Monday Mailbag: We Have Liftoff

09/15/14 | Karyl Patredis

Wait, you mean you have indices beyond the AMZ?

Yes indeed. While the Alerian MLP Index (AMZ) is our flagship index and the leading gauge of large- and mid-cap energy MLPs, we have other indices. The Alerian MLP Equal Weight Index (AMZE) is an equally weighted version of the AMZ. The Alerian MLP Infrastructure Index (AMZI) tracks 25 energy infrastructure MLPs. The Alerian Natural Gas MLP Index (ANGI) tracks 20 natural gas MLPs. The Alerian Large Cap MLP index (ALCI) tracks the 15 largest energy MLPs. And finally, our newest index, the Alerian Energy Infrastructure Index (AMEI), tracks 30 MLPs and corporations in North America that engage in the transportation, storage, and processing of energy commodities.

If you launched the AMZ in 2006, how do you have data going back to 1995?

In preparation for the release of an index, we not only use the methodology guide to determine current index constituents, but we also backtest the index in order to give stakeholders historical data for benchmarking and informational purposes. Notably, all Alerian indices are backtested, and not backfilled.

What is the difference between an index that is backtested versus one that is backfilled?

An index that is backfilled simply takes the index constituents at the time of launch and rebalances historically using only those constituents. Companies that were previously in existence but have since been acquired, merged, or delisted are excluded. This can lead to a heightened degree of survivorship bias in an index.

An index that is backtested takes the methodology guide in place at the time of launch and uses it to rebalance at every period preceding the launch. No events that chronologically occur after the rebalancing are used to inform the process. This means that companies that have been acquired, merged, or delisted are included. It also means that companies that are currently disqualified from the indices (due to distribution cuts, bankruptcy, etc.) would still be eligible for index inclusion before those events occurred. In short, we believe backtesting paints a more historically accurate and unbiased picture of the MLP space.

You didn’t ask, but there is also a historical index calculation method called backcasting. As the name implies, it’s similar to forecasting, but goes backwards. With forecasting, you’re trying to predict what will happen in the future using information available today. With backcasting, you’re armed with the knowledge of what has already occurred, and the goal is to use that knowledge to simulate a path that would create the most optimal outcome. In relation to indexing, a backcasted index typically selects the constituents that have the best historical performance and then builds a methodology around those names. While a backcasted index may have excellent historical performance prior to its real-time launch, it is also the least accurate in terms of historical representation.

Where can I find information about the methodology Alerian uses?

Our methodology guides are always available for download on the indices page of our website.