Close Price Benchmark
Interest in the closing price is due to the structure of the market. Mutual funds are marked at the end of the day at the closing price. This is the published net asset value (NAV) that indicates that the mutual fund will be marked once a day, and where all the purchases and sales of that mutual fund will be marked at. This is a relic of the market structure of mutual funds. Now, mutual funds are not traded each year or all day long – buys and sells are made at any point during the day and the price is given at the market close. If mutual funds are traded on any given day, the mutual fund trader is going to attempt to get the closing price if at all possible.
Another way in which a trader would try to beat the closing price is via a transition trade. This is when a pension fund moves assets from one manager to another by selling the assets in one manager’s holding in order to buy the assets from another. The pension fund may go to a specialist transitional manager, who takes all the holdings from the current manager, sells them, uses the proceeds to buy the holdings for the new manager, and then passes those holdings back to the new manager. This process has a mark on valuation and the closing price is that mark.
The final type of trade that allows traders to beat the closing price is index rebalancing. Asset managers may opt for a guarantee on their trade. Brokers will bid aggressively for those trades with the same tradeoffs occurring. Index rebalancing trades have an additional nuance in that everyone in the market typically knows whether the street has to buy or sell a stock for the rebalance, so brokers will put out research ahead of the rebalance.
The brokers then have to make a tradeoff, knowing there is potential demand to buy or sell these stocks from many different buyers and sellers. Traders must decide whether to trade early because they know everyone is going to buy the stocks when the index weight goes up, or trade them later (or even the next day), because everyone is going to sell. In the last few years, more and more investors have the requisite information to make the right decision on rebalancing trades.
Implications of Missing the Close Price
The implications of missing the close price benchmark are straightforward. If the trader purchases below the close price, the mutual fund investor buys the fund at a higher price than their investment, which creates transfer of wealth from the new purchaser to the shareholders of the fund. If the mutual fund is not able to beat the close price but requires funds in excess of the new investment, then the existing shareholders subsidize the purchase.
In a transition trade, missing the close price on the funds to sell and the funds to buy creates numerous problems. For transition trades, brokers will very often give an assessment of the expected range of slippage ahead of time, based on the liquidity of the portfolio they are trying to liquidate and the portfolio they are trying to invest in. The broker clearly hopes to land within that range. If they are outside that range however, the transitional manager might refund some of their fee or maybe even negotiate a profit share ahead of time to incentivize them to minimize slippage. Unless the transition manager is able to buy at a discount, missing the close price means a loss to the fund. This slippage can have major implications for the value of assets retained by the client.
The fundamental issue when aiming for the close price is that traders do not know the value of that benchmark until it is too late. If the volume traded going into the close is less than expected, then it is highly likely that any orders to execute with the close price benchmark will have an incrementally higher impact than would otherwise be expected.
One of the factors increasing the likelihood of missing the benchmark is the circuit breakers at exchanges which prevent the close price from moving too much. An order expected to finish at the close will not deviate from the benchmark, but if it triggers a circuit breaker and cannot finish, this introduces overnight price risk. In order to hit the benchmark, traders must be reasonably sure that the expected liquidity will be available. Being able to judge when to start an order is important for beating the close price. Considering all the statistical indicators and overall daily volumes, it may be prudent to begin trading the order before the close to ensure that it completes. This may require deviating further from the close than if you were able to finish the order at the close, but saves the trader from potentially further deviation via overnight risk. Predicting volume leading up to the close allows traders to alter their strategy to minimize slippage.
Volatility can also cause traders to miss the close price benchmark. If a trade is expected to be 5% of the closing print, it is unlikely to move the price and the whole order can be entered. If the order is for a volatile stock and there is reason to believe the closing print will be small, it may be prudent to start trading in advance of the close. The resulting prints will be different than the close because the stock price can move significantly because it is a volatile stock. With low volatility, it can be effective to trade ahead of the close, but for stocks with high volatility that tactic is risky because the stock price tends to move around. Experienced traders segment their trades leading up to the close. They trade in advance where price volatility is low and where volatility is high, trade more of that order into the close (and not be so concerned about pushing the close price).
Experience of Automation
An experienced trader, with all the knowledge and expertise that he or she has built up over time, will generally beat an automated strategy most of the time. The problem is that human traders are not physically able to trade every single stock. A computer applies the same set of rules across everything it sees, and because of the speed of processing power, a computer can read everything. While a human can do the job better, it would require so many humans that it becomes uneconomic.
The question is not whether to use a human or an automated MOC algorithm strategy, it is where to cut off between the human and the computer. For example, if there are 500 orders to do at the close and 480 of those can be dealt with automatically, then more time can be directed to the 20 orders which have a greater impact on portfolio performance. As automation improves, that threshold will change and so traders will be able to take on more trades or perform better on the fewer trades they actively look at.
When a MOC algorithm strategy is employed to beating the close price benchmark, it is important to understand if the system.
- Is able to execute both in the auction and the continuous trading session, and if required, based on the estimated impact of the order size?
- Is smart and intuitive? Does the system analyze historical volume profiling and realtime trading signals (volume traded over the day, predicted auction volume, current spread, current volatility) to create an optimal ratio of volume to trade in the auction and continuous sessions.
- Recognizes urgency levels? The system should allow user to control the level of auction participation and how early to start trading in the continuous session, if required.
Trying to be the axe regardless of the benchmark used, means a trader can provide the same price to everybody and not move the market because the market exists on their desk. Whenever higher closing volume is expected, (whether through a transition trade or a rebalance of an index), brokers will compete to be the axe in the names that matter for that trade. Attracting other traders for that stock allows the broker to provide an equilibrium price without spilling their trading flow into the open market. The sell-side is constantly trying to leverage its ability to trade the close better.
Buy-side traders might also pay for a guarantee to beat the close price and accept a fixed amount of slippage, so transferring the risk from the buy-side to the sell-side. The sell-side takes the risk, the buy-side gets the zero risk trade, and the sell-side then has an opportunity to beat the price that they gave by trading intelligently. This is beneficial for buy-side traders who are risk averse or lack the technology and time to execute such a large trade. If a buy-side trader does not handle this type of trade often or is otherwise occupied elsewhere, they may come to the brokers looking for an agency or a principal trade.
It is generally thought that the sell-side should be marginally better at closing trades than the average buy-side desk, because of the scale that they have in terms of technology. Large closing trades are complex and require tradeoffs, but the technology an experienced broker has can enable a trader to be competitive.
Beating the close price with a MOC algorithm strategy offers significant benefits especially when traders have orders with closing price benchmark and when they want to capture close liquidity while minimizing price impact and next day reversion. It especially works well when the system is sophisticated but remains intuitive.