Every month, The Big Question video series brings together a panel of Chicago Booth faculty with industry experts for an in-depth discussion. This is an edited excerpt from October’s episode, in which John C. Heaton, Joseph L. Gidwitz Professor of Finance and deputy dean for faculty; Tobias J. Moskowitz, Fama Family Professor of Finance; Eric Budish, associate professor of economics; and Stephen Brodsky, CEO of Spot Trading, analyzed the effects of high-frequency trading on financial markets. The discussion was hosted by Hal Weitzman, Booth’s executive director for intellectual capital.
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Hal Weitzman: Flash crashes, exchange shutdowns, incorrect orders, and algorithms gone wild. Technology has completely transformed financial markets, and not always in a good way. For many, the culprit is high-frequency trading, the practice in which black boxes automatically send orders to buy and sell at lightning-fast speeds, and firms and exchanges compete by buying ever-more expensive technology to trade faster and faster.
High-frequency trading now dominates the equity markets and is growing in the derivative sector, a trend that concerns many observers. Regulators in Washington fret about a race to the bottom in which speed is more important than risk management. But is more regulation really the answer? And if so, should it be directed at high-frequency trading or at the overall structure of markets?
Welcome to The Big Question, the monthly video series from Capital Ideas at Chicago Booth. I’m Hal Weitzman, and with me to discuss the issue is another expert panel.
John Heaton is the Joseph L. Gidwitz Professor of Finance and deputy dean for faculty at Chicago Booth. An expert on asset pricing, portfolio allocation, and time series econometrics, his teaching focuses on the practical problems facing investors and institutions.
Toby Moskowitz is the Fama Family Professor of Finance at Chicago Booth, an authority on asset pricing, portfolio choice, risk sharing, and market efficiency. He also knows a fair bit about the business and analytics of sport, which is showcased in his best-selling book, Scorecasting: The Hidden Influences behind How Sports Are Played and Games Are Won.
Steve Brodsky is the chief executive officer of Spot Trading, a proprietary trading firm that specializes in equities, equity options, and futures. He was formerly president of the parent company of the Chicago Stock Exchange, the exchange’s chief financial officer, and a managing director at a private-equity firm.
Eric Budish is an associate professor of economics at Chicago Booth. A former Goldman Sachs analyst, he researches auction and matching markets and the design of market institutions.
Panel, welcome to The Big Question.
I want to start by deciding what we’re actually talking about. Toby Moskowitz, let me start with you. What do we mean when we say high-frequency trading?
Tobias Moskowitz: Well, that’s a good question. I think what I think it means is, like you said in the opening, algorithmic trading at incredibly high speeds. Now with technology, that’s become in milliseconds. Previously, it would have been on the order of minutes or seconds.
But I think the idea is that they’re essentially creating markets, something we’ll probably talk about later. But I think that’s what people mean by high-frequency trading. It’s just the speed of getting in and getting out at lightning-fast speeds.
Hal Weitzman: OK, and when we say lightning-fast speeds, Steve Brodksy, you’re actually in the industry. How fast is lightning-fast?
Stephen Brodsky: Very, very fast. We are talking milliseconds to microseconds. I do believe at some level, though, just in the nature of trying to define it, it’s become so pervasive in the marketplace that at some level, the market has moved a bit past the debate. I mean, the tools that we’re, I’m sure, going to talk about today, if you’re a large market maker, a large proprietary trading firm, these technologies persist throughout your organization. It’s part of being in the industry.
So to talk about, to try to define it as any one strategy, I think that’s where people have difficulty. It’s more of a technology. It’s a technique. It’s really the way the markets function.
Hal Weitzman: It’s not a trading strategy per se. It’s just the technology that uses the speed–
Stephen Brodsky: That underpins the marketplace, certainly from a liquidity-providing perspective.
Hal Weitzman: OK, and that’s important when we discuss who’s to blame for particular problems in the market.
Eric Budish, how important is high-frequency trading nowadays to financial markets?
Eric Budish: So high-frequency trading is commonly attributed as constituting more than half of volume across a wide variety of markets.
So data’s a little bit hard to come by. GetGo, which is a Chicago-based high-frequency trading firm, recently had to file public documents with the Securities and Exchange Commission. So you can get a detailed glimpse of one firm.
