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Nasdaq’s Chai Discusses The Tech That Manages Risk And Volatility

Roland Chai talks digital transformation and volatility in financial markets and outlines areas where Nasdaq is expanding its suite of offerings, including cryptocurrency custody and the tokenization of carbon credits.

27 min read

FinanceModern Money

Roland Chai, Nasdaq

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The digital transformation of financial markets has spawned incredible connectivity and efficiency, but it has also created plenty of challenges. Roland Chai, executive vice president for market technology at Nasdaq, joins the show to outline how new technologies are enhancing market resiliency — even in the face of extreme volatility events like interest rate moves, wars, bank failures, the GameStop frenzy and the pandemic.

Roland explains how investors are leveraging algorithmic trading and other technologies to manage risk in globally connected markets and he also delves into numerous other areas where Nasdaq is expanding its suite of offerings, including cryptocurrency custody and the tokenization of carbon credits. And, of course … you can’t talk about technology these days without talking about artificial intelligence, so Roland covers that ground as well.

Key highlights

The impact of digitalization on markets in recent years – (5:28)
Maintaining market resiliency through extreme volatility events – (9:26)
How the speed of news and other information is reshaping markets – (11:02)
Should the use of circuit breakers be expanded? – (13:33)
Challenges presented by digital transformation – (17:43)
Artificial intelligence in markets – (20:14)
The people behind trading algorithms –  (24:17)
Areas where Nasdaq is expanding its footprint – (26:41)

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(Note: This transcript was created using artificial intelligence. It has not been edited verbatim.)

Sean McMahon  00:18

Hello everyone and welcome back to the Modern Money SmartPod. I’m your host Sean McMahon … and today we are going to be talking about the technology that powers global markets. My guest is Roland Chai, Executive Vice President of Market Technology at Nasdaq and Roland is going to share his insights about the underlying technology that helps markets operate with efficiency and, perhaps most important, resiliency. Think about it …. The last few years have given us plenty of examples of extreme volatility. There have been interest rate moves … wars … bank failures … the gamestop frenzy … and yes, even a little event called the pandemic.

Throughout ALL those events – markets continued to function. Not just in terms of things like price discovery and capital flows … but the actual markets remained open. They kept the lights on, if you will.

Roland is going to outline what it takes to maintain that level of resiliency and the role automation and digitailization play in rapidly evolving markets. And with his extensive background in risk management, Roland will also outline how investors are leveraging algorithmic trading and other technologies to manage risk in globally connected markets where money is moving 24 hours a day. We are also going to delve into other areas where Nasdaq is expanding its suite of offerings, like cryptocurrency custody and carbon markets … and, of course … you can’t talk about technology these days without talking about artificial intelligence, so Roland and I will cover that ground as well. We had a great conversation, I hope you enjoy it.

Hello, everyone, and thank you for joining me today. My guest is Roland Chai from Nasdaq. Roland, how you doing today?

Roland Chai  02:10

Hi, Sean, I’m great. Thanks for having me on your podcast, really pleased to be here.

Sean McMahon  02:16

Yeah, I’m excited to bring you on, we’re gonna have a pretty deep conversation about the role technology is playing in today’s modern markets. But first, tell me a little bit about yourself. What’s your role at Nasdaq and your background in industry?

Roland Chai  02:27

Yeah, so my role is Executive Vice President of market technology. And I’m joined Nasdaq three years ago. Originally as chief risk officer, I performed the chief risk officer role for two years and I moved into looking after the commercial technology business about a year ago. Prior to that, I’ve sort of done a world tour of exchanges. I was at Hong Kong exchange, chief risk officer there and also then looked after post trade. And then prior to that I was at LCH. London clearing house which was part of the LC group. I ran equities clearing there. And then before that are sold off in in Australia working for the Australian Securities Exchange, and the Sydney futures exchange to start off with that. And before that, just various technology rolls in and around capital markets, foreign exchange futures options, and cash equities in Sydney. So from Sydney, to London, to Hong Kong to New York and Stockholm. It’s been a very varied ride through through all the different capital markets across the world.

