Navigating Complexity: Session Recap: Key Takeaways from Rob Laible, John Bright, Tobias Unger, Michail Steliaros, Timothy Stark at Equities Leaders Summit 2026

2026, Equity Leaders Summit. Panel: Navigating Complexity – Reshaping Your Global Buy-Side Trading Desk Through Data and Analytics to Meet the Moment and the Future

Announcer: Stage. I'm gonna ask our next panelists to make their way straight here because we're gonna keep you on time this morning. This now is all about reshaping your global buy-side, trading desk through data and analytics to meet the moment and indeed the future. To guide us through this discussion is the head of America's of BMLL, Rob Laible and Rob introduce your panel and take it away.

You have 30 minutes on the clock. Thank you. Thank

• Rob Laible, Head of Americas, BMLL (moderator): you.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Wow.

• Rob Laible, Head of Americas, BMLL (moderator): Ah, feels good to sit down.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Yeah, it's a bit deep. It's

• Rob Laible, Head of Americas, BMLL (moderator): all right. We'll let everybody get settled.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Interrogation lights.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: How am I getting time?

• Rob Laible, Head of Americas, BMLL (moderator): So welcome to the fireside chat, reshaping your global buy-side, trading desk through data and analytics to meet the moment and the future. I think we've got a very distinguished panel here today to speak on this.

• Rob Laible, Head of Americas, BMLL (moderator): They are experts in their field. They are agents of change, and we're about to find out if clients are actually our best salespeople. I also wanna mention that John Bright from Fidelity was originally gonna be on this panel could not get out of Boston. Just stuck

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: with me instead.

• Rob Laible, Head of Americas, BMLL (moderator): So we went up with the designated hitter.

• Rob Laible, Head of Americas, BMLL (moderator): So thank you Okay. For doing that. I'd like for everybody to know exactly. Not just who you are, but really what is your role and your responsibilities? Because you, you all come at it from a slightly different angle and I think it's important 'cause you all arrive, I think, at similar conclusions.

• Rob Laible, Head of Americas, BMLL (moderator): So why don't we just go down the line. Mikel.

Michail Steliaros, Speaker 2: Hi I’m Michail Steliaros. I run the equity and fixed income beta assets at ADIA and Global Trading

• Rob Laible, Head of Americas, BMLL (moderator): to us To

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: elaborate or,

• Rob Laible, Head of Americas, BMLL (moderator): yeah. Yeah. What do you what do you do for a day job?

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: We don't have all day yeah. It's an interesting role. I'm very lucky to be able to manage the portfolio management side of things and the trading under one roof.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Part of the responsibility, I guess the biggest part is maintaining ideas, long-term views in the public markets. So the equity and fixed income assets that we hold and how you express these long-term views inside the, that portfolio. And on the trading side, we've got a very centralized, say, setup where we have 25 traders.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: More or less equally split between fixed income and equities trading around the clock. On the equity side, I would say it's pretty vanilla. On the fixed income side, it's extremely complicated and gives increasing in terms of complexity and the lack of data, the lack of visibility that we have in equity markets.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: But I guess for this audience, we can stick with the equity side of things. Yeah, that's great, Tobias.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: To be, I represent Norge as a quantitative trader. I guess I'm not gonna talk that much about what I, my team does, but rather what I do. So a lot of that is focused on, or has historically been focused on that kind of the technical stack in a quantitative stack, which is also why I'm sitting here with, with Rob. So I've gone through a couple of migrations of building up our market data infrastructure TCI infrastructure algo stack. So we do a global algo management out of my team. At the same time I've been involved in most of our in-house bespoke software and systems. So we run bespoke omas, CMS basically anything that moves in our pipes on a technology basis.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: And in the US I've also acted as a, call it a part-time equity trader,

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Tim. So my name's Tim Stark. I work at Capital Group. I manage a group of people that we collectively call market and transaction research. Before I was a capital group, I was a position trader for the first half of my career at a couple different investment banks.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And here, like our group is the market structure go-to experts within the firm. And we're also the firm that does all of the data analytics around equity trading function. We basically function as execution consultants to the desk to the trading desk in our portfolio managers to trying to tell them what tools work better more often than not in different situations.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And also we have a street facing function where we provide information back to the brokers about how they're doing comparative relatively to others. A lot of algo analysis, some cash desk analysis as well. And that's kinda what we do.

