Anyone who collects academic texts knows that the hobby can be a bit expensive. Well, today I happened to notice that there is an incredible deal on Amazon's Gold Box Deal for today for many kindle academic books. And they are not just unpo...

Anyone who collects academic texts knows that the hobby can be a bit expensive. Well, today I happened to notice that there is an incredible deal on Amazon's Gold Box Deal for today for many kindle academic books. And they are not just unpo...

As mentioned in the Appendix of Modern Actuarial Risk Theory, “R (and S) is the ‘lingua franca’ of data analysis and statistical computing, used in academia, climate research, computer science, bioinformatics, pharmaceutical industry, customer analytics, data mining, finance and by some insurers. Apart from being stable, fast, always up-to-date and very versatile, the chief advantage of R is that...

The go-to bible for this data scientist and many others is The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Each of the authors is an expert in machine learning / prediction, and in some cases invented the techniques we turn to today to make sense of big data: ensemble...

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

Calibrations of 2013 predictions for 18 equity indices — plus some publicly available predictions. Orientation The distributions are an attempt to see the variability if there were no market-driving news for the whole year. Another way of thinking: mentally moving the distribution to center on a prediction gives a sense of the variability of results … Continue reading...

Coursera is offering free courses about R among other interesting subjects. The first one on the application of R in financial econometrics is happening this week (but you can still enroll). There are two more courses starting in January 2013 are more about using R to analyse the data. The differences between the two are

Mike Bostock has revolutionized visualization with his d3 and his seemingly infinite examples. In another adaptation of his amazing work, I will adapt one of my favorite examples to supplement the interactive scatterplot with data supplied by R t...

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