Exegy, the market data and trading technology solutions provider, has enhanced its AI-driven iceberg order detection tool, Liquidity Lamp, with the addition of intraday signals that provide quantitative traders with additional insights into iceberg order volumes.
The new intraday version of Liquidity Lamp, which filters out the ‘noise’ typically associated with retail and high-frequency trading (HFT) activities, summarises iceberg trading activity every ten minutes and presents it in an easily digestible CSV format. The resulting files can be accessed via a direct cross-connect at the NY4 data centre or through an AWS S3 bucket specified by the user.
“This is bridging the gap between our real-time customers, who get this data on every single tick but are required to have an Exegy ticker plant, which is a significant piece of infrastructure, and our customers who pick up the data at the end-of-day via AWS,” says Andy Lee, Director of Quantitative Research at Exegy, in conversation with TradingTech Insight.
The development comes as a response to the growing need among institutional investors for sophisticated tools to monitor large-volume trades, which are often obscured by exchange-native iceberg orders, which, by their nature, reveal only a fraction of the actual order size. The introduction of intraday files to Liquidity Lamp offers such traders the ability to leverage iceberg data for making strategic decisions in near real-time, thus capitalising on trading opportunities as they arise, before the market closes.
“The CSV files are well-structured, with each line representing a specific symbol, indicating the volumes and notional values of all stocks traded as iceberg orders in the preceding ten minutes,” says Lee. “This arrangement provides a clear, row-by-row presentation of data, making it straightforward to interpret and utilise.”
The intraday volume signal, powered by Exegy’s proprietary iceberg order detection algorithm and leveraging data from the Exegy Ticker Plant, empowers traders to uncover institutional order flows, gain insights into informed investor actions, and understand price impact dynamics. This enables optimised portfolio positioning, timely responses to significant institutional volume, and the enhancement of predictive models for improved market responsiveness. The new enhancement aims to not only enable traders to detect hidden liquidity but also to refine their strategies by incorporating insights not typically captured by traditional models.
“Customers to date have been 100% alpha seekers,” says Lee. “So systematic traders, quant hedge funds, stat arb traders, those looking for new and differentiated data that can drive distinctive alphas that are uncorrelated to anything currently in their portfolio. And the delivery mechanism makes it easily consumable by anyone. If you have internet access, you can access this from the cloud through an AWS environment.”
David Taylor, CEO of Exegy, comments: “This dataset represents an opportunity for the quant trading community to elevate their strategies with a unique view on intraday institutional trading activity. Its integrations into sophisticated models by early adopters is both intriguing and inspiring.”
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