty easy of a code change to me.  Read their blog for further insights into HPC...
  
  • Multicore:  Why all the Hubbub?
  • What is "Productivity" in High Performance Computing?
  
  
   - post by taylortree

Recent Links 09/04/2007

World Beta - Engineering Targeted Returns and Risk: More On The Endowment Style Of Investing  Annotated

• World Beta shares some links covering the endowment investing side of things...
  
  • A link to
    Frontier Capital Management
    - check out their knowledge section for more great papers similar to the ones Faber links to.
  • Faber mentions a great upcoming book covering the twelve top endowment CIO's .
  • from Alpha Magazine...Highbridge Capital Managment shares its office organization - putting traders and developers together.  I've always thought this would be a great idea in any shop.  By putting users and developers together - manual taks can be seen and automation can happen.
    
  
  
   - post by taylortree

Frontier Capital Management

SourceForge.net: tkdiff

• Great little file compare utility.  Graphic front end to the diff program.
  note:  tested this today against a large file/program (well, not that large in my line of work...but I guess to Google's)...couldn't handle it.  But, works great on small files.
   - post by taylortree

Google Mondrian: web-based code review and storage

• Online code review that works like a blog/wiki.  I wonder...is it possible to create a code review system similar to Mondrian within a source management toolset such as subversion?  Seems like most of the backend is there already...would only need to add some front end tools to display the changes being committed and allow comments on those changes.
   - post by taylortree

Recent Links 09/03/2007

ONLamp.com -- Numerical Python Basics

• Numpy basics.
   - post by taylortree

Programming in R

Finding Duplicate Elements in an Array :: Phil! Gregory  Annotated

• Interesting way to find duplicates in an array.  Enjoyed the links on the pigeonhold principle and Floyd's cycle-finding algorithm.
   - post by taylortree

Now, suppose that the array is of length n and only contains positive
integers less than n. We can be sure (by the pigeonhole principle)
that there is at least one duplicate.

So, how do we find the beginning of the cycle? The easiest approach is to
use Floyd's cycle-finding algorithm. It works roughly like this:
Start at the beginning of the sequence. Keep track of two values (call
them a_i and a_j). At
each step of the algorithm, move a_i one step
along the sequence, but move a_j two steps. Stop
when a_i = a_j.