Monday, May 12, 2014

backfill bias and survivorship bias, briefly

based on http://oyc.yale.edu/sites/default/files/midterm_exam1_solutions.pdf --

A hedge fund index has a daily NAV value based on the weighted average NAV of constituent funds. If today we discover some data error in the 1999 NAV, we the index provider are allowed to correct that historical data. Immediately, many performance stats would be affected and needs update. Such data error is rare (I just made it up for illustration.) This procedure happens only in special scenarios like the 2 scenarios below.

Survivorship bias: When a fund is dropped from an index, past values of the index is adjusted to remove that fund's past data.

Backfill bias: For example, if a new fund has been in business for two years at the time it is added to the index, past index values are adjusted for those two years. Suppose the index return over the last 2 years was 33%, based on weighted average of 200 funds. Now this new fund is likely more successful than average. Suppose its 2Y return is 220%. Even though this new fund has a small weight in the index, including it would undoubtedly boost the 2Y index return – a welcome "adjustment".

While backfilling is obviously a questionable practice, it is also quite understandable. When an index provider first launches an index, they have an understandable desire to go back and construct the index for the preceding few years. If you look at time series of hedge fund index performance data, you will often note that indexes have very strong performance in the first few years, and this may be due to backfilling.

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