BestEx Research offers a powerful functionality that enables the aggregation of multiple parent orders for the same instrument for both futures and equities trading. This innovation aims to reduce slippage by increasing the efficiency of scheduling, order placement, and liquidity-seeking behavior, particularly for buy-side firms handling large volumes and multiple accounts.

The Problem: Higher Slippage for Multiple Parent Orders on the Same Symbol and Side

Submitting multiple parent orders on the same side for the same stock or futures instrument can lead to unnecessarily increased slippage. For example, a single order for 5% of the daily volume may experience slippage of 15 basis points (bps). However, splitting that order into two separate parent orders of 2.5% each could yield an aggregated market impact of more than 15 bps due to fragmented liquidity and increased market exposure. Associated challenges tend to come from four sources, detailed below. 

1. Suboptimal Limit Order Placement

When multiple parent orders are placed on the same symbol and side, execution algorithms are unaware of the other parent orders. This can result in:

• Overplacement in the order book: Algorithms may inadvertently place excessive child orders, reducing spread capture and increasing temporary market impact.
• Synchronized aggressiveness: Algorithms could act simultaneously when they detect an attractive price, intensifying impact.

2. Increased Trading Speed, Higher Market Impact

For algorithms that target a specific participation rate, multiple parent orders (unaggregated) can unintentionally result in faster trading, exceeding intended participation rates and creating suboptimal outcomes for traders. Consider the following examples, each with the potential to create much more market impact than intended:

• In a POV algo, two orders targeting 5% of volume each left unaggregated may represent a total of 10% of volume–higher participation than intended. In addition, as they see one another’s volume expressed in the market, they could respond by trading more volume of their own–even faster. 
• In an IS algo, two orders targeting medium urgency may trade collectively as if they are trading with high urgency leading to a more front-loaded schedule than what the client desired. If aggregated, the algorithm will consider the combined order size and optimize the aggregate trade plan. 
• Closing auction algos, designed to back-load but not to exceed a certain participation rate, will face similar issues. If not aggregated, the algorithm will participate at a much higher participation rate than intended by the algorithm (more back-loaded) and hence may impact the closing price of the day. If aggregated, the algorithm will consider the combined order size to optimize an aggregate trade plan near the close. 

In all cases, there could be an unnecessary, unintentional increase in the market impact of the collected orders if they are left to trade separately. 

‍3. Missed Liquidity Opportunities in Fragmented Markets 

In fragmented markets, like the US equities market, multiple parent orders can lead to missed opportunities in dark pools:

• Smaller, fragmented orders (e.g., 500 shares per dark pool) may fail to meet minimum quantity requirements to cross against larger counterparties (e.g., 1,000 shares).

4. Fair Price Allocation Across Accounts

Asset managers often face regulatory pressures to demonstrate equal treatment across accounts. Aggregating orders helps ensure that all accounts receive similar execution prices, enhancing transparency and fairness. While OMS platforms support bundling orders from different accounts, they often don't allow aggregation when orders arrive at different times.

BestEx Research is addressing each of these issues with its new order aggregation functionality. 

The Solution

BestEx Research now offers order aggregation functionality that allows the user to inform our algorithms that specific orders must be traded in an aggregated manner. This functionality allows the algorithm to: 

• Place child orders optimally without unnecessary information leakage
• Trade at the optimal speed based on the total size of the order
• Seek block liquidity efficiently and increase fill-rate
• Access as much liquidity as it possibly can

It also allows BestEx Research clients to ensure fair fill allocation across all accounts. In addition, our sell-side customers can offer this customizable functionality to their own clients–a competitive advantage. 

How to Access Aggregation Functionality

By default, BestEx Research algorithms do not aggregate multiple parent orders for the same symbol and side. However, clients can request this feature by contacting their algo execution consultant or coverage personnel.

How It Works

When aggregation is enabled, orders are first routed to an aggregator algorithm. This aggregator evaluates whether new orders can be combined with existing ones based on eligibility criteria (detailed in a later section). If the criteria are met, the new order size is added to the existing parent order. Otherwise, the new order is passed to the intended algorithm.

Example:
A client submits an order to VWAP at 9:30 AM for 100,000 shares, followed by another VWAP order at 11:30 AM for 50,000 shares. If the orders meet the aggregation criteria, the original order is modified to 150,000 shares. 

Fill Allocation After Aggregation

Even when orders are aggregated, fills are still allocated back to the original parent orders proportionally based on the remaining size at the time of aggregation.