And they alone constitute a 5–10 percent of volume across a wide variety of asset classes, stocks, currencies, bonds. And just to Steve’s point, I would argue that high-frequency trading firms . . .first of all, they’re trading at incredibly fast speeds, at lightning-fast speeds. So put it into context, blinking your eye is 400 milliseconds, so four-tenths of a second. So when we’re talking about milliseconds or microseconds, which are millionths of a second, we’re talking about unfathomably small amounts of time. And they’re also sophisticated information technology firms.
And when we think of developments in financial markets over the last few decades, there’s a lot of evidence to suggest that the developments in information technology have benefited fundamental investors in lots of ways, that IT has been very healthy and very good for the function and performance of financial markets. But some aspects of the speed race, and I’m sure we’ll discuss this in our discussion, the speed-race component of high-frequency trading, right? I take your millisecond . . . take your millisecond latency and try to be just ever-so-slightly faster than you, I’ll argue will have some negative consequences.
Hal Weitzman: Let’s talk about how it’s changed the markets, then. John Heaton, what effect has this ever-fasting trading had on the markets?
John Heaton: Well, I think that’s open to debate, frankly. We’ve certainly seen an increase in liquidity in the markets in the last many decades.
Hal Weitzman: So that’s just more orders coming in.
John Heaton: One argument is that the high-frequency trading is part of it, but it could be just the increase in technology. So if we just define high-frequency trading as use of technology, then almost by definition it’s had a massive impact in the markets, in terms of increasing liquidity.
So I think it’s open to debate whether it’s had a major impact on liquidity in the markets, per se, independent of the technology itself.
The other thing in terms of thinking about size, if you thought about fees or profits in the trading environment, standard mutual funds would dwarf this industry many times over. So in terms of importance in developments, I think it’s open to debate.
Hal Weitzman: So we shouldn’t exaggerate it.
John Heaton: We shouldn’t exaggerate it.
Hal Weitzman: One of the claims or concerns that’s been raised is that exchanges are forever sort of pandering to high-frequency traders. building expensive facilities where they can locate their black box computers right next to the exchanges, match an engine, and get the fastest possible trading times, and that kind of thing. The allegation being that there’s sort of a two-tier market. The high-frequency traders have privileged access, either to information or to certain kinds of trades, and the sort of mom-and-pop investors are left out.
Steve, how is that criticism viewed within the industry?
Stephen Brodsky: I think it’s important to acknowledge where we’ve come from. We can’t look at the technology developments isolated from the regulatory developments. All of this came out of an environment where you’ve had a specialist system, a floor-based exchange model. You had very little transparency into what was going on in the marketplace. You had high fees. You had slower turnaround times for the retail investor.
All of these things were in place when these changes occurred. So I think it’s important to have that in mind when you start talking about things like co-location. Firms co-locate in exchange facilities to be near the servers to generate the types of latency that we’ve talked about.
Hal Weitzman: And they pay huge amounts of money for the privilege.
Stephen Brodsky: They pay . . . and what’s different about it today than certainly years ago, I could have gotten the same privilege 10 years ago if I paid $2 million for a New York Stock Exchange seat. And I would have been limited in terms of my access at that point. What occurs today is if, yes, you are willing to invest in technology, the exchange, by rule, has to treat everyone equally, and this is important also when we talk about co-location.
For opponents of co-location, if you remove it, all that’s gonna happen is that the most valuable piece of real estate is gonna be the person who owns the building next door to the exchange. So I think the good thing about the way it’s structured today is it’s regulated. People have . . . the exchanges are responsible for making sure that it’s fair across members. And fairness isn’t necessarily that everyone gets the same . . . everyone has the same opportunity to, or guarantee of making the same amount of money. Fairness is about access and making investments.
And it is no doubt expensive and part of the business model, but it’s fundamentally different than it had been many years ago. So to look at it in isolation I think is a little bit flawed and I think it’s important to acknowledge why we’ve come to where we are today.
Hal Weitzman: Toby Moskowitz, are the markets better today than they were before we had this technology?
Tobias Moskowitz: You know, again, it’s hard to say. You can make arguments in either case. I mean, one argument saying that markets are better because of this is liquidity may have improved. I don’t know if that’s caused by this kind of trading or a consequence of technology and improved liquidity.
And there’s some evidence to suggest that maybe that’s the case. But it’s also the case that maybe it causes other problems. And I think, for instance, some of the work that Eric’s been doing is just scratching the surface on some of these issues. And I think before we have any policy debates about this, there’s an awful lot of evidence that we need to gather. We don’t know much about it yet.
