Monthly Archives: October 2012

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

Posted in Quant finance, R language | Tagged , , | 6 Comments

US market portrait 2012 week 44

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

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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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Introduction to “Tao Te Programming”

The author is Patrick Burns. Genesis While I was in the early planning stages of a programming class (the one highlighted here), I became dissatisfied. Many elements of programming — especially good programming — are not usually discussed in programming classes.  The typical class focuses on how to slot the screwdriver into the screw and … Continue reading

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US market portrait 2012 week 43

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

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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”

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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US market portrait 2012 week 42

US large cap market returns. Fine print The data are from Yahoo Almost all of the S&P 500 stocks are used The initial post was “Replacing market indices” The R code is in marketportrait_funs.R

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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

Posted in Quant finance, R language | Tagged , , | 5 Comments

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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