Understanding Index Tracking Methodologies

An index fund is a mutual fund designed to track certain components of the financial markets, such as the S&P 500. Index funds are simple investment vehicles that provide broad market exposure with low operating expenses. Because they are passively managed, index funds usually have lower costs compared with more actively managed funds.

Portfolio managers have several ways for ensuring their index funds move in lockstep with the underlying market index they seek to replicate. The main strategies include the following:
 
1. Full replication
2. Stratified sampling and optimization
3. Synthetic replication
 
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Full replication is a process whereby the fund manager buys all the securities that make up an index. The strategy is simple to execute: Hold every security in the index in the same weight as the index.

This is useful for investors who want their index mutual funds to deliver the same return as the index they track. It’s mostly used to replicate the performance of large and liquid markets, such as the S&P 500 or Russell 3000.
 
A full replication strategy is advantageous only when you’re dealing with indexes that can be easily replicated. It provides broad exposure to the largest markets, ensuring better diversification and lower turnover costs. On the flip side, these advantages disappear when dealing with complex or illiquid markets, such as emerging markets. The leading example of a full replication index fund is the SPDR S&P 500 ETF (SPY).
 
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Sometimes, it’s not possible to buy all the components of a leading market index. That’s where stratified sampling or optimization comes in handy.

As the name implies, a stratified sampling strategy invests in a ‘sample’ of holdings from the underlying index. The combination of ‘sampling’ and ‘optimization’ means the portfolio gains exposure to certain segments of the index to provide an acceptable level of risk versus reward. For example. this could mean that you only invest in 75% of securities in the index. A prominent example is the Nationwide S&P 500 Index B (GRMBX), which invests at least 80% of its net assets in S&P 500 companies.
 
Sampling and optimization are beneficial because they provide the most representative sample of the index based on key metrics like exposure, risk, and correlation. But unlike the full replication strategy, sampling and optimization could leave you under-exposed to the index you are trying to track, which could lead to subpar returns.
 
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Synthetic replication is a less popular form of indexing that involves derivatives to track an underlying index. Instead of buying all the securities of an index, synthetic replication entails the use of an investment dealer to swap the performance of the index for a flat fee. For example, if the index increases, the fund receives a payment from the investment dealer based on the value of the gain. If it decreases, the fund pays the investment dealer the value of the decrease. This strategy is more common in ETFs than in mutual funds, but has seen a drop-off since 2010 when the U.S. Securities and Exchange Commission (SEC) prevented the creation of new synthetic ETFs.

The advantage of this approach is that the fund doesn’t incur any purchasing or selling expenses. The downside is that the fee paid to the investment dealer is subtracted from the fund’s overall return. Additionally, synthetic portfolios are inefficient for developed liquid markets like the S&P 500 and are often used when dealing with emerging markets.

There are many ways that mutual funds can track the performance of an index. Full replication, stratified sampling, and synthetic replication are by far the most common. Ultimately, the method selected should reflect the individual’s risk tolerance and overall investment strategy.

 
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