Well that was a nice segue into Eric Budish’s research because, Eric, you’ve recently put out a paper about high-frequency trading, about the markets that enable this kind of technology to flourish and be successful. So give us your kind of judgment on whether the markets are better now than they were in the past, and if there are any downsides.
Eric Budish: Great question. So first thing’s first. To Steve’s point, no nostalgia for financial markets in the 1990s or, more generally, pre the IT revolution, pre the information-technology revolution.
That said, my research suggests that current financial-market design is flawed in an important way. And that flaw is that trading occurs in continuous time. What I mean by continuous time is that investors, algorithms can trade at literally any instant of the trading day, from the time that markets open at 9:30 in the morning to the time that markets close at 4 o’clock in the afternoon.
And continuous-time trading is problematic for two reasons. The first reason is that continuous-time trading builds in a speed race. When trading is in continuous time, any time there is a news event—so if the Federal Reserve announces it’s not gonna taper bond purchases, or some stock price goes up and that has implications for other stock price—any time there’s a news event, market participants are gonna race to react to that news event.
And if I react a millisecond or a microsecond or a picosecond faster than you do, I win the right to trade on the basis of that information. So number one, continuous-time trading builds in a speed race. And then number two, my research shows that the speed race has a lot of negative consequences for fundamental investors.
So we can go through this in some depth if you like, but the speed race, number one, we show that it harms fundamental investors in reducing liquidity. Number two, we argue that the speed race is destabilizing for financial markets, makes the markets more vulnerable to events like the Flash Crash or the Facebook IPO debacle. And number three, and put this off to a corner if you like, the speed race is bad PR. It makes financial markets look bad. It might undermine investor confidence. That might also be important from a regulatory perspective. Although, I would put that after liquidity and stability in terms of importance.
Hal Weitzman: OK, let’s get into those in a little bit. Just let me press you on those two points just very briefly. So the markets are more volatile because of the kind of trading environment that we have, is that right?
Eric Budish: Algorithms acting at millisecond or microsecond speeds is potentially destabilizing for financial markets. So when I think of volatility, I think: Are stock prices on a day-to-day basis moving around a lot? When I think of stability, I have in mind extreme events like the Flash Crash or when NASDAQ’s computers couldn’t . . .
Hal Weitzman: Went down.
Eric Budish: Went out for three hours this summer, or couldn’t keep up with the surge of orders during the Facebook IPO.
Hal Weitzman: So the stability of markets is affected by it.
Tobias Moskowitz:I think that the issue’s not . . . I mean, Eric’s research I think does show some of that, but I think, generally, the evidence is not quite clear. We had a student here last year, Brian Weller, who was working on this in different markets, in commodities futures. And there, what he found is actually flash crashes typically occur in the absence of high-frequency traders, than when they’re removed from the market. Now I don’t know whether you want to blame them for that as well. It’s hard to blame them for being there and causing things as well as when you remove them, they cause things. I think they are unpopular politically.
Hal Weitzman: But actually, isn’t that the point? Because in the old system, bad as it was, there was always a market maker who’s forced to make a market, even when things were disastrous.
Tobias Moskowitz: There’s also a second side to this, which is maybe, even if we do blame them for some of these rare events, and I’m not sure that’s even clear, the question is are there other benefits on the other side?
So for instance, you may be willing to tolerate the occasional additional flash crash, if most of the time, 99 percent of the time, you get better liquidity, maybe less volatility, maybe all kinds of other things that we haven’t quite documented across all these markets. So I think the issue is open to debate.
Hal Weitzman: John Heaton?
John Heaton: Yeah, I was just gonna say very similar things to what Toby was just saying. I mean, I just wanna talk about Eric’s work. Eric is one of my colleagues but independent of that, it’s a wonderful paper. And it does point out these potential problems with continuous trading.
I would be a little careful, more careful than Eric, about saying the magnitude of the effects that he’s finding. I think that’s open to debate. Certainly, I think we need empirical evidence. What’s interesting is that we might see exchanges experimenting. So for example, there’s private foreign exchange markets that are doing not exactly what Eric wants. They are doing some batch processing of orders.
The other interesting part in Eric’s paper, by the way, is beyond just limiting trading is coming up with the appropriate mechanisms designed—
Hal Weitzman: Right, so let’s come to that.