Sean McMahon  03:38

Yeah, that sounds like an exciting career kind of bouncing to all the different corners of the world. So I want to talk a little about Nasdaq. Obviously, everyone knows Nasdaq is one of the world’s leading exchanges. But the organization is a lot more than that, in terms of, you know, technology solutions provider and things like where do things stand now, what’s Nasdaq’s position in the marketplace right now when it comes to providing technology and solutions?

Roland Chai  04:01

Yeah, so that’s I mean, we’re well known as an owner and operator of exchanges in North America, and the Nordics and the Baltics. So, so we run equities exchanges in those places. We also have a CCP Clearing House and in the Nordics that does fixed income, equity derivatives, and also commodities. And in the Baltics, we have CSDs and exchanges there. So aside from that, Nasdaq also produces quite a lot of technology. And we provide technology for a lot of other exchange groups and market participants around the world in futures and options, cash, equities, fixed income, we supply about 130 marketplaces in about 50 countries, from Latin and the Americas, North America to Europe, Middle East, and parts of Africa, as well as North Asia, Asia Pacific, all around those countries. So we provide training and matching technologies, the stuff that we run on our own exchanges weave supply that highly resilient technology. They’re also post trade has been growing. So CCP central counterparties and CSD central securities depositories, and then also risk technology to banks and broker dealers to manage volatility and market risk, stress testing, margin replication. So it’s quite a diverse and wide set of customers that we have.

Sean McMahon  05:28

Yeah, it’s I mean, it sounds like your background, also kind of from all points of the world. What I can say about technology and how it’s modernized markets is, you know, it’s made them bigger in terms of expanding access, but it also has made it smaller in terms of, you know, something that happens in one corner of the world definitely impacts everywhere else. So I want to get into that a little bit about the digital transformation of markets. So how have things changed? Not necessary throughout your career, but just say, in the last five or 10 years, how is the digital transformation change markets?

Roland Chai  05:54

Yeah. So in the 2000s, the rise of computers and digitalization and algorithmic trading, we saw that trend, latency became a lot of issues. So too, we produce ultra low latency trading platforms. And that that’s increased, I think the those kind of trends of technology driven API driven, automatic machine interfacing, and that’s accelerated on the pre trade side. And then obviously, on the post trade side, that’s taken a lot longer to catch up. But now we find automation quite a bit across the post trade landscape as well, I think the pandemic was almost an inflection point for a lot of volume, especially in the pre prep pandemic cycles. For example, we were looking at an order of magnitude of about 50 billion messages in North American markets a day, then it grew during the pandemic to 80 billion. And we’re now preparing our systems and scaling our systems to manage for the future, which is about 150 to 200 billion messages a day. And you can see that in a lot of the customers that we work with, both in their trading infrastructure and the post trade infrastructure for national exchanges and markets today, it can be quiet a lot of the time and then there’s there will be certain world events, certain interest rate decisions, wars, or certain commodity events, that will suddenly cause spikes in in capacity and that all the exchanges have to deal with. And that’s a constant obligation and duty that to keep the marketplace as open. It’s interesting, when you having worked on both sides of the fence in terms of working as a chief risk officer, but also running a clearing service and running a regulated business you. When you get to marketplaces, the one thing, especially in stressed scenarios is that having the national market open is really, really important. And having the ability and the resilience to keep the market running in stress situations is such an important requirement, especially for national infrastructure. And that those are the kinds of investments and conversations we have is about how do you produce things at scale and functionality at scale that works day in day out. And the second thing is the trading window. So when I started out in the late 90s, it was very much you had to start with the trading period and the close of the trading period. And in futures and options that’s traditionally been also been bridging quite a long, 20 hours of the day, you had your day session and your night session. And then the volume of connectivity went through. But I think what’s happened in last five years is also global connectivity for obviously, having passive investors and the growth of passive investing, investing in worldwide equities and worldwide markets. And also hedging that market, you see a lot more flows across borders and accessing markets. And a lot of that has pushed the boundaries of liquidity, and also trading cycles. And Kryptos. There’s also been a trend where that 24 By seven trading has pushed normal training to extend it out and not allow participation, price discovery and transparency in those markets as well.