• Rob Laible, Head of Americas, BMLL (moderator): Great. TOAs, lemme start with you. 'cause I remember when we first started talking you mentioned there was an opportunity to try to create a bit of a new standard.

• Rob Laible, Head of Americas, BMLL (moderator): I think what you were hinting at was your peer groups were doing things maybe differently in that there was an opportunity to try to level set that. Could you maybe expand on that a little bit?

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Yeah I guess so I've been with nor so at, for nine years now. Obviously we work a lot and I have a lot of meetings with both the Dubai and the sell side.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: At least up until the last couple of years it's trending in a better direction. I feel like most of our meetings, they boil down to some. Certain basic, like very annoying things that everyone does. No one really seems to want to do them, but we're all in the same boat, and then we're vaguely discussing how to solve it.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: So when we talk about, or when I personally talk about like at a standardization, it's really about finding where we have a common foundation across the market, both buy and sell side. And seeing if we're able to lift that into, call it a co, co-joined potentially service provider, then.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: So effectively for us, what we're targeting is to reduce a bit the mote that has existed on technology and ideally just you retain the mote on your talent instead of on the technology side.

• Rob Laible, Head of Americas, BMLL (moderator): Makes sense. Michail, Miguel you've implemented a lot of changes at AIA over the years.

• Rob Laible, Head of Americas, BMLL (moderator): Can you walk people through maybe how you addressed. Some of the changes that you had to make, whether it was pain points or an ROI type of decision, or,

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: yeah, I mean for what is relevant for this topic here, I'm just trying to copy what the bias is doing. That's the short story.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: They're way ahead in that concept of integrating systems, using what is best in class for the particular task, but essentially creating a framework and infrastructure where the the unique tasks that you try to achieve are. Owned by you and you have the ability to trade and calibrate your execution to the needs of the firm that are for everyone.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: It's different. And then use a certain set of, OMSS providers, strip them down to the bare basics and create that layer of logic. On top. So from the execution side, this is a big effort. It's ongoing. I don't think it ever ends. I dunno, you tell me you ever get to that point. But with the ability to have, the technological advancements, the data provision, all these things are becoming easier and easier.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Markets are becoming more complex in terms of fragmentation participants. How do you trade? For me the most important thing is the link between PM intention. And the trading desk and being in this latty position of having visibility onto both that integration, I think is very important.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: It's, most places don't necessarily have that, so it's not about how much spread capture can I bake in my vwe and whether I'm 12% or 9% or 15%. Of spread it is what is the intention of the trade? What is the long term or for us long term, alpha or beta behind the trade, and how do you link that with the way you execute?

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Obviously for other people, it'll be different if you're a high frequency trader, if you have shorter, if you have high churn type, portfolios, other things may matter. But from our perspective, because it is large pool of assets, large types of trades that take. Long time to execute other dynamics that are usually not taken into account by an algo needs to be taken into account and incorporated into execution.

• Rob Laible, Head of Americas, BMLL (moderator): Makes sense.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Also if I could just add on Yeah, because I find that interesting and like one thing I've forgot to mention is that ultimately internally, and I think mostly on the buy and sell side, a lot of the market data processing and baseline TCA et right? It gets punted to like the juniors on the desk, whoever's the most inexperienced and then they learn through that and fine. All good. The problem is that a lot of the things that so here and ourselves are actually looking at and trying to solve is on midterm and long term horizons. And at that point it does not really, you want your tactile, your quant talent to focus on that and not focus on what condition code should be interactable volume in Europe.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Which is ultimately what they have to do now, because it cannot, you need some market understanding to do the nitty gritty as well. But our quants historically have focused way too much on the nitty gritty and not enough on the mid and long term, and translating the PM instructions into the markets, which is what we're trying to solve.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Yeah,

• Rob Laible, Head of Americas, BMLL (moderator): it makes sense, right? People talk about quants, hiring an army to take in the data, clean the data, munge it, store it, make it available to people. They should be focusing on Alpha or we've

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: got you for that.