John Heaton: Which is a really interesting part of what he’s coming up with. What they’re doing is just randomly assigning ordering within batches of time. It’ll be interesting to see what’ll happen in those markets as we add these different features.
So I think an interesting . . . we’re gonna talk about regulation at some point. An interesting thing would be to allow the markets to experiment and to see with these different mechanisms. I think Eric has an interesting one to try.
But I’d be careful about magnitudes. I agree with Toby, we have to be a little careful before we draw too many conclusions from this one piece of theory, however good it is.
Hal Weitzman: Eric, I’ll let you come back on that.
Eric Budish: A couple of points I’d like to make. Number one is, is I wouldn’t . . . I think of continuous trading as the culprit, not high-frequency traders as the culprits.
So a lot of the public-policy debate seems oriented around a debate of whether high-frequency trading is good or evil. I think that’s the wrong debate. The debate we should be having is whether continuous-time trading is the right market design.
Number two, on magnitudes, our work does get at the magnitudes for one piece of the puzzle, and I think with millisecond-level data directly from exchanges, where what we are able to document empirically is the amount of money at stake in the arms race for particular kinds of latency arbitrage trades.
Hal Weitzman: Hang on, so tell us what you’re saying about latency arbitrage trades, just explain what that is.
Eric Budish: So say there are . . . say there are two securities that are very highly correlated to each other. So in the paper, we use two securities that track the S&P 500 Index, one of which trades in Chicago and one of which trades in New York. Now, to the human eye, these securities’ prices are gonna move almost in perfect lockstep, which they should, because the securities are very highly correlated to each other. They track the same index.
So to the human eye, the securities’ prices go roughly like that. But when you zoom in to the high-frequency-level data, so to millisecond-level data that we purchase from exchanges, the price path is a lot choppier. Really, prices kinda go like this, where one security’s price moves and then the other security’s price—
Hal Weitzman: And traders can make money from that anomaly there.
Eric Budish: And that’s the key is that this choppiness creates arbitrage opportunities, where if the prices are supposed to go like this, but really what happens is first this one moves and then this one follows, there’s a momentary arbitrage opportunity, buying the cheap one and selling the expensive one. And there’s a lot of money to be made from those kinds of arbitrage opportunities.
So in our paper, we show that for this one opportunity alone . . . so S&P 500 arbitrage between a futures contract that trades in Chicago and an ETF, and exchange-traded fund, that trades in New York, the annual sums at stake are on the order of $75 million. And that’s just one pair of securities that’s highly correlated.
Of course, if you teach a finance class, the correlation structure of the market is the very foundation of asset pricing theory. Correlations are everywhere, and this is just one example of a pair of securities that’s correlated. So I grant that that’s one number, but it’s suggestive of large sums of dollars at stake.
Hal Weitzman: Steve Brodsky?
Stephen Brodsky: Couple things on that. First of all, I enjoyed the paper. I’m the only one who’s not a professor here, but I enjoyed it nonetheless. And I do appreciate the fact that, exactly as you said, it was an analysis based on not the right or wrong of one type of liquidity versus another, but, simply, is the market structure correct or optimal?
Just a couple of points. I do think the fact that arbitrage exists is, that’s just a reality of whenever you have two products, two correlated products trading together, and that’s the role that liquidity providers play. The reason an S&P 500 Index ETF is a product that’s marketable is because there are firms out there who are compressing that arbitrage opportunity.
So there is a utility to that function and it will always exist in various forms. It happens to exist today in a low-latent capacity.
Eric talked about the continuous markets. That’s a function of just competitive markets in and of itself. We have 13 or 14 exchanges. We have multiple dark pools. We have an environment where a good idea will be backed by investors, order flow providers. There are ways to express, certainly, all these types of models, which are being experimented with in various forms.
The complication is that when you have these competitive markets, and you’re trying to design a system where you say, this market in now locked up for a period of time, be it a second, whatever increment, to the extent it’s slower than the increment that the other markets are trading the same product, it complicates things for firms like ours.
I am, to the extent that we were able to all lay down our weapons and no longer engage in the arms race, I am the first one at the peace table. The reality, though, is that we’re competing against other firms who won’t. That gets to your prisoner’s dilemma. And there will always be markets that cater to those type of firms. So we’re constantly locked in this competitive battle.
