The artificial intelligence-based order type could make stock trading even more efficient.
Nasdaq announced that the United States Securities and Exchange Commission (SEC) has approved its request to operate the first exchange AI-driven order type on Sep. 8.
Called the dynamic midpoint extended life order (M-ELO), the new system expands on the M-ELO automated order type by making it “dynamic,” meaning it will use artificial intelligence to update and, essentially, recalibrate itself in real time.
⚡ Bringing AI to the capital markets: Today, @Nasdaq announced it has received @SECGov approval to launch Dynamic Midpoint Extended Life Order (M-ELO), the first artificial intelligence (AI) powered order type.
Learn more about this next step we are taking to modernize markets,… pic.twitter.com/vFkLdjM3Br
— Nasdaq (@Nasdaq) September 8, 2023
Order types are a set of software instructions that execute specific trade pairs at exact market pricing thresholds. This form of automation has been around for a while but the new AI-driven order type is the first of its kind to use real-time reinforcement learning AI to execute orders.
This should have the follow-on effect of substantially speeding up orders placed with the system. In a blog post accompanying the approval announcement, NASDAQ stated that dyamic M-ELO had demonstrated a “20.3% increase in fill rates and an 11.4% reduction in mark-outs” during their research and testing.
According to a data sheet published by Nasdaq:
“Calculated on a symbol-by-symbol basis, this new functionality analyzes 140+ data points every 30 seconds to detect market conditions and optimize the holding period prior to which a trade is eligible to execute.”
By adjusting the holding periods for orders in real-time, as opposed to the traditional system which simply applies static timeouts to orders, fill-rates should increase without a significant increase in market impact.
Related: Bybit debuts AI-powered ‘TradeGPT’ for market analysis and data-driven Q&A
The advent of artificial intelligence technologies for the fintech sector has impacted the entire financial industry. ChatGPT and similar large language models have been adapted for use as educational tools for both traditional stock and cryptocurrency traders.
NASDAQ’s previous forays into combining AI with finance include the inclusion of predictive AI models to aid in parsing the more than 1.5 million options listings in the U.S. market.