• Rob Laible, Head of Americas, BMLL (moderator): Yeah.

• Rob Laible, Head of Americas, BMLL (moderator): Is this with,

• Rob Laible, Head of Americas, BMLL (moderator): Tim? I'm sure that resonates with you 'cause, because I think your approach has evolved over the years too, where you probably did a lot of in-house build and then, looking to partner with people.

• Rob Laible, Head of Americas, BMLL (moderator): And I know you're talking about buyer build later, so I don't want you to expand too much on that, but Tim, why don't you jump in on that

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So I can, I can do this and it is actually, apologies gonna be a little bit of A-B-M-L-L commercial. So for the past 15 years, we've had an architecture where we connected to real time streaming market data, which of course we use in our trading system and all that.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: But we also, we've been capturing it and then using that for all of our post-trade analysis that we do, and we have a rather sizable. Infrastructure that we have built up and processes that we have built up to do that because we don't think any of the TCA vendor providers out there do a particularly good job at giving anything resembling actionable information that a human being would look at and go, I'm gonna do something different next time.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So that's what our team does. And what we found is that as time has gone by. Is the rules from the people. We're getting the information from both the data, the exchange data, realtime aggregators, and then all of the individual exchanges themselves. The cost of dealing with all those relationships has gotten just ridiculous.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: We get audits from the individual exchanges. We get audits from the aggregator. The best example I had is we had about three years ago, someone come to us and go. You know that legal agreement we signed with you 20 years ago about how you can use our data and it was literally, I think it was like 18 years old.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: It says you can absolutely store our data, the exchange data, trades and quotes, but it doesn't say you can use it.

Speaker 5: Yeah.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So you owe us 18 years of back fees because you've been using it, not just storing it. And that's the kind of stuff we're going through. So not only is there explicit costs, there is all the costs, the human costs of administering all of these agreements and dealing with all these audits and everything.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So what we have done is for real time uses, we still have real time data. Of course, yeah. And then those are all access controlled by the individual in the exchange, whether it's true real time or the 15 minute delayed or whatever. But for all of our post-trade processes, we are switching in the extent that we haven't rewritten the whole code base yet we are clients of BMLL and we're switching over to that because they're taking care of all of that for us.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: We don't have those exchange level agreements and we're, they're not necessary anymore. And the other thing that they're doing to go back to your thing about condition codes is they are doing all of the work that we were doing internally about, we're taking all of these trades, which ones do we want to include or not when we consider accessible liquidity, they're doing that now for us.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And we don't have to continually update our processes to make sure that our calculations are relevant. And it's again, a thing we could do ourselves, but instead of us having to pay for doing all of it, they're doing it once and sharing the cost among X of that, that admin cost among X number of clients.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And it just has taken a lot of the administrative overhead for us out of the equation. And oh yeah, it actually wounds up being cheaper, explicitly in the checks we have to write to people than what we were doing before.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: I think splitting history and lamb and live is probably our biggest, like system-wise success.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Yeah.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: And the other thing that I would just want to add onto everything, I fully agree with everything you said. It allows your research and your history work on the historic data to move separately. So move at different speeds than live, right? Yeah. If you can joinin them, then every change you have to make to your live processing will be your history and you, your researcher can't work until someone has made a change to your live system, which it lets them act as separate services and they have separate users.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Yeah. Usually

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: The other one fun thing is that when you're capturing real time data, you only have the data for the symbols you've told it to capture, and no one's ticker plant is ever perfect. Symbols change and it doesn't get caught in time, whatever. Or you just didn't subscribe to a symbol 'cause you didn't know you were gonna want that data at some point in the future.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: What is nice about this system is because they're taking end of day files for an exchange. They if they have the exchange, they have every symbol that trades on it.

• Rob Laible, Head of Americas, BMLL (moderator): So I saw Tobias, you were nodding your head on the real time historical and you were wincing when he talked about the 18 year history.

• Rob Laible, Head of Americas, BMLL (moderator): They must have come audited you right after capital or something. One thing I'd like to get at too is people think that trading desks are just trading desks. I think the information that's being captured there permeates across the organization. It goes upstream to the portfolio managers, et cetera.

