Question: Way back when, I used to work in finance, and I remember helping a coworker use some kind of block bootstrap. (I believe the application was: we had weekly data on some financial indicator X, along with weekly data on some stock, and we wanted to measure how well X could be used to predict the stock's movements. And I believe we needed to bring in the bootstrap, because we only had a couple months of weekly data, so we didn't really have many datapoints. I might be misremembering all this, though.)

In any case, I totally forget now how the block bootstrap worked, and I want to remember/review/learn more, so can anyone suggest a good tutorial on it? I tried googling, but all I found were some random research papers. I also tried looking in my copy of Efron & Tibshirani's "An Introduction to the Bootstrap Book", but didn't find anything (unless it's under a name other than "block bootstrap").

Answer: 
Try the [Handbook of Computational Statistics, Part III, section 2.4](http://sfb649.wiwi.hu-berlin.de/fedc_homepage/xplore/ebooks/html/csa/node132.html).
For an evaluation of its effectiveness and a comparison to alternative methods, see: 

Bertrand, Marianne, Esther Duflo and Sendhil Mullainathan. 2004. "How Much Should we Trust Difference-in-Difference Estimates?" *Quarterly Journal of Economics*. 119 (1): 249-275. [[pre-publication version](http://economics.mit.edu/files/750)]