Buy-Side Trader Q&A: Enrico Cacciatore, Voya IM
Enrico Cacciatore, Senior Quantitative Trader, Head of Market Structure & Trading Analytics, Voya IM
What is the access fee pilot and what does it mean for buy-side traders?
Rule 610 was implemented in 2007. This is essentially a fee cap, rebate cap of 30 mils, or $.30 per 100 shares on transactions traded on regulated exchanges. The impact of this Transaction Fee Pilot for buy-side traders is around understanding ‘maker-taker’, or fees associated with transactions on regulated exchanges. The SEC wants to empirically evaluate how those fees impact execution quality, as potentially there is some broker conflict in how they route orders to the marketplace based on those fees that might be against the investor’s best interest, as well as market quality in general.
Essentially, they’re taking around 1500 symbols, including ETFs and ETPs, and breaking them into two buckets. Each bucket is roughly 730 securities. One is going to really test the fee cap, so it goes to 10 mils, both for fees and keeping the rebate uncapped. The other one will test the rebate — you maintain the 30 mil fee cap, but there is no rebate.
And then the remaining approximately 5600 securities that are eligible for this, they become the test group. They’re going to try to empirically evaluate all those names.
My big concern is that we need to understand the intent of what the order route is going to the marketplace. That’s not being captured right now. We’re going to look at the effect on spreads, volume, and volatility. Does volume migrate from one exchange to another? Does it go off-exchange? That’s what the SEC is going to evaluate.
We want to understand the intent of the order route. Another big concern for me is the potential for some sort of coding error with these new venues, which could provide some short-term event within the marketplace and disrupt markets. So I think it’s important that we take our time and that SEC is patient in allowing market participants time to prepare for this pilot.
How might the newly announced Members Exchange (MEMX) disrupt the equity trading landscape?
MEMX, or Members Exchange, is fascinating in that it brings in a player that is a kaleidoscope of nine unique players in a marketplace. You have four of the largest eBrokers, three of the largest sell-side broker dealers (of which one is the largest ATS provider in the marketplace), and two of the largest market makers that trade over half, probably more like 70 percent of the retail order flow in the marketplace. I expect this will disrupt the marketplace. Even if they don’t capture the market share that they expect, their collective power will force exchanges to become more transparent on market data fees and fees in general.
How is Transaction Cost Analysis (TCA) evolving?
There are three critical pillars for Transaction Cost Analysis, or TCA. One is transparency — transparency at every point. Two is data capture. How do we capture analog, human behavioral information into digital? And the third is applying this transparency and data capture into an optimization problem utilizing machine learning and artificial intelligence.
Historically, TCA has simply been the PM’s send in orders. It tells you your benchmark, which might be to participate over the day, perhaps with VWAP or on arrival. If an order sent in at 10:00, the price at 10:00 is my benchmark. If I can get that or better, great.
Or it might be the close, the last price of the day, or the open. Those are very static points, and they can be gamed. So I think where we’re going to now is that we want to capture every state of the trade. If we can understand every point of the process and quantify that into an alpha signal, we’re going to improve it over time.
How are trading desks managing data?
Let’s look at the tech sector and look at how we capture data. Before, you had catalogs, you went to the store, and marketing research would give you the characteristics of what’s going on and what’s the retail order flow at the mall.
Now, you have your phone on you, and it captures everything you do, what you’re looking at. It’s listening to you. All of that is going digitized as information, and then they can sell it to the providers and they can optimize who’s going to buy and when’s the best time.
We’re trying to take that same model into trading. What has changed is the ability to digest that data — the computational power, the databases that can process tons of data quickly and efficiently.
Another critical aspect is that the need for transparency and synchronized time stamping on the exchanges has made the data much more efficient and clean for evaluation.