• Rob Laible, Head of Americas, BMLL (moderator): Can you talk about that a little bit? 'cause it should, because you've got everything.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: It doesn't, it should necessarily

• Rob Laible, Head of Americas, BMLL (moderator): Okay.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Do that. And my biggest pet peeve is when PMs try to do trader's jobs, say, no, I know how to trade. Oh, you should trade this one hour twap, and then two hour vwa, and then hold off and then start again 15 minutes before the close.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: I'm like, that's not your job. So with data, with the proper infrastructure, essentially you need to convince people that's not the right thing to be doing. And let the traders be traders and the portfolio managers be portfolio managers, but that loop and that information. Is essential and it's usually neglected when you make an allocation decision or an alpha or a better decision.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Most PMs in most places, I'm not talking just about us, don't take into account the cost of that decision. And when they do, usually it's rudimentary. It's oh, it would cost me 10 bits to do something, and that's about it. So that feedback loop is essential. That's on one side of the fence. The other thing that I have an issue with is all the artificial benchmarks that we're imposing on trading risks.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Like what is VOP? Like why should the benchmark for trading be v WP and get measured on how close to v WP you are? That is totally artificial. You have a decision to make, you need to invest your capital in a certain way. Why should we want bigger benchmark or market on close? It is, it's, it doesn't make any sense.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: 'cause you're, you are breaking that link by imposing these types of benchmarks to trading desks. It is, have a decision to make. It would cost me x to do it. Can I do it better? And that's where the modeling and the data and the higher fidelity and higher accuracy, that, again, it's not A-B-M-L-L sort of advertising session, but that's something that you've helped a lot in clarifying especially in markets like Europe where it's not clear.

• Rob Laible, Head of Americas, BMLL (moderator): You're,

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: it's a little messy. What? It's addressable liquidity. But back to your question, yes. That feedback loop is essential. And I, in my experience it doesn't exist to the degree it should in, in the industry. It's throw something over the fence, trading, do your job, but what is your job? Defined by what that's why that integration is paramount and we are.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Lucky because we don't have clients, we don't have, it's one pool of assets we need to do what's best for that and long term capital preservation and growth. When you have, multiple clients, they have. If John was here, we've had this discussion with John Fidelity for many years.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: They have so many mouths to fade and so many different. Funds and objectives that trading becomes so fragmented and compartmentalized. It's super inefficient vis-a-vis the total. But again, that's from our side, I would say it's a much easier job to create those links. Much more difficult in many other places.

• Rob Laible, Head of Americas, BMLL (moderator): So Tobias, have you become more data-driven in terms of the communication? It's, you were nodding in agreement there. So

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: I think to a large extent we've been relatively data-driven over the last, call it around a decade, slightly less maybe. There's more trust. I think that's the biggest difference.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: A little bit like Michail here talked about we also like thinking about this as in the PMs. The information he takes in to make his decision stops at some point, and then the trader takes over and then a broker, I go, something takes over. So we're trying to ensure that there's not too much overlap between those various scenarios, and that also means that a trader, effectively what we're trying to do, at least for a lot of, for like our chunkier positions, is to compliment the trader, right?

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: And not replace them. Lot of the trader replacements that I usually see is you, we up something 2% or something over the day, right? We're not beholden to a view benchmark. We, we never are. So what we're really seeing with the data and the changes that have, for example, through yourselves is that there is a bigger, larger degree of trust and there's a larger degree of adoption of new metrics, new tools, new models onto this.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: For us, we're also lucky in the sense that we've, we have a strong technology focus and we've for the last 10, 12, 15 years, I think built our own O-M-S-E-M-S that runs on the side of our main pipe, which really allows us to have a zero time to market. So we don't have a research team that publishes a report that sits on the side and no one uses, if it sits within my team or in my, in the associated teams.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: You don't build something that doesn't hit a desk. It's not interesting, like research becomes obsolete quicker than you can use it. So to a large extent we push things directly through our through to our trading desks.

