Monthly Archives: April 2012

Volatility Position Sizing to improve Risk Adjusted Performance

April 30, 2012
By
Volatility Position Sizing to improve Risk Adjusted Performance

Today I want to show how to use Volatility Position Sizing to improve strategy’s Risk Adjusted Performance. I will use the Average True Range (ATR) as a measure of Volatility and will increase allocation during low Volatility periods and will decrease allocation during high Volatility periods. Following are two good references that explain these strategy

Read more »

Simple Moving Average Strategy with a Volatility Filter: Follow-Up Part 2

April 30, 2012
By
Simple Moving Average Strategy with a Volatility Filter: Follow-Up Part 2

In the Follow-Up Part 1, I explored some of the functions in the quantstrat package that allowed us to drill down trade by trade to explain the difference in performance of the two strategies. By doing this, I found that my choice of a volatility measure may not have been the best choice. Although the … Continue reading...

Read more »

Information Age: graduates driving industry adoption of R

April 30, 2012
By

Information Age recently published a feature article devoted to the R language, "Putting the R in analytics". Says author Pete Swabey: Already popular in universities, there are signs that R is finding increasing adoption in the enterprise. This promises to lower the barriers of entry for advanced analytics, and may accelerate the mathemitisation of business management. The article includes...

Read more »

French Global Factors

April 30, 2012
By
French Global Factors

I have said it already in multiple posts, but Kenneth French’s data library is one of the most generous and powerful contributions to the financial community.  To build on Systematic Investor’s series on factors, I thought I should run some ba...

Read more »

Bayesian ANOVA for sensory panel profiling data

April 30, 2012
By
Bayesian ANOVA for sensory panel profiling data

In this post it is examined if it is possible to use Bayesian methods and specifically JAGS to analyze sensory profiling data. The aim is not to obtain different results, but rather to confirm that the results are fairly similar. The data used is the c...

Read more »

Example 9.29: the perils of for loops

April 30, 2012
By
Example 9.29: the perils of for loops

A recent exchange on the R-sig-teaching list featured a discussion of how best to teach new students R. The initial post included an exercise to write a function, that given a n, will draw n rows of a triangle made up of "*", noting that for a beginner, this may require two for loops. For example,...

Read more »

Teaching code, production code, benchmarks and new languages

April 30, 2012
By
Teaching code, production code, benchmarks and new languages

I’m a bit obsessive with words. May be I should have used learning in the title, rather than teaching code. Or perhaps remembering code. You know? Code where one actually has very clear idea of what is going on; for … Continue reading →

Read more »

Cross-sectional skewness and kurtosis: stocks and portfolios

April 30, 2012
By
Cross-sectional skewness and kurtosis: stocks and portfolios

Not quite expected behavior of skewness and kurtosis. The question In each time period the returns of a universe of stocks will have some distribution — distributions as displayed in “Replacing market indices” and Figure 1. Figure 1: A cross-sectional distribution of simple returns of stocks. In particular they will have values for skewness and … Continue reading...

Read more »

Incompetence borne of excessive cleverness

April 29, 2012
By

I have just got back from the 24 hour Data Science Global Hackathon; I was an on-site participant at Hub Westminster in London (thanks to Carlos and his team for doing such a great job looking after us all {around 50 turned up from the 100 who registered; the percentage was similar in other cities

Read more »

The Need for paste2 (part II)

April 29, 2012
By
The Need for paste2 (part II)

This is Part II of a multi part blog on the paste2 function… In my first post on the paste2 function I promised a proof of a few practical uses.  The first example I have comes from psychometrics and comes out of … Continue reading →

Read more »