1695 search results for "Time series"

A practical introduction to garch modeling

July 6, 2012
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A practical introduction to garch modeling

We look at volatility clustering, and some aspects of modeling it with a univariate GARCH(1,1) model. Volatility clustering Volatility clustering — the phenomenon of there being periods of relative calm and periods of high volatility — is a seemingly universal attribute of market data.  There is no universally accepted explanation of it. GARCH (Generalized AutoRegressive … Continue reading...

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Health Care Costs – Part 1, "The Problem"

July 5, 2012
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Health Care Costs – Part 1, "The Problem"

The Problem In the United States, health care costs have been going up for a number of years, even when adjusted for inflation. Not unlike a runaway freight train, this rampant inflation cannot continue indefinitely without crashing. ...

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Alternative to Monte Carlo Testing

July 4, 2012
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Alternative to Monte Carlo Testing

When we backtest a strategy on a portfolio, it is a simple analysis of a single period in time. There are ways to “stress test” a strategy such as monte carlo, random portfolios, or shuffling the returns in a random order. I could never really wrap my head around monte carlo and shuffling the returns … Continue reading...

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Glmnet_1.8 uploaded to CRAN

July 4, 2012
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(by Trevor Hastie) Glmnet_1.8 uploaded to CRAN – This is a major revision, with two additional models included. 1) Multiresponse regression – family=”mgaussian” Here we have a matrix of M responses, and we fit a series of linear models in parallel. We use a group-lasso penalty on the set of M coefficients for each variable. This means they are...

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To the Basics: Bayesian Inference on A Binomial Proportion

July 4, 2012
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To the Basics: Bayesian Inference on A Binomial Proportion

Think of something observable – countable – that you care about with only one outcome or another. It could be the votes cast in a two-way election in your town, or the free throw shots the center on your favorite...

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precise pangolin (Ubuntu 12.04)

July 2, 2012
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precise pangolin (Ubuntu 12.04)

Following the crash of my hard drive right before leaving Kyoto, I bought a cheap Compaq Presario CQ57 to reinstall Ubuntu 12.04 over the weekend (and have a laptop available before leaving for Australia…)  It took about one hour to install from the DVD and everything seems to be working out of the box. The

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My first competition at Kaggle

July 2, 2012
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My first competition at Kaggle

For me Kaggle becomes a social network for data scientist, as stackoverflow.com or github.com for programmers. If you are data scientist, machine learner or statistician you better off to have a profile there, otherwise you do not exist. Nevertheless, I won’t bet on rosy future for data scientist as journalists suggest (sexy job for next

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impacTwit : How big is your work on twitter?

June 29, 2012
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impacTwit : How big is your work on twitter?

There’s a great Tom Waits song from the album “Mule Variations” called “Big in Japan”. The beauty of saying you’re big in Japan is that no one can ever really verify the statement (or at least that was more true in 1999). You might assert “my work is big on twitter”, and hey, how would I know?...

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Solving Big Problems with Oracle R Enterprise, Part II

June 27, 2012
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Solving Big Problems with Oracle R Enterprise, Part II

Part II – Solving Big Problems with Oracle R Enterprise In the first post in this series (see https://blogs.oracle.com/R/entry/solving_big_problems_with_oracle), we showed how you can use R to perform historical rate of return calculations against investment data sourced from a spreadsheet.  We demonstrated the calculations against sample data for a small set of accounts.  While this worked...

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Factor Attribution 2

June 26, 2012
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Factor Attribution 2

I want to continue with Factor Attribution theme that I presented in the Factor Attribution post. I have re-organized the code logic into the following 4 functions: factor.rolling.regression – Factor Attribution over given rolling window factor.rolling.regression.detail.plot – detail time-series plot and histogram for each factor factor.rolling.regression.style.plot – historical style plot for selected 2 factors factor.rolling.regression.bt.plot

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