• Rob Laible, Head of Americas, BMLL (moderator): Tim I'm guessing you might have a different story in terms of managing PM's expectations.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Yeah, so we have low turnover. We have long holding periods. We, a lot of times when you try to talk to. PMs about trade costs or whatever. They're like you're talking to me about, 200 versus 150 basis points to get into some very large position that I'm looking to be a two bagger or a three bagger over the next five years.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So I don't really care. But where we have found traction is the other thing, if you guys don't know capital, we have a thing called the multi portfolio manager system. So for one of our mutual funds, there's not a PM, there'll be like six, and they each have a chunk that they get to manage. But there is a principal investment officer for the fund.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And what we found to be interesting in fruitful discussions then, or where individual PMs are outperforming or underperforming as individuals, then we can talk to them about what their trading patterns look like. And then we start to tie, you know what they, if they are a high cost PM and they're outperforming, who really cares?

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: But if they're underperforming. Then we can start to have a discussion about how frequently they're updating their portfolios, what their transaction costs are like. And there we have actually seen tweaks in behaviors from people. But it is they are sensitive discussions in the way things need to be framed and couched to bet.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And some people are just more open to it than others.

• Rob Laible, Head of Americas, BMLL (moderator): Yeah,

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: it same goes for traders to be honest.

• Rob Laible, Head of Americas, BMLL (moderator): It's always been about the feedback loop, right? Yeah. Can you learn from it? And it's

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: also about materiality, right? Yeah. The businesses are different. What is the important thing you need to tackle first?

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: In, in team's case, because of the horizon, because of the big positions, market microstructure and the nuances of every child order are less relevant. For a quant high frequency fund, they're super relevant.

Yeah.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: For us it is horizon. It is very long duration and horizon trades that are at the portfolio level.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: We don't trade single stocks because of an active fundamental view that we expect 20% return in a year. And then yeah, the 1% trading course doesn't matter. It matters 'cause it's beta, it's big portfolios and everything that you can save matters a lot. But as I mentioned before, it's not because of having a better grasp on the microstructure of every market.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: It is a better grasp of horizon risk. What is the volatility over the five days that is going gonna take me to trade for the entire portfolio, not for a single stock. So all of these things generate the need for different types of models, data and focus sometimes because the more nuanced and the more sort of heavy data driven, essentially, especially for us, like a qu it is a sexual problem to tackle.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: You may go down rabbit holes that are totally unnecessary and spend too much effort for things that don't necessarily move the bottom line.

• Rob Laible, Head of Americas, BMLL (moderator): Tim, did you wanna jump on that? I think you were no. Okay.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: I just find it interesting because you still have the problem with what does actual transaction cost, right?

Yeah.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Like when usually we model, like most people model it from the order sent in.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: Okay, so when a PM clicked, optimize and send something that's your T cost. But that's like woefully incorrect as well, right? Yeah. And then you talked, already talked about MOC and vwa and all the also incorrect, right?

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: So there's not even like a proper and obviously not really possible, a proper industry standard for TCOs for your actual impact. It is at the micro level, but at the larger portfolio level. Pretty lucky.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So I guess actually, so I do have one thing. It's what is the transaction cost? One of the more interesting angles that we've come in when you're talking with PMs is not talking about the cost itself.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: It's talking about the reversion, particularly when that PM is giving instructions to the desk. I just want to get done. And when you go to them, the cost, they're like, okay, so that's the cost. But it's but if you'd slowed down, you probably could have saved X number of basis points. And when you can show them that not on an order, 'cause an order is a roll of the dice, when you can show them a behavior like that occurs again and again.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: We have seen that change people's instructions to the desk.

• Rob Laible, Head of Americas, BMLL (moderator): Yeah. So given where you are in terms of. Becoming more data driven, more process, more systematic. W what's on your to-do list in the next year or so?

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: For me personally, is this integration of logic onto the systems that we have and is what Tobias and the team have done, which is create this ecosystem.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: Where the intention of every order of every portfolio trade, of every thing that we do is very clearly translated into algo, essentially behavior. It's that, that usage of as much information as we can plus trading, acumen translated as mechanically, the systematically as we can to essentially release the traders to do the higher value add activities, which is find blocks discuss with street civil liquidity lies, but automate systematize.

