Hidden Costs In Index Tracking by Christophe Bernard, PhD, Senior Scientist, Winton Capital Management
Buying an index tracker is seen as a cheap and easy way to get exposure to stock markets. The last decade has seen a growth in the amount of money passively tracking market capitalization weighted indexes.
This trend has been driven by evidence of traditional active fund managers underperforming passive benchmarks. This added validity to the argument of market efficiency; the Capital Asset Pricing Model dictates that a market capitalization portfolio represents an “optimal” that you should not expect to beat. Furthermore such a portfolio requires almost no turnover.
In this study we look at the S&P 500 which is the most prominent market capitalization weighted index in the world. It is very hard to know just how much money is passively tracking the S&P 500, but it has been estimated  at more than 10% of the total capitalization.
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Buying a tracker on the S&P 500 is therefore akin to buying a share of a huge managed equity portfolio. The size of which is at least $1.5 TN. Collectively the managers of such funds can be attempting to buy or sell 10% of an entire company within the space of 1 or 2 days. In addition, their intention is publicly known often a week in advance. This opens up the possibility of other market participants profiting at their expense. All this has a cost to index tracking investors which is not reflected in the tracking error. We estimate this to be at least 20 basis points per year, which could be saved by an active manager following a less crowded strategy even at a much higher turnover.
Hidden Costs In Index Tracking – Introduction
Standard and Poor’s (S&P) define computation rules for their index which amount to calculating the profit and loss (P&L) of a trading system, where the manager of an equity fund is following the S&P’s guidelines for changing the composition of the portfolio and the reinvestment of cash proceeds. Further to this effect, since October 1989, S&P announce changes in the composition of their index early enough to allow index fund managers to buy (or sell) stocks added to (or removed from) the index in a timely fashion. This is true for all S&P indices, as well the majority of indices provided by the other index providers such as MSCI or Nikkei.
In this paper, we focus on the most prominent stock index: the S&P 500, and analyze its turnover. For equity fund managers turnover is associated with costs, and costs can be split into two components. The first is commissions that have to be paid for brokerage services and the second is market impact, often referred to as ‘slippage’. Buying large blocks of shares in a single company normally causes the price of the shares to increase, forcing one to purchase them at a premium.
In this paper we analyse the costs involved when tracking the S&P500 index. In section 1, we detail the data we use for this analysis, and how it was collected. In section 2, we analyse the turnover of the S&P index since 1989, and give a rough estimate of the amount of commissions that have to be paid for this turnover. In section 3, we estimate the price impact that such a large amount of turnover will induce, focusing on a subset of events: additions to and deletions from the index. We conclude with a discussion in section 4.
Most of the stock level data (and especially index membership information) is provided by S&P, together with various amounts of index level data (market capitalisation, price and total return index values). We checked the data against other providers, and apart from very minor or temporary glitches in earlier years, the data is very consistent and of good quality.
It is worth noting that S&P have conventions about the definition of price and dividend returns that might be misleading at first glance. For instance, S&P’s methodology is to incorporate large special dividends (such as the one paid by Microsoft in 2004) in the price return and not in the dividend return.
In order to assess price impact, we needed historical prices for individual stocks outside of their lifespan within the S&P 500 index, which S&P do not provide. For that, we used data provided by the Centre for Research in Security Prices (CRSP). Finally, we collected data on S&P announcements.
Whenever possible, since 1989 S&P have announced changes to index constituents 5 days in advance, but in practice this can vary substantially. In order to accurately compute the past performance of an arbitrage strategy it is important to have accurate announcement dates. S&P provided us with data they had collated for earlier academic studies, and for the remaining announcements we collected the original press-releases from various sources (S&P archives, S&P online site, internet news archives), using a combination of automated and manual searches.
On most days, a manager replicating the S&P 500 price index need do no transactions. The index is market capitalization weighted, so variations in price of the stocks do not make any rebalancing necessary. Replicating the total return index creates a little extra turnover when the dividends have to be reinvested.
However, some changes to the index do necessitate rebalancing by the manager. The most important case is when S&P decide to modify the constituent list of their index. The manager then has to sell the stocks removed from the index, and buy the newly added ones. Further, since the market capitalisation of the added and deleted companies rarely matches exactly, some rebalancing of all remaining stocks must take place – buying or selling an identical fraction.
Another case is when a company is issuing new shares, or buying back those in issue. The manager then has to buy or sell stocks to adjust the weight of that company, and then also rebalance the weights of all other stocks accordingly.
A final (relatively minor) case is when S&P changes the fraction of what they consider to be the freely floating shares of a company. This changes the weight of the company in the index and is also a source of turnover for the manager.
The following table gives an estimate of the resulting turnover caused by the various types of changes listed above.
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