I think that’s a good thing. I think the competition has created tremendous choice for investors, including, ultimately, the retail investor. So I’m a proponent of that. My struggle is just how, say, an auction or a break of the continuous market would function in that ecosystem.
Hal Weitzman: I understand. Well, Eric, seeing as we’ve sort of obliquely referred to it several times, let’s talk about what you think the solution is, the “peace at last” that Steve referred to. Tell us a bit about your alternative to the current continuous market.
Eric Budish: So we’re proposing that financial exchanges, instead of using a continuous-time limit order book, which is the predominant market design today, use what we call frequent batch auctions.
And a batch auction is a very standard auction that actually has its roots in work by Milton Friedman 50 years ago in the design of Treasury auctions. And we’re proposing that batch auctions be conducted at very frequent but discrete time intervals, such as once per second or once per hundred milliseconds.
So the market structure we’re proposing is that for each stock or for each, each futures contract, each foreign exchange contract, etc., once per second, there is an auction to determine the price for that stock. And in the auction, investors submit bids and asks, desire to buy, desire to sell. Market-making firms also submit bids and asks the way they currently do in the limit order book system, and the market clears where supply meets demand.
Hal Weitzman: Gathers up all those orders and every second it—
Eric Budish: Exactly, it gathers up or batches a full second worth of orders, then computes based on that second of activity, where does supply meet demand? And then anybody that’s willing to pay more than the market-clearing price, or sell for less than the market-clearing price gets to trade at the market-clearing price. It’s a uniform price.
Hal Weitzman: So what problems does that resolve?
Eric Budish: So batching solves two problems. One benefit of batching is that by moving from a continuous-time design to a discrete-time design. So from continuous to once per second, you eliminate the incentive to spend substantial amounts of money on tiny speed advantages.
So to Steve’s point, you’re solving the arms race. This would save Steve a lot of money in the sense that he wouldn’t have to spend substantial resources to be a millisecond faster or a microsecond faster than he was yesterday.
Tobias Moskowitz: It’d probably cost him more money.
Eric Budish: Well, we can debate that. I think that’s an interesting debate.
Hal Weitzman: So let’s just put . . . Toby, what is that concern there?
Tobias Moskowitz: Well, no, I was just saying that there’s a reason Steve wants to spend that money, right, which is he’s presumably making more than it costs. So it’s gonna cost him more than it’s gonna save him, and other people like him.
Stephen Brodsky: Maybe there are two, I think, critical points. I mean, that feature of trading today has become more commoditized. There are more firms able to spend money on this type of technology. There’s just a limit to how far this can go, and you described in your research, you hit a plateau.
And then, really, it’s just a zero-sum game between market makers. And I think that’s evidenced by, you see firms like GetGo who made significant amounts of money several years ago. Now you can publicly see, really, they’re the one of the representative firms losing money.
Where when things are moved from my perspective, are how do you apply the technology to other things you do well, be it analytics, be it valuation, be it access to customer-order flow, if it’s providing liquidity to customers. Those kinds of things.
Hal Weitzman: So is your point that there would still be a technology arms race, just in different areas?
Stephen Brodsky: In my mind, if you look back time immemorial, there’s been this tension between market-maker rights and obligations and speed. If you wanna slow things down, you give market makers certain levels of benefits. A specialist, you get to see every order that comes to the exchange. A market maker, you get to participate in a certain number . . . you favor one participant versus the other, that will slow it down. That will bring stability to the marketplace. But at a cost, be it transparency, be it explicit cost.
Hal Weitzman: Eric, just to be clear, who would actually institute this rule? Would it be regulators? Should it be the exchanges themselves? Who do you envisage would put this in place?
Eric Budish: So the cleanest way to implement this would be via a regulator, such as the Securities and Exchange Commission. And I’m not a pro-regulation or antiregulation guy. The current market structure is a product of regulation.
And I would argue that frequent batch auctions is a smarter regulation than the continuous-time framework that’s currently the product of regulation. But this is still a regulatory intervention in what is a freer market, right, John Heaton?
John Heaton: The reason you need a regulatory intervention is to allow coordination across markets. Because if one market does this, you could see a migration to another market.