• John Bright, Head of Systematic Trading and Quantitative Analysis, Fidelity Investments: A big chunk of the workflow that doesn't need to be touched. But to do that, you need to essentially translate a lot of the PM and trading logic into systems, that, that's essentially an execution ecosystem, we call it, that spans the O-M-S-E-M-S pm intent and trading behavior.

• Rob Laible, Head of Americas, BMLL (moderator): Dubose, what's on your agenda?

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: I think it's somewhat twofold. I guess we have a significant amount of our flow is very chunky and high alpha as well. So I guess it's somewhat twofold in a sense that we're looking to more, call it more thoughtfully, treat the high beta flow. A lot of it through the same means as Michail is talking about here.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: And the other side is enabling the traders to a larger extent, treat the alpha flow or the chunkier flow in a better way. So effectively giving them a better view of what or ourselves, a better view of what is going on in the market, not just on the lines we're looking at, but on everything, on the entire ecosystem.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: So the thing we're looking at or working on right now is predominantly a. It reduces the separation of the P-M-S-O-M-S-E-M-S and I I just want one system. If it's one account, the traders and PMs all manage the same risk anyway. Why do I have so many systems? I just, I don't need them.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: And being able to thoughtfully look at your live interactions, long use everything happening in the market, letting your traders disseminate that, and still having the systematic approach to trade on the portfolios. I think that will be our 2026.

• Rob Laible, Head of Americas, BMLL (moderator): What about you, Tim?

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: So I'm gonna go a little more speculative and the other thing is we have very different trading problems than these guys who fundamentally trading their own money.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Absolutely. It, I started in this business as an fa in, in, on the international desk at Goldman in 98. And if I think about from then until now, the role of the human in the system. Like the sell side and the buy side trader is fundamentally really close to the same job. The way you do things, the way you interact with the system in front of you is a lot the same.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Of course there's algos and of course there's ATSs and all this kind of stuff. So the market structure has changed, but the role of the person really hasn't. And a lot of the stuff that we talk about here with data and stuff, fundamentally you could do all that stuff 25 years ago too. It was really hard 'cause you were writing like see to do it but you could do it all if you had the resources.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: What's happened is a lot of the things are easier and we have we are able to use the data that we have in ways that you just couldn't, for cost reasons and complexity reasons before. But I do really think that things are going to start to change now. I think the amount of flow that is no touch is going to start increasing.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: I think the use of AI agents to start to do things that were just too hard to do before. Are going to change the way humans interact. And I think humans are gonna become a lot more like that person in the emergency control center that is watching things happen and is only interacting when they need to.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: And I just the humans are gonna take the most idiosyncratic trades, but most of the rest of it is gonna start to get automated. And I think that's gonna be the change and figuring out how to do that the right way. I think is the job of the next five years.

• Rob Laible, Head of Americas, BMLL (moderator): I was wondering how long it was gonna take us to talk about ai.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: I think it really 'cause the typical use case, so LLMs are whatever, right? But it, when you're using LLMs to code just think about the typical thing with a human and an s is they want alerts When interesting market events happen. But how do you make, how do you not get so many false positives that you just turn the alerting system off?

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: You could design that as super complicated if false statements. That's all it is. But the number that you would need to capture all of the corner cases means that the programming you'd have to continually update them means that the programming job becomes complex enough that no one actually has ever designed a good alerting system for an oms.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: I really think you can actually do that now with agents and AI because it'll learn over time. All you gotta do is click meaningful or not when the alert pops up and it'll learn over time and it'll rewrite the rules for itself. Now, something that was a very complex, a k, a expensive programming problem become something that you can actually develop and design.

• Tobias Unger, Senior Quantitative Trader, Norges Bank Investment Management: That's

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: also been, and that's how I think AI is gonna change.

• Rob Laible, Head of Americas, BMLL (moderator): Great. Yeah.

Good use is, that's the panel that's coming up next.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Oh, sorry.

• Rob Laible, Head of Americas, BMLL (moderator): We teed it up for you. I like to thank everybody for coming up and taking the time to, to put this panel together. So thank you guys. Thank you.

Thank Very good.

• Timothy Stark, Equity Market Structure and Transaction Research, Capital Group: Thanks

Announcer: Jen. Sorry time to cut you short on that, but it's a beautiful segue, so thank you very much indeed. Take that up beautifully.