Example:

• 10:00 AM: Parent Order 1 (PO1) arrives for 100,000 units.
• 11:00 AM: Parent Order 2 (PO2) arrives for 25,000 units; PO1 has 50,000 shares remaining.
• Proportion is set: 2:1 (50,000:25,000).
• Fill arrives: If a fill of 75 units arrives at $21.50, PO1 gets 50 units, and PO2 gets 25 units.

If a fill cannot be proportionally allocated (e.g., 2 units), the algorithm tracks deviations from proportional allocation and corrects in subsequent fills. See appendix for a detailed explanation with examples. 

Aggregation Eligibility Criteria

For orders to be aggregated, the following criteria must be met:

• Same instrument and side: Orders must be for the same instrument and on the same side of the market to be aggregated.
• Same algorithm and urgency: Orders routed to different algorithms (e.g., VWAP and Close) or to different urgencies cannot be aggregated.
• Same limit price: All aggregated orders must have the same limit price or be market orders.
• Same parameters: Aggregation can be contingent on matching parameters (e.g., end time, participation rate). If not contingent, new orders sent for aggregation will update existing orders. For example, if end time matching is not required, a new order ending at 3pm will update the end time of the aggregated order to 3pm for all component orders. 

Handling Cancellations and Modifications

Cancellation

If a parent order is canceled after aggregation, the aggregator reduces the size of the aggregated order accordingly, and all future fills are directed to the remaining parent orders in appropriate proportion.

Size Modification

If the size of one of the parent orders is modified, the aggregator adjusts the aggregated order and recalculates proportion for subsequent fill allocation.

Parameter Modification

Updating parameters like limit price or end time will trigger a reevaluation. If the modified order no longer meets the aggregation criteria, the aggregator splits the updated order into a new order and reduces the size of the aggregated parent order.

Customization and Flexibility

Clients can modify the eligibility criteria to suit their needs. For example, an additional eligibility criterion could be added based on the time of order receipt to aggregate only those orders arriving within 5 seconds of the original order on the same symbol and side, keeping all other orders separate. In addition, clients can designate specific algorithms for aggregation (e.g., Liquidity_Seek_Aggregate vs. Liquidity_Seek algorithms), allowing flexibility in how different orders are handled.

Post Trade Analysis (TCA)

Aggregated orders will appear as a single order in post-trade TCA reporting from BestEx Research. However, our TCA can provide performance on a stitched or unstitched basis for parent orders regardless of whether the orders are aggregated or not. Readers can learn more about our order stitching functionality here. 

Order Aggregation For Sell-Side Firms

Aggregation functionality is available to both buy-side and sell-side firms. Sell-side firms can enable the aggregation functionality for a subset of their accounts and algorithms. For example, sell-side firms can work with BestEx Research to develop a liquidity-seeking algorithm that aggregates orders only for a subset of their accounts.  

Appendix: Step-by-Step Fill Allocation Process

1) Aggregation Time: When multiple parent orders are aggregated, the remaining quantity of each parent order is calculated and a proportion or ratio between the orders is established.

Example:

• Parent Order 1 (PO1) has 100,000 units.
• Parent Order 2 (PO2) arrives later, with 50,000 units.
• At the time of aggregation, PO1 has already filled 50,000 units, leaving 50,000 units.
• Therefore, the ratio of remaining quantities is 2:1 (50,000:25,000).

2) Proportional Fills: As fills come back from the algorithm, they are distributed proportionally to the parent orders based on this ratio.‍

Example:

• A fill of 75 units comes in at $21.50.
• Since the ratio is 2:1, PO1 receives 50 units, and PO2 receives 25 units, both at $21.50.

3) Handling Small Fills: If the fill quantity is too small to split proportionally (e.g., a fill of 2 units), the system will allocate as closely as possible to the proportion and track any deviation. Future fills will correct this deviation to ensure fairness.

Example:‍

• A fill of 2 units comes in. Since it can't be split perfectly, PO1 gets 1 unit, and PO2 gets 1 unit. This creates a slight under allocation for PO1 (1 unit).
• For the next fill (e.g., 4 units), the system corrects by giving PO1 3 units and PO2 1 unit, restoring the appropriate fill proportions.

4) Real-time Adjustments: The algorithm continuously monitors and adjusts the allocation to maintain proportionality as fills come in. This ensures that all parent orders receive the correct allocation based on their assigned share of the remaining aggregated order.

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Reach out to your BestEx Research representative or info@bestexresearch.com to learn more about how our new order aggregation functionality can help improve your execution.