Making a Splash: How Hedge Funds are Using Technology to Minimize the Impact of Large-Scale Orders

While AUM and returns remain the most valuable metrics to judge the relative strength of hedge funds today, investment in technology could soon stake a place to become a primary consideration among clients. 

Hedge funds, in particular, have started to seek out more technologically advanced processes to improve operational efficiency in managing the market impact surrounding their orders. 

According to a recent Broadridge study, 58% of hedge funds claim that digital transformation is their most important strategic initiative. In addition to this, hedge funds intend to bolster their investments in cloud platforms and applications by 26%. 

While much of this added emphasis on digital transformation will focus on factors such as data analytics and cybersecurity, we can also expect to see institutions directly address the challenges posed by large-scale ordering, which has become a game of cat and mouse in recent years. 

Managing Market Impact 

The market impact of hedge funds has become a major consideration for investors of all sizes. Because large-scale orders carry significant ramifications for securities and the industries that they’re linked to, tracking the execution of these orders could help shape the strategies of other traders. 

Major purchases can carry lasting impacts on specific markets that can artificially rally and contract based on hedge fund interest. 

This noise has caused many hedge funds to seek out a series of intelligent measures to mitigate their market impact.

One solution that’s gathered momentum in recent years is the use of dark pools, which are private exchanges that hedge funds can use to place orders for their clients without impacting the wider market when these large block orders are placed. Additionally, the private nature of these dark pools means that hedge funds don’t have to justify their trades to buyers or sellers. 

Modern brokers can also empower investors to place hidden orders to hide the submitted quantity from the wider market. This helps to maintain a level of anonymity surrounding orders, which can pave the way for more stability when looking to protect the wider market impact following a significant order volume. 

One of the most popular ways for hedge funds to execute large-scale orders is through iceberg ordering. This refers to an order holding far greater volume under the surface than what meets the eye. 

Otherwise known as reserve orders, an iceberg order is typically used by hedge funds to break a significant order into a series of smaller trades. 

These smaller orders generally have no attributes that would link them to a single larger order, making their full magnitude impossible to deduce for other traders. 

Technology to Avoid ‘Making a Splash’

Hedge funds are popularly compared to whales when it comes to making market movements. This is because their order sizes can resemble making a splash, in terms of its wider impact on securities and their respective sectors. 

It’s for this reason that these ‘whales’ are adopting new technologies to better hide their splashes. 

With this in mind, it’s unsurprising that hedge funds like Man Group have turned to machine learning (ML) as a means of predicting how investors will react to gains or losses, and similar applications of ML and the artificial intelligence frameworks it runs on are attempting to minimize the footprint of hedge funds and their respective market impact. 

In one recent breakthrough, Overbond launched a new range of AI-focused smart order routing (SOR) systems, which operates alongside the firm’s bid-ask liquidity scoring model. 

The automation technology helps to pinpoint the best possible trade execution opportunities based on price and liquidity, paving the way for the optimal compartmentalization of trades for large-scale orders. 

These innovations are a leading asset for institutions seeking to manage their market impact, and hedge funds rely on prime solutions as a leading means of delivering iceberg ordering innovation packed with intelligent order routing to break down the execution of trades at optimal prices. 

Smart order routing is a key consideration for hedge funds due to the challenges of breaking down large orders into many component parts. Any inefficient processes here can run up extensive fees that wouldn’t otherwise come into play when executing a single large order. 

To make iceberg ordering more efficient, the incorporation of AI and ML solutions to identify the most opportune associated costs for trades is essential for hedge funds.

The Battle for Discretion 

However, as the technology available to optimize iceberg trades improves, so too does the quality of tools available to other market participants in identifying large-scale orders. 

The lure of identifying iceberg orders stems from the advantages that investors can gain from understanding the movements of hedge funds and other market whales. They can also help to make sense of the true market impact of orders, helping traders to become more proactive in seeking out new opportunities. 

This year saw trading infrastructure provider Exegy add intraday signals to its AI-based iceberg order detection system. 

The system, known as Liquidity Lamp, will utilize intraday signals to provide extra visibility regarding the volume of iceberg orders throughout the day with the help of summary files that are delivered every 10 minutes. 

Technological Cat and Mouse

The evolution of technology surrounding institutional trading is paving the way for a game of cat and mouse among investors. This will challenge more hedge funds to adopt digital transformation tools that are sophisticated enough to bypass the threat of detection from other market players. 

For hedge funds that are ambitious about managing their market impact, investing in innovative tools can help to prevent the size of the splash that can be made when large-scale orders are actioned. His can be key in building a sustainable trading strategy that helps to ensure outperformance long into the future.