ETF Aggregation for Buy Sides
Risk Composition
ETF composition risk can be another term used to describe tracking error risk. If two or more ETFs used different methodologies and/or baskets of securities to track an index, they may end up with different performances. Synthetic replication via swaps can perform differently to cash or physical replication via directly holding the underlying securities, in part because swaps can entail additional embedded costs.
Moreover, swaps are often based on derivatives such as futures, which can trade above or below fair value versus the underlying cash. And tracking an index by taking a sample can perform differently from owning every part of the index or fully replicating it. Various combinations and interactions of the above approaches can result in more potential for divergent performance.
Performance calculations
Accurate performance calculation needs to take account of several factors that can lead to errors if they are overlooked. Some ETFs distribute income and others roll it up inside the ETF. For distributing ETFs, the total return performance calculation needs to include some assumption about when the income was reinvested, which can be further complicated by the different tax treatment of income and dividends in different countries.
The same currency share class should also be used to measure performance over time, because currency hedging, errors thereof (or the absence of it) can add to or detract from returns on different currency share classes. The ETF price should be used because the underlying NAV of the ETF may not always track its performance perfectly on the relatively rare occasions when ETFs go to significant premiums or discounts versus NAV.
Peer group analysis
Peer group performance benchmarking needs to define similar ETFs, which is easiest when they share a common benchmark but more difficult for absolute return products targeting a fixed return or spread over cash. How broadly the peer group is defined partly depends on how portfolios are constructed.
For instance, investors taking a top down macro view might group all US equity ETFs in one bucket, while those taking a more bottom up sector approach could split US equity ETFs into their sector focus, such as healthcare, technology, banks and so on. As with performance analysis, peers need to be compared on a like for like basis, allowing for factors such as dividend distribution policy and currency share class.
Our handy brochure provides even more detail and can be downloaded below
Workflow framework for buy- side
A single, flexible, dynamically updated API oils the wheels of buyside operational routines, in contrast to multiple customised files that can be slow to update and leave operational teams and algorithms grappling with a messy jigsaw.
Index Benchmark Module
Index modules are the building blocks of an index. For instance, event modules will include corporate events such as M&A and spinoffs, corporate actions such as dividends, stock splits and rights issues, index rebalances including additions, deletions and re-weightings.
Primary Source ETF data
The primary market for ETFs involves authorised participants (APs) and ETF issuers creating and redeeming ETF shares, in exchange for their constituent baskets of securities: the creation or redemption is in kind rather than in cash. This continuous process provides the foundation for secondary market trading in ETFs.
