Monthly Archives: December 2011

R-specific review of blog year 2011

Most popular posts Two of the ten most popular posts during the year were completely about R: The R Inferno revised (number 6) Solve your R problems (number 9) R played a role in the other eight top ten, and many of the rest of the posts as well. R The R Inferno was revised … Continue reading

Posted in R language | Tagged | Leave a comment

Blog year 2011 in review

Highlights of the blog over the past year. See also “Blog year 2010 in review”. Most popular posts The posts with the most hits during the year. 4 and a half myths about beta in finance A tale of two returns (posted in 2010) The number 1 novice quant mistake What the hell is a … Continue reading

Posted in Blog | Tagged , , | 4 Comments

Three talks from CFE

The Computational and Financial Econometrics conference was just held in London.  Here are three talks from the large menu. Lars Helge Hass The objective is to find a way to do an asset allocation optimization that includes private equity.  A problem of course is that private equity is seriously opaque.  To highlight that, using one … Continue reading

Posted in Quant finance | Tagged , , | Leave a comment

Portfolio optimization inside out

A possible way to search for constraints that improve optimization. The perspective The usual way of thinking about portfolio optimization is to first consider the utility and then restrict to where the constraints are satisfied.  A perfectly reasonable view. We use random portfolios to get a different point of view: first ensure that the constraints … Continue reading

Posted in optimization, Quant finance, Random portfolios | Tagged , , | Leave a comment

There’s news and there’s news

Two recent posts included the word “news”, but in different senses. Events “News” in the sense of reports on events was discussed in “News analytics”.  We can think of this as an approximation to objective reality. Market moves The post “Volatility estimation and time-adjusted returns” used “news” in the sense of “that which moves market … Continue reading

Posted in Quant finance | Tagged , | Leave a comment

Volatility estimation and time-adjusted returns

Do non-trading days explain the mystery of volatility estimation? Previously The post “The volatility mystery continues” showed that volatility estimated with daily data tends to be larger (in recent years) than when estimated with lower frequency returns. Time adjusting One of the comments — from Joseph Wilson — was that there is a problem with … Continue reading

Posted in Quant finance, R language | Tagged , , , | Leave a comment

Searching for inspiration on financial risk

Two people, two sources. Planes Deus ex Macchiato has a post called “Planes not bridges” in which it is suggested that learning from air traffic investigators makes sense.  The logic is that a large component of plane accidents is caused by human (mis)beliefs.  So perhaps finance can imitate air safety in reducing the frequency of … Continue reading

Posted in Risk | Leave a comment

News analytics

Last week was the news analytics workshop at Birkbeck College. The idea There is room in news analytics for a large range of approaches.  The leading model runs along the lines of: something happens a journalist (possibly a machine) creates a news item the news item is captured, time-stamped and given an id the news … Continue reading

Posted in Quant finance | Tagged | 4 Comments

LondonR recap

The biggest and perhaps best meeting yet. The talks James Long: “Easy Parallel Stochastic Simulations using Amazon’s EC2 & Segue”.  This was a lively talk about James’ package to use Amazon’s cloud to speed up a (huge) call to lapply.  The good part is that if you want to use Amazon as your cloud provider, … Continue reading

Posted in R language | Leave a comment

The volatility mystery continues

How do volatility estimates based on monthly versus daily returns differ? Previously The post “The mystery of volatility estimates from daily versus monthly returns” and its offspring “Another look at autocorrelation in the S&P 500” discussed what appears to be an anomaly in the estimation of volatility from daily versus monthly data. In recent times … Continue reading

Posted in Quant finance, R language | Tagged , , , | 11 Comments