Blog Archives

BurStFin R package version 1.02 released

March 16, 2014
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BurStFin R package version 1.02 released

More efficiency and an additional function in the new version on CRAN. Variance estimation The major functionality in the package is variance estimation: Ledoit-Wolf shrinkage via var.shrink.eqcor statistical factor model (principal components) via factor.model.stat There have been a number of previous blog posts on both factor models and Ledoit-Wolf shrinkage. Positive-definiteness The default value of … Continue reading →

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A complicated answer to a simple correlation question

February 9, 2014
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A complicated answer to a simple correlation question

A data analysis surprise party. Simple question If I have correlation matrices each estimated with a month of daily returns, how much worse is the average of six of those compared to the estimate with six months of daily data? Expected answer Do a statistical bootstrap with the returns and compare the standard deviations across … Continue reading →

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What is volatility?

January 19, 2014
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What is volatility?

Some facts and some speculation. Definition Volatility is the annualized standard deviation of returns — it is often expressed in percent. A volatility of 20 means that there is about a one-third probability that an asset’s price a year from now will have fallen or risen by more than 20% from its present value. In … Continue reading →

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garch models caught in the spotlight

January 13, 2014
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An attempt to clarify the basics. Previously There have been several posts about garch.  In particular: A practical introduction to garch modeling The components garch model in the rugarch package Genesis A reader emailed me because he was confused about the workings of garch in general, and simulation with the empirical distribution in particular. If … Continue reading →

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S&P that might have been

January 6, 2014
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S&P that might have been

The S&P 500 returned 29.6% in 2013.  How might that have varied? S&P weights There are many features that could vary — here we will keep the same constituents (almost) and weights with similar sizes but that are randomly assigned rather than based on market capitalization. That is, we want the large weights of our … Continue reading →

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Blog year 2013 in review

December 30, 2013
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Blog year 2013 in review

Highlights of the blog over the past year. Most popular posts The posts with the most hits during the year. A practical introduction to garch modeling (posted in 2012) A tale of two returns (posted in 2010) The top 7 portfolio optimization problems (posted in 2012) The number 1 novice quant mistake (posted in 2011) On smart beta … Continue reading →

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Further adventures with higher moments

December 23, 2013
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Further adventures with higher moments

Additional views of the stability of skewness and kurtosis of equity portfolios. Previously A post called “Four moments of portfolios” introduced the idea of looking at the stability of the mean, variance, skewness and kurtosis of portfolios through time. That post gave birth to a presentation at the London Quant Group. That talk gave birth … Continue reading →

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Historical Value at Risk versus historical Expected Shortfall

November 18, 2013
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Historical Value at Risk versus historical Expected Shortfall

Comparing the behavior of the two on the S&P 500. Previously There have been a few posts about Value at Risk (VaR) and Expected Shortfall (ES) including an introduction to Value at Risk and Expected Shortfall. Data and model The underlying data are daily returns for the S&P 500 from 1950 to the present. The VaR and … Continue reading →

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Quant finance blogs

October 22, 2013
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What I’ve learned from updating the blogroll. New entries The easy option is to go to The Whole Street which aggregates lots of quant finance blogs. Somehow Bookstaber missed out being on the blogroll before — definitely an oversight. Timely Portfolio was another that I was surprised wasn’t already there. The R Trader talks about … Continue reading →

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Four moments of portfolios

October 14, 2013
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Four moments of portfolios

What good are the skewness and kurtosis of portfolios? Previously The post “Cross-sectional skewness and kurtosis: stocks and portfolios” looked at skewness and kurtosis in portfolios.  The key difference between that post and this one is what distribution is being looked at. The previous post specified a single time and looked at the distribution across … Continue reading →

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