Last week, Exegy added intraday signals to its AI-powered iceberg order detection offering, Liquidity Lamp. The enhancement provides quantitative traders with visibility on the volume of iceberg orders throughout the day using summary files delivered every ten minutes.

Traders Magazine spoke with Andy Lee, Director of Quantitative Research at Exegy, to learn more.

What is the background of Liquidity Lamp?

Liquidity Lamp first came to market in 2020, as a real-time product for customers who consume data via the Exegy Ticker Plant.

Liquidity Lamp is originally a product that detects when a reserve order is found on US equity markets. Once we find it, we can track it in the order book and also the price book. But a lot of customers came to us and said, “Is there a way that a mid-frequency, or even a low-frequency product can be derived from that HFT signal?” That’s when we came out with our initial end-of-day product.

The end-of-day product basically provides a summary by tracking the reserve orders. It allows us to note that a particular order was traded against at this exchange for this symbol at that time of the day, and we can roll that up and tell customers really easily what symbols, how much volume, and how much notional value was traded on any given day.

That product really galvanized Liquidity Lamp, because it was the buy-side firms that were looking for alpha and looking for unique, differentiated data sets that were uncorrelated to anything they were already working with. So that’s the storyline of how Liquidity Lamp became a success.

What is the essence of the new offering?

This new product bridges the gap between the real-time product and the end-of-day product. We had been thinking, “Is there a way we can deliver the customer the same end-of-day summary file that’s easily consumable, but every 10 minutes instead of end-of-day so they can action something when it’s most tactically opportunistic rather than having to wait until the next day?” This is the answer.

Who are the core users of Liquidity Lamp?

It’s quantitative, systematic funds that are looking for statistically significant data points and using Liquidity Lamp in AI and in their models. Other users would be stat arbs, mid- to low-frequency intra-day traders, and multi-day traders. The product is not geared toward fundamental investors.

Do you expect some customers who use the end-of-day product to switch to this new product?

People have different objectives. Some customers have strategies that involve accumulating information across multiple days, weeks, and months, rather than intra-day; they will still be happy with the end-of-day product. But other customers want to deploy this more on an intra-day basis. They may see a large iceberg order trade in a given name, and they want to take advantage of that information intraday, because that information may not be helpful tomorrow. So it just opens up the opportunity for new and more strategies to use this, versus the end-of-day.

Comparing Liquidity Lamp real-time with every 10 minutes and end of day, what is the difference in ‘lift’ from the user’s perspective?

Real-time is infrastructure-intensive – you need to purchase a ticker plant and consume full-depth market data feeds. End of day is the opposite – we just give you an AWS [Amazon Web Services] free bucket to grab the data files from, which you can do with commercial internet access on your laptop from the basement of your home.

The new intraday product has some infrastructure necessary because it is consuming real time market data, but it’s mostly distributing out to AWS. It’s a hybrid approach, but we take up a lot of the infrastructure cost and try to make consumption very easy for customers.

What’s the most important takeaway from the associated whitepaper?

One point is that we had some early adopters of Liquidity Lamp come back to us and say this is beneficial as a creative product to our existing P&L. Meaning, instead of creating brand new alpha, what it does is enhance our existing strategies. That was the draw.

Because of that draw, in the whitepaper, we took the early adopters’ approach. We said, “Let’s design a basic, plain vanilla stat arb strategy and then inject that baseline model with Liquidity Lamp information to see if it creates a better portfolio, a better strategy.”

And that’s exactly what we found. It reduces draw downs, it increases returns, it increases your Sharpe ratio and beats the S&P 500 on a relative basis, but it also defeats the baseline stat arb model on an absolute basis, which we were really pleased about.

Final thoughts?

We’re not traders at Exegy. From a customer perspective, that is an important consideration.  Rather, we’re trying to take tools that are closely guarded at most HFT shops and democratize those signals so that more people can access this information to create their own alphas and improve their strategies.

(This article first appeared as Trading Reimagined on Traders Magazine. Trading Reimagined is sponsored by Exegy.)