Sean McMahon  09:26

Okay, now, you mentioned a couple of volatility events, right, the pandemic interest rate decisions, the war in Ukraine So, so what lessons have been learned about maintaining market resiliency through all those experiences?

Roland Chai  09:38

Yeah, so I think I mean, number one lesson has always been it never gets dull, right? And that sort of like post 2008 In terms of infrastructure, volumes would have been in a bit muted, but sort of the growth of derivatives and futures and options and actually, volatility especially The since the pandemic has picked up, you’d have events like GameStop, you had the Russian invasion, the energy crisis, electricity, those have created really, really tail events. And in risk circles, you look at standard deviations of volatility and the events of last three years, whether it’s pandemic GameStop, or the energy crisis has seen multiples inflections of risk over that. So I think the the increasing impact of that, as coupled with the increasing interest rate environment has been the liquidity that people have used to manage their positions on different exchanges, whether it’s futures and options or regulated markets, whether it’s OTC that has created a lot of alternative activity, and being able to manage your clients position your own positions, and also manage visa vie exchanges, clearing houses, the obligations, that’s become much more of a difficult thing. Also, I think the information cycle, in terms of events that’s happened is going back to the 24 hour by seven comments is when things happen as a risk manager and also technology, we used to worry about gap risk over the weekend. And also, what would happen on those days. But now, as the event cycle and information is being circulated a lot faster, it’s about how do you how are you able to react to use technology and platforms to be able to manage the different data points. And also, the market moves much much quicker? Because the data points come a lot quicker as well.

Sean McMahon  11:43

Yeah, so how do you manage that? I mean, I think, you know, right now, we’re still kind of in the middle of of, of what I would call like a mini banking crisis in the US was certain institutions have either gone under or been acquired. And part of the aftermath of all that is people are pointing to things like Twitter, and you know, other information where it just, you know, in seconds, billions of dollars can be moved out of out of the bank, just because everyone has information so fast. whereas years ago, it would take minutes, hours, maybe even a day, day or two, for troubling information to spread to all the investors. So as someone who’s kind of, quite frankly, tasked with managing exchange that has to handle all that trading activity, what are you trying to do to keep up with the speed of information?

Roland Chai  12:26

I think it’s interesting, when I speak to colleagues across the industry, in my peers, it, a lot of it is about getting the right type of information. And there’s a lot of signals in the market. And some of those signals are false, some of them are misleading, and the ability to process the right signals that impact your own risk appetite and your own position. And so part of it is not so much to absorb every single signal that’s out there. One part of it is yes, you need to be able to process it. But you also need to understand and have be very clear about what are signals that move the dial that what are signals that affects your position, or your investments, beyond all your customers investments across that, and then being able to a get access to the right information, analyze and process that information in the right timeframe, and then be able to action that information. That’s the biggest challenge that a lot of people have at the moment.

Sean McMahon  13:33

Yeah, you’re talking about, you know, managing those moments of extreme volatility. You know, I remember back in out onset of the pandemic, a lot of circuit breakers were tripped in trading for a couple of days there. Right. And, and folks who didn’t know the marketplace, or were kind of like, Oh, my God, they had to close the market. I’m like, Well, no, that’s how it’s designed. Like, this is how the market is supposed to function. But looking back on that now, are there any kind of lessons from that, that could be applied to maybe other other asset classes or other ways to kind of manage these events that because I think a few times, the circuit breakers were chipped multiple times, within an hour, you know, I think was seven seconds one time and things like that. So are you or other folks in the industry kind of considering tools like that, for where you wouldn’t close an entire market, but maybe a certain kind of asset class, like I said, or I don’t want to say individual stock, but you know, I’m saying like any kind of tools like that, just slow down all this crazy speed of volatility. Yeah, I

