Monthly Archives: January 2013

Reserving based on log-incremental payments in R, part I

January 8, 2013
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A recent post on the PirateGrunt blog on claims reserving inspired me to look into the paper Regression models based on log-incremental payments by Stavros Christofides , published as part of the Claims Reserving Manual (Version 2) of the Institute of Actuaries.The paper is available together with a spread sheet model, illustrating the calculations. It...

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The myth of the missing Data Scientist

January 7, 2013
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The myth of the missing Data Scientist

Much has been said about the dire shortage of Data Scientists looming on the horizon. With the spectre of Big …Continue reading »

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Does anything NOT beat the GARCH(1,1)?

January 7, 2013
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Does anything NOT beat the GARCH(1,1)?

In their paper on GARCH model comparison, Hansen and Lunde (2005) present evidence that among 330 different models, and using daily data on the DM/$ rate and IBM stock returns, no model does significantly better at predicting volatility (based on a realized measure) than the GARCH(1,1) model, for an out of sample period of about

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Does anything NOT beat the GARCH(1,1)?

January 7, 2013
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Does anything NOT beat the GARCH(1,1)?

In their paper on GARCH model comparison, Hansen and Lunde (2005) present evidence that among 330 different models, and using daily data on the DM/$ rate and IBM stock returns, no model does significantly better at predicting volatility (based on a realized measure) than the GARCH(1,1) model, for an out of sample period of about

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Creating a Covariance Matrix from Scratch

January 7, 2013
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I have been conducting several simulations that use a covariance matrix.  I needed to expand the code that I found in the psych package to have more than 2 latent variables (the code probably allows it but I didn’t figure it out).  I ran across Joreskog’s 1971 paper and realized that I could use the confirmatory factor analysis...

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Creating a Covariance Matrix from Scratch

January 7, 2013
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I have been conducting several simulations that use a covariance matrix.  I needed to expand the code that I found in the psych package to have more than 2 latent variables (the code probably allows it but I didn’t figure it out).  I ran across Joreskog’s 1971 paper and realized that I could use the confirmatory factor analysis...

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Speed trick: unlist(…, use.names=FALSE) is heaps faster!

January 7, 2013
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Sometimes a minor change to your R code can make a big difference in processing time. Here is an example showing that if you're don't care about the names attribute when unlist():ing a list, specifying argument use.names=FALSE can speed up the process...

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Setting up emacs org-mode babel for R on Ubuntu

January 7, 2013
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Setting up emacs org-mode babel for R on Ubuntu

I installed org-mode seperately, since I had troubles with its default setting (similar to the problems described here). sudo apt-get install org-mode Next I download and installed ESS cd ~/.emacs.d/ wget http://ess.r-project.org/downloads/ess/ess-12.09-1.zip unzip ess-12.09-1.zip rm ess-12.09-1.zip Finally I had to … Continue reading →

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R/Finance 2013: May 17-18 in Chicago

January 7, 2013
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This year's R/Finance conference on applied finance with R is scheduled for May 17-18 in Chicago, and promises once again to be the go-to conference for anyone using R in the finance industry. The keynote speakers have been announced, and it's a great lineup: Sanjiv Das, Professor of Finance and Chair of Finance Dept, Santa Clara University’s Leavey School...

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Breaking the rules with spatial correlation

January 7, 2013
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Breaking the rules with spatial correlation

Students in any basic statistics class are taught linear regression, which is one of the simplest forms of a statistical model. The basic idea is that a ‘response’ variable can be mathematically related to one or any number of ‘explanatory’ variables through a linear equation and a normally distributed error term. With any statistical tool,

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