In just about every action movie and TV show these days there is at least one scene where the hero asks one of his or her techies to “sharpen” a satellite image.  Suddenly, what looked like a fuzzy bunch of pixelated squares takes on the form of someone’s face, a car, or some kind of mobile rocket launcher.   We’re not graphic imaging specialists.  But to us, it looks kind of outlandish that someone could take a very small amount of information (a few pixels) and divine the underlying image in fantastic detail.

But in a way, that’s exactly what Daniel Li & Michael Markov (of quantitative investment software vendor Markov Processes) and Russ Wermers of the University of Maryland have done in a paper released last month called “Monitoring Daily Hedge Fund Performance When Only Monthly Data is Available.”  Their trick is to leverage another kind of technology: hedge fund replication.

As we have reported extensively, “linear factor replication” aims to predict the performance of hedge funds based on a multiple regression of their historical returns on a number of variables such as equities, Fama/French factors, and several more “exotic” risk factors. More…