Roland Chai  14:24

think that’s a very good point. So on because if you take the electricity crisis during the war, the ongoing war that’s going on, especially in Europe, trying to have price discovery, like on the onset of the crisis and pre crisis, and ideally, we believe in futures and options and regulated markets that you have transparent lit books, where there can be price discovery, but often in those situations, especially if you’ve got algorithmics the prices get pulled right and if certain volatility is tripped The depth on the bit on the order disappears. Right? So one of the crisis during electricity is that with the severe volatility on a day by day or hour by hour, a lot of the electricity prices were just yo yoing. And the data points were scarcer, because a lot of people were not sure, in various regions in Europe about how to price electricity. I mean, we saw, I think, in 2020, a data point is I think, in the Nordic power future, it was a 40 euros per megawatt was the five year average price. And in 2021, it was going from 40 to 400, to 600. So you’re talking 1020 times, and that often would swing in in two or three day increments. So I think one of the lessons there is, is the question is, does the market know where the price is. And as you mentioned, circuit breakers and circuit breakers are a hot topic and that they’ve traditionally been put in but but some of their ideas behind circuit breakers is, okay, maybe the market needs a pause. And you may be need to think about it and take away the urgency of putting prices in and just process the information and therefore understand what the price is. So there is an argument to be said, whether it’s electricity or other asset classes is, is there something like circuit breakers that you’re able to put in there. And to a certain extent, we saw in Europe, politicians and government stepped in to guarantee prices, put price caps in and put subsidies in, which was basically to, to try and put controls in enterprises, and alleviate the concern. So I think having a pause or the ability to, in especially dislocated markets, to find price levels, that that’s really important. But the devils in the details now, I’m not sure how regulators and and when you look at the international bodies, and the regulators is, is how do you design the right mechanism? That’s fair, because obviously, the flip side of the argument is, if you put in a pause, if you’ve got a position, you can’t get out of the position. So it’s always a trick about, okay, if you if you put in a hold, that’s great for people to consider whether they want to go in the market, but it also means that it creates a stressful situation for those with positions in the market who want to get out or want to hedge. So it’s a difficult issue. But I think more discussion about this, and how those these mechanisms can be useful would be better.

Sean McMahon  17:43

Okay. And what other ways is the digital transformation creating challenges for market participants?

Roland Chai  17:49

Yeah, so obviously, on the trading side, there’s been speed algorithmic trading, and it’s been a race arms race for latency. But also, I think what I’m what’s come out of that is, is proliferation of standards across securities, so equities and bonds, and movement of those securities, but also digitalization of those securities. I’m not talking about digital assets, or tokenization. But what we’ve seen de materialization happened 2030 years ago, that much CSDs, but it’s about how to how to move positions, inventory, and also price signals electronically, and how markets interconnect electronically. So I think that digitization is, and that movement is always a challenge, that part of it is also about technology, using technology to lower the barriers of entry, and also to modernize market structure. So how do you attract liquidity? I think digitization and also, technology API’s have done a massive amount to do that standardization of API’s, I know, across futures and options industry has been massively helpful to lower the cost of entry so that each market doesn’t have a different way of doing things. I think, overall, the introduction of cloud and cloud is starting to get in. So Nasdaq has moved one market to the cloud. And we sort of see adoption of cloud, whether on our side as market infrastructure with banks and brokers is increasing. And I think that helps with resiliency. And what we were talking about for in terms of having really extreme points of stress and capacity of trading, going out that’s very difficult to manage with fixed infrastructure cloud gives you a certain elasticity, that’s able to do it. And then if you look at what’s ahead, whether you look at the challenge of artificial intelligence or machine learning, all of that is dependent on having a huge amount of processing power and data. So it’s about being able to put those workloads in into Cloud out. So those are some of the kind of challenges that as those technologies grow as well, how do we get past capsule markets, move them up the curve, and modernize markets while doing it safely and resiliently as well.