I mean, another interesting issue of coordination is across securities. I mean, something . . . we all talk about liquidity, but really when we’re talking about the high-frequency trading, it’s mostly in large cap stocks, what we really think as very liquid stocks. I’m not exactly sure how this mechanism helps or hurts, say, for someone who wants to trade in small cap stocks. And how to coordinate the auctions across the stocks would be an interesting thing. I’m not sure if Eric’s thought about it. I think he’s thinking about it. It’d be an interesting situation.
I mean, I am the last person to advocate regulation, but to implement what Eric has in mind, I think you would need, you know, a national regulatory body to implement it.
Hal Weitzman: Toby Moskowitz, would that be a step forward in your mind if we regulated to batch auctions in this way?
Tobias Moskowitz: Again, I’m gonna take the cop-out, which is it depends. I think we’re still gathering new evidence. I think Eric in his paper has some very good arguments. I think, you know, that may be a better system. I kind of like what John was saying earlier, which is it’d be nice to let the exchanges experiment a little bit. I think Eric’s proposal is extremely interesting, and I think it does solve some potential problems.
We don’t know, necessarily, what the unintended consequences might be. This would be a way to find out. I think if we let the exchanges experiment a little bit, that would be terrific.
Hal Weitzman: That’d be better than having it imposed on them? I think, you know, any . . .
Tobias Moskowitz: Well, at least for a while, right? Let’s try some different things. I think that would be interesting.
Eric Budish: So, just to Toby’s comment, two things: one is that there are current regulatory impediments to exchanges experimenting with frequent batch auctions. Frequent batch auctions would potentially be in conflict with a regulation imposed about 10 years ago by the SEC called National Market System, or NMS, which imposes continuous trading, or implicitly assumes continuous trading.
So number one is there are impediments to exchanges experimenting with this idea. And number two is I’d like to see individual companies, so listed companies be able to elect for frequent batch auctions over the current market structure. A lot of . . . I’ve heard industry participants say that they hear CEOs of listed companies say, “My stock trades in a casino. Why does my stock need to trade at a millisecond?”
Tobias Moskowitz: They also complain about shorting.
Eric Budish: They complain about all sorts of stuff. But I like the idea of giving listed companies the—
John Heaton: “Why does my stock go down?”
Eric Budish: Yeah, “Why does my stock go down?” Sure. So I like the idea of allowing listed companies to elect a different market structure, but the current regulatory environment would prohibit that. There’s a regulatory assumption in favor of continuous trading. It’s as if the regulation assumes that retail and fundamental investors, what they really want is immediate execution.
Hal Weitzman: I wanna come to Steve. Is this the peace that you’ve been praying for?
Stephen Brodsky: I do think that what I’m struggling a bit to reconcile in my own mind, and again, I preface it by saying that I would like it to work, is that the second you have two market models trading the same security, or a heavily correlated security, you inevitably inject race and speed into the equation.
So if the goal is to eliminate that as an input therefore all of us can invest more in providing liquidity, and therefore, either narrowing spreads or increasing depth, I’m not sure it gets there unless there’s a very large regulatory mandate. And I’m talking about a central limit order book for every correlated product.
Hal Weitzman: And presumably, that would have to be international as well, wouldn’t it?
Stephen Brodsky: Certainly, you could start small and just do, say, the products that you studied in your proposal where you have an SEC-regulated set of equities, a CFTC-regulated set of futures who are heavily correlated, actively arbitraged, and really subject to the arms race that you described. Unless they’re trading on the same platform, and that would involve getting into the corporate structures of both the Chicago Mercantile Exchange and the New York Stock Exchange. That’s a complexity. That’s a really big hurdle.
My concern would be unless you’re willing to go all the way to that, which I think is a difficult process, I’m exposed to being held up in an auction.
Hal Weitzman: Alright, Eric, let me give you the final word, very briefly.
Eric Budish: Thank you. So, to Steve’s point, if I can bring this debate with my research to where a panel of experts says this is a good idea. We agree that continuous-time markets have problems and that frequent batch auctions is a good idea in theory, but there is regulatory complexities with implementing that idea, then I’ll consider that a tremendous victory as a research paper.
Hal Weitzman: OK, wonderful. I hope today we’ve at least started to do that. But unfortunately, on that discussion of speed, our time is up.
My thanks very much to our panel: John Heaton, Toby Moskowitz, Steve Brodsky, and Eric Budish.
For more research, analysis, and commentary, including much more analysis of Eric Budish’s work, visit us online at chicagobooth.edu/capideas. And join us again next time for another The Big Question.
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