Posts Tagged ‘ R Language ’

The guts of a statistical factor model

November 12, 2012
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The guts of a statistical factor model

Specifics of statistical factor models and of a particular implementation of them. Previously Posts that are background for this one include: Three things factor models do Factor models of variance in finance The BurStFin R package The quality of variance matrix estimation The problem Someone asked me some questions about the statistical factor model in … Continue reading...

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An easy mistake with returns

November 5, 2012
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An easy mistake with returns

When aggregating over both time and assets, the order of aggregation matters. Task We have the weights for a portfolio and we want to use those and a matrix of returns over time to compute the (long-term) portfolio return. “A tale of two returns” tells us that aggregation over time is easiest to do in … Continue reading...

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Volatility from daily or monthly: garch evidence

October 29, 2012
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Volatility from daily or monthly: garch evidence

Should you use daily or monthly returns to estimate volatility? Does garch explain why volatility estimated with daily data tends to be bigger than if it is estimated with monthly data? Previously There are a number of previous posts — with the variance compression tag — that discuss the phenomenon of volatility estimated with daily … Continue reading...

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The basics of Value at Risk and Expected Shortfall

October 23, 2012
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The basics of Value at Risk and Expected Shortfall

Value at Risk and Expected Shortfall are common risk measures.  Here is a quick explanation. Ingredients The first two ingredients are each a number: The time horizon — how many days do we look ahead? The probability level — how far in the tail are we looking? Ingredient number 3 is a prediction distribution of … Continue reading...

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Review of “R For Dummies”

October 15, 2012
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Review of “R For Dummies”

The authors are Andrie de Vries and Joris Meys. Executive summary Pretty much all I’d hoped for — and I had high hopes. Significance The “Dummies” series is popular for introducing specific topics in an inviting way. R For Dummies is a worthy addition to the pack. There is a competitor by the name of … Continue reading...

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Annotations for “R For Dummies”

October 15, 2012
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Annotations for “R For Dummies”

Here are detailed comments on the book.  Elsewhere there is a review of the book. How to read R For Dummies In order to learn R you need to do something with it.  After you have read a little of the book, find something to do.  Mix reading and doing your project. You cannot win … Continue reading...

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S&P 500 sector strengths

October 10, 2012
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S&P 500 sector strengths

Which sectors are coherent, and which aren’t? Previously The post “S&P 500 correlations up to date” looked at rolling mean correlations among stocks.  In particular it looked at rolling mean correlations of stocks within sectors. Of importance to this post is that the sectors used are taken from Wikipedia. Relative correlations The thought is that … Continue reading...

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Upcoming events

October 9, 2012
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Upcoming events

Featured I’ll be leading two courses in the near future: Value-at-Risk versus Expected Shortfall 2012 October 30-31, London. 30th: “Addressing the critical challenges and issues raised by the Basel proposal to replace VaR with Expected Shortfall” 31st: “Variability in Value-at-Risk and Expected Shortfall” led by Patrick Burns Details at CFP Events. Finance with R Workshop … Continue reading...

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S&P 500 correlations up to date

October 8, 2012
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S&P 500 correlations up to date

I haven’t heard much about correlation lately.  I was curious about what it’s been doing. Data The dataset is daily log returns on 464 large cap US stocks from the start of 2006 to 2012 October 5. The sector data were taken from Wikipedia. The correlation calculated here is the mean correlation of stocks among … Continue reading...

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How to add a benchmark to a variance matrix

October 1, 2012
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How to add a benchmark to a variance matrix

There is a good way and a bad way to add a benchmark to a variance matrix that will be used for optimization and similar operations.  Our examination sheds a little light on the process of variance matrix estimation in this realm. Role of benchmarks Investing Benchmarks are common in investment management.  It’s my opinion … Continue reading...

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