Sean McMahon  20:14

And you touched on artificial intelligence. Obviously, that’s a hot topic right now generative AI with Chet GPT, and things like that. So considering it’s in the headlines now, we’ll we’ll call mainstream media, but it’s been in the markets for a while, at least the AI has, right, the underlying AI. So how has that already reshaped markets? And then how do you think it will continue to in the next few years as the technology appears to be advancing quite rapidly?

Roland Chai  20:37

I think you raise a good point it has been in markets, like when we look at examples, and especially I mean, from my experience in Asia as well. There’s been a number of brokers using AI, for example, quantitative funds using AI and machine learning to help with information arbitrage and take positions to obviously, things like natural language processing, being used in understanding and processing signals, as well as Robo advisory, for example, I’ve seen brokers like probably at least a year or two years ago, starting to generate AI portfolios. So have a trading portfolio that will generate returns for you and self manage, obviously, on the investment side, you’ve seen that come through. Now, what we’re seeing in the market is, we’re coming out with using AI to look at options strikes, for example, rather than every time, we have options, listing a whole set of strikes, using AI and machine learning to understand, okay, which in the money at the money strikes, based on previous behavior, what are the likely strikes that are going to be have depth and liquidity. And rather than listing a whole wide band, we use AI to reduce that list and be able to manage more efficiently how many strikes we put on to also using AI to look at, okay, if we have certain orders, we’ve got something called a dynamic mellow order, which is a limit order, which has a variable length of time because it processes over 100 data points, to understand how long it will stay in the market based on different signals in there, and it will expire at a dynamic time. So little things like that, where you can see applications of that that is already been used in the markets. On the risk management side, we see machine learning being able to help with stress testing and back testing, and processing huge amounts of data to ensure that margin methodologies are correct. So all of those applications are there. But I think in terms of transformative, I think that we still need to see how markets can harness that. And I think to a certain extent that technology is out there, it’s a question of who uses it and how the evolution happens. I think it’s very difficult to stick your head in the sand and say, Okay, this is something we don’t understand. And therefore we’ll ignore, I think you have to manage it safely. But I don’t think you can ignore it at the moment.

Sean McMahon  23:16

And I want to get to you know, how these programs are written, right? You mentioned earlier how the price of energy in the Nordics jumped from 40 to 400 or 600. Right. So a lot of these programs are written using previous data. So yeah, how do you manage the risk of that program suddenly being presented with a data point that is so far out of the bounds of what it had been written to consider?

Roland Chai  23:39

Yeah, no, that’s a great question, Sean, when you look at your classic Value at Risk methodology, and it basically if you take historical simulation, you look have a look back period of five years. Now, the classic would have been, if you’d run the portfolio prior to 2008, you wouldn’t have predicted 2008. And so therefore, you would have been terrible what what historical simulation and those back data data is not good at is predicting tail events and tail risk on that kind of thing. So as you said, if you’ve never come across a situation, how you do tell events. Now, a lot of the methodologies and the models are used, whether it’s Monte Carlo or predictive ones, it’s about how you how you input that model. So I think a lot of it is how you design it, a model is only as good as the design is in there. And if the person who designed it is never thought of the possibility of that event, and the model is going to be quite reactive, and potentially quite procyclical, right, but you can put measures in about how you control that. And also, you can use technology to look up predictive analysis and also open a universe of potential outcomes. And actually, that’s where software can be quite useful. or is because if you if you are a human being and trying to work out, okay, what’s all possible permutations of electricity prices, for example, and the possible outcomes, it would take us a long time. But if you harness artificial intelligence or compute to do that, then you can generate a much better coverage and understanding of that. But it comes down to how much he designer and the smarts that you put in that, but it’s also about discipline and rigor. So I think it’s about control as well.

