The data team at Exegy has used our Signum signals Quote Fuse and Quote Vector to enhance a Volume Weighted Average Price (VWAP) algorithm with predictive power. We’ve published a whitepaper explaining this “intelligent” VWAP algo.
The VWAP whitepaper shows how our enhanced VWAP uses knowledge of imminent changes to the NBBO to improve execution costs over a standard VWAP—by over two basis points. And we lay out the data supporting our conclusions.
Following the VWAP Curve
Firms seeking to execute large orders with minimal impact on the market must slice them into smaller orders, carefully timing their placement in accordance with an algorithm. One of the most common of these algos spreads out orders so that they track the volume-weighted average price of an asset over a trading session.
For example, a VWAP algo may assign a larger part of the order to the first minutes of the session, based on its volume profile. Our VWAP whitepaper gives an example of a VWAP distribution.
How do you make a VWAP “smarter?” Add prediction.
The Power of Prediction
Exegy’s Signum Signals-as-a-Service offers two AI-powered predictive signals:
- Quote Fuse, which shows the probability of a price change to the NBBO for a given equity in the next 50-millisecond interval.
- Quote Vector, which shows a pair of probabilities for a given equity: The probability that the next change to the bid price will be up, and the probability that the next change to the offer price will be up.
As our VWAP whitepaper shows, Exegy’s team was able to enhance a standard VWAP by making minute improvements over short timescales, adding up to more than two basis points of improvement overall.
It’s a compelling argument for adding predictive signaling to your toolbox—and for developing your own enhancements to existing strategies.
Curious about our intelligent VWAP and how you might replicate its success? Read the VWAP whitepaper. When you submit this form, a member of Exegy’s team will send you a copy.