In my prior post, describing the August, 2009, performance of the Dynamic Trading Risk Factor, I alluded to the fact that the source data, the Barclay Hedge hedge fund indices, does not accrue atomically — in fact it is gradually updated during the course of each month.

In prior posts, I pointed out that the final month's factor return is mostly little changed from that computed from earlier, incomplete, data. As it should be, if the Law of Large Numbers is working it's usual magic. However, nature is often a little more subtle than that, and mankind often deliberately so. It therefore falls to us to ask whether there is any bias between the latency of a given fund's publication of its performance numbers and that same fund's performance relative to the mean of all reporting funds? Our strong prior is that human frailty would lead the bearers of good news to rush it out as soon as possible; and, in contrast, the bearers of bad news to wait a little longer than they should before revealing their shame.

The above chart illustrates my attempt to quantify this effect on the September, 2009, data, which represents the aggregated reported August, 2009, returns of around 2,500 funds as reported during the month. Not possessing an inside track at the data vendor, I had to resort to archiving and timestamping sampled copies of the cumulatively reported data. Thus, it was tedious to collect. Exhibited above is the mean relationship between the relative error in the Hedge Fund Index's reported average return and the relative proportion of the total number of funds that had reported at that time. (In both cases, relative means relative to the final sample value I have for that month's datum.) From this sample there does appear to be a very strong negative correlation, confirming our cynical prior from the earlier paragraph. Unfortunately, the serial correlation of the errors complicates a statistical analysis of the goodness of fit — but by eye it appears excellent.