Imagine, if you will, a research paper that compares mammalian morphology based solely on the animal’s weight. A great weight match would be the 2,175 pound white rhinoceros and the 2,200 pound short-finned pilot whale. We suspect this study would not offer a whole lot of insight into the field. However, if the author added additional factors, such as habitat, diet and brain size to body weight ratio, the author might uncover more valuable revelations.
In the equity markets, market capitalization is a critical measure that allows us to compare stocks. However, like body weight, that factor alone may not allow us to accurately compare security behaviors. We are confident that Agilent, in the Healthcare sector, whose market capitalization is $38.4bn, has very different investing and trading characteristics compared to Fortinet, an Info tech company with the same market capitalization, but with daily volume and price a fraction of Agilent’s.
There are many factors we can use to create robust stock pairs. The most widely accepted method is a matched sample. We matched NYSE- and Nasdaq-listed stocksi by requiring the securities to be in the same sector, and by minimizing the difference between security market capitalization, volume-weighted average price (VWAP), and average daily volume.ii Our matching procedureiii resulted in matches on 1,356 securities. We then calculated consolidated quoted spreads, quote volatility, open auction accuracy and two measures of closing auction accuracy across June - August 2022.
We will show that our unbiased matching procedure shows that NYSE-listed companies, backed by our superior market model, led by the Designated Market Maker (DMM), and the unique liquidity proffered by the Floor community, attains generally superior market quality when compared to similar stocks listed on Nasdaq.
When we measured stocks across the whole matched sample, NYSE-listed securities exhibited strong advantages in the market quality measures. As Chart 1 below shows, spreads for Nasdaq stocks were wider by an average of nearly 11% and had 26% higher quote volatility. Price change in the five minutes after open was 8% larger for matched Nasdaq securities, and the price change from the last mid-point quote pre-close was 18% greater in Nasdaq stocks.iv
Chart 1: NYSE vs. Nasdaq Market Quality Matched Sample
Information Technology stocks provide a valuable point of reference. Many of the world’s largest companies by market capitalization reside in this sector. Our sample includes 137 stocks in the sector. While NYSE’s market quality advantage was not as large in Info Tech as the overall average, NYSE-listed securities garnered lower spreads and quote volatility. Close to mid-quote and close vs. last 2-minute VWAP were better too, although the last 2-minute difference was small.
Chart 2: NYSE vs. Nasdaq Info Tech Market Quality
There are many ways to measure volatility. Possibly the simplest measure is to look at a stock’s daily trading range or its day-to-day price change. Another popular measure looks at intraday trading ranges over short periods of time. This should have a closer relationship to an exchange’s market model, but it fails to give an accurate picture for less liquid stocks, that may not trade throughout the day.
Our preferred measure calculates the average second-to-second midpoint price change and then annualizes these results. If a stock’s quote is a moving target, investors may have a difficult time completing their trades and meeting expected benchmarks.
The NYSE market model helps limit quote changes as DMMs are required to maintain a fair and orderly market and have regulatory depth and continuity guidelines, which help to prevent large price moves over short time frames. Additionally, DMMs are incented to provide liquidity at the National Best Price (NBBO). These incentives and regulatory requirements helped NYSE to produce lower quote volatilities, in many cases by a large margin, in all sectors when compared to matched Nasdaq-listed stocks. In multiple cases, Nasdaq quote volatilities measure 10% or more higher than matched NYSE-listed stocks in the same sector. Chart 3 below shows the details.
Chart 3: NYSE vs. Nasdaq Quote Volatility
A matched sample that considers key security characteristics is the most accurate method for comparing listing-market models. While individual matches may still be influenced by one-off single stock news, across more than 1,300 securities, these individual anomalies should cancel out.
We show in this article that NYSE-listed stocks achieve tighter spreads, lower volatility and more accurate open and close auctions than their matched Nasdaq stocks, often by a significant margin.
i Sources: Factset - Market capitalization and industry sectors, NYSE Research - Market quality statistics
ii For volume, we include core hours trading only, and exclude auctions, to allow us to better measure differences in intraday market quality metrics. We used end of August 2022 market caps and sectors, and measured volume and price for the full month of August.
iii We matched based on propensity scores using VWAP, CADV and market cap ratios, and chose the best match for each stock. Once a Nasdaq stock was chosen to match to an NYSE stock, it could not be matched again. We required the stocks to be listed on the same exchange for each day during the study period and excluded stocks with recent splits. Matched stocks market quality was measured over June - August 2022.
iv All measures except quote volatility are in basis points. One basis point = 0.01%.
Comparing listing market quality across a large number of stocks is best achieved by using a matched sample, using key firm characteristics, such as sector, market cap, price and volume. Our analysis found that NYSE-listed stocks achieve tighter spreads, lower volatility and more accurate open and close auctions than their matched Nasdaq stocks, often by a significant margin.
The eight largest NYSE closing auctions have all occurred since June 2020, driven by growth in index rebalance events. We’ve previously studied the market impact of large auction orders and more recently highlighted the significant additional liquidity opportunities at the close. With significant index rebalances on the horizon, we now focus on volume dynamics in the days before and after large index rebalances, finding additional liquidity available in the market.
To help enable a data-driven, fact-based discussion around price improvement activity, NYSE has published a study quantifying the aggregate price improvement achieved by US equity investors in H1 2022 and analyzing its composition. Our study is based on public TAQ data and evaluates every standard trade in the first two quarters against the prevailing NBBO at that time.