Sean McMahon  25:30

Yeah, I think I like the point made about the folks designing it, and how they have to be able to, quite frankly, imagine what could happen because not only you know, we talked about the price of energy going up in the Nordics. But I also remember the price of oil going negative, you know, tip my hat to any of the AI designers who realize that could happen.

Roland Chai  25:47

Yeah. And we’re seeing that in climate as well. So Nasdaq, we produce catastrophe models for insurance companies, so flood, and earthquakes and cyclones as well. And that that area of the industry as well is completely changed. Because everyone’s, as you see in North America, or Europe or Asia, the amount of velocity and the change in speed, which temperature and also, weather events have completely broken out, those models are constantly updating. And it’s almost like you have to, especially for the insurance company, it’s such a critical component of is to understand, okay, a once in a lifetime cyclone event in Florida has now become something that happens every three years with the same velocity and damage. Right.

Sean McMahon  26:41

Okay, that segues to my next question, you know, your comments about expanded activity by Nasdaq and insurance markets. So what other areas is Nasdaq focusing on right now that might not come top of mind because you know, someone who’s listening to the show,

Roland Chai  26:53

at the moment, we returned, looking at digital assets custody. So we have a digital assets business that we’re going through subject to regulatory approval from the New York Department of Financial Services, and that will go go live at the end of q2, subject to their approval, this is a house new service for Bitcoin, that we will release in the US jurisdiction. And that’s something new. And that’s come from a place from the market where obviously, we’ve seen the rise of crypto in the crypto winter and that, but a lot of clients and stakeholders in the market came to Nasdaq and said, Hey, can you get involved in this market? Given our reputation, our brand, in terms of being a financial market intermediary? How can we lend our expertise in that space? So that’s, that’s coming alive, we are working with one Latin American market about digitizing bonds, central government securities, and that that works kicked off and that should go live early 2024. And that will take government bonds and in a way tokenize them onto a platform and allow them more readily to do that. We’re working with a payments company called finality, where we’re looking at starting with Sterling and having a DLT platform on the payment side. So one thing is securities, but it’s also digitization of payments. And then obviously, there’s there’s various experiments with central banks that are going through there. And then on the carbon side, we we have a majority ownership of a subsidiary called puro, which is in carbon removal. So they run standards and and also a carbon business. And we’re actively partnering with a number of carbon initiatives, where we’re also creating a registry for carbon tokens as well. And that’s interesting, because that’s a new asset class, whether you call it commodities or where it fits in quite in the taxonomy. I’m not sure, but it is sort of a brand new look at it. And since cop 26, and cop 27, you see a lot of national government standing that up. And then looking at do they use financial markets infrastructure to do that? Or do they use a totally new platform technology set to do that?

Sean McMahon  29:13

So you’re talking about tokenizing, carbon markets and offsets and things like that?

Roland Chai  29:17

Yes. So So basically, we will produce for puro, we’re building the registry of DLT registry, and then we’ll have tokenized carbon credits on that. And that’s really interesting, because it’s whitespace asset class, right? There’s no infrastructure for that at the moment. But it also highlights I mean, when you look at the way the capital markets were designed, they probably grew up in each marketplace slightly different. And then we had standards bodies like Fia, or is, and then Isa, which is the international security standards, we’re all trying to say, Okay, let’s come up with a common standard. Whereas with something like carbon, which is a brand new asset class, you start saying, Okay, well, why don’t we do The standard way to start with rather than proliferate all these individual marketplaces in each country and then do that, so a lot of work is going on trying to generate standards for those as well.

Sean McMahon  30:12

All right, well definitely sounds like Nasdaq’s got its hands and all kinds of markets and data market technology development. So, Rowan, I really appreciate your time today. This has been a great conversation. Thank you.

Roland Chai  30:23

Okay. Thank you, Sean. Real pleasure to be with you today.

Sean McMahon  30:30

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