Audio Interview – Peter Kovac on High Frequency Trading – Market Making, Profits, Front-Running

I recommend listening to the audio version of this interview…It’s the best part!

 

Michael:          Hi, my name is Michael, and I used to be a hedge fund manager.

Peter:              My name is Peter Kovac, and I’m the author of Flash Boys: Not So Fast.

Michael:          Flash Boys: Not So Fast came out recently on Amazon[1] and is of course available, and is a response to Michael Lewis’ book named Flash Boys in which I’d characterize you as disturbed enough by his version of high-frequency trading or algorithmic trading to try to correct the record, which you have done, and I have reviewed. I just thought it would be interesting if we could talk through some of the issues.

I’m assuming for the purposes of this that people are familiar with the broad outline of Flash Boys. The hero of Flash Boys is this guy Brad Katsuyama and he doesn’t end up as a hero in your retelling. I describe him – kind of paraphrasing your words – as he’s either a dupe for not really understanding how equities trade in 2012, or he’s mostly a salesman. Is this a correct characterization of your view of him, or am I being overly aggressive?

Peter:              Michael Lewis kind of channeled the entire story of Flash Boys through him. And so I’m really responding to the way that Lewis has portrayed Katsuyama. In Lewis’s portrayal, it does kind of seem like he’s a dupe. He seems like the guy who is the head of a major equities desk,  yet apparently is unaware what the fee structure is across the market and he has to Google it. He makes very large trades that have huge price impact on the market, and then is unable to explain them. So it really seems to me like it is Michael Lewis who set him up this way and I’m just responding to how he’s been portrayed in the book.
Michael:          Okay, I’m not an equities guy, so I learned stuff from both Michael Lewis’s book about how the equity market does or might work, and I learned stuff from your book about how the equity market does or might work. I’m assuming lots of people listening to this know even less than me. But what’s the traditional role of a guy like Katsuyama or a legacy Wall Street equity trader? Can you describe that a bit before we get to what is “algorithmic” or how HFTs or high-frequency traders get involved?

Price Impact

Peter:              Sure. Let me describe specifically the role that Lewis has put Katsuyama into here, which is to take a large order a client has, and the client says this order is too large for me to handle myself. I don’t have the specialized expertise. I don’t know how to put that order into the market, and not create a huge price impact. Price impact is a really fancy way of saying what you learned in Econ 101.

In Econ 101 you learned that if you have a big change in supply or demand it’s going to affect the price. And so if you have a really big order you want to place in the market, obviously if you’re going to be selling a lot of shares, the market is going to drop in price as you’re selling those shares. If you’re buying a lot of shares, the demand is increasing and the market is going to go up.

If you aren’t doing this every day of your life, there’s a chance you’re going to screw it up and not do it as well as it could be done. The function of a trader like Katsuyama in Flash Boys is to take some institution or individual’s large order, and as Lewis says, work on it for hours in the market to try to put a little bit of it out now, a little out later, trying to minimize the impact on the supply-and-demand dynamics so that way you can get a price that’s fairly reasonable.

Michael:          Okay, so we would call that maybe block trading by Wall Street. They have a big block of shares they need to sell into the market without moving the market. And he found or at least as Lewis describes he could no longer do that in 2011 or 2012 when he’s reporting on this story, because prices react extremely quickly, in ways that suggest there’s some kind of conspiracy or the markets are not as they a ppear when he tries to trade. Is that an accurate description of Lewis’s version?

Peter:              I think so. I think he makes a couple of trades and he sees the market reacting to his trades. Happy to go into those trades. He kind of explains why it’s very reasonable the way the market reacted. But he sees the market react to those trades, and then suddenly instead of being the master of price impact, the master of trying to work these orders over many hours, he says I’m the victim of this price impact. He looks to blame someone.

Michael:          Can you tell me in your words what role high-frequency trading firms – because that is your background – interact with somebody like Katsuyama or the rest of the market?

Market Makers

Peter:              I can speak to how my firm would have interacted with him. My firm was an electronic market-making firm. What that means is at any given moment we stood ready to buy and to sell any particular security. Whenever you say I want to go out and buy shares of IBM, you may have wondered “It’s funny that when I go out to buy some shares of IBM there’s someone out there who wants to sell them to me at the exact same time. That’s very convenient.:

The reason there is, is there’s a function in the market called a market maker. That person’s or firm’s job is to provide those prices on a continuous basis. And the way market makers make money is if they’re saying we’re going to buy shares of IBM at $164 and we’re going to sell them at $164.01. Then if the market doesn’t move all day long, and equal numbers go and buy and sell, then I’ll make a penny every round trip. That’s how they make their money.

ibm

Someone like Katsuyama who then comes into the market and says today I have to buy three million shares of IBM will place an order in the market to buy and we would have orders in the market that are willing to sell. So when his orders come into the market to buy, they would interact with our sell orders. We would never know we were interacting with him. It’s completely anonymous. We would never see his order. We would never know how much he wanted. We would simply get a report back telling my firm you placed an order saying you were willing to sell 10,000 shares. And someone has bought 10,000 shares from you.

We might say great, you know what? We’re going to place another order to sell 10,000 shares because that’s what we do. We put in another order to sell 10,000 shares and then maybe he comes back again and buys 10,000 shares from us. He would be doing that throughout the course of the day, from us and many other firms who are market makers. By the end of the day he has completed his transaction, and hopefully we were able to buy those shares back at a slightly lower price. And we didn’t lose our shirt on this whole transaction.

Michael:          I’m familiar because I sat on a trading desk of a bond desk, which is not the same as stocks, but the way the bond desk works is just as you’re describing. We’re trying to buy it at one price and sell it, it being the bond or the stock or the security, slightly lower than where we sell it. And we don’t have a fundamental view on whether that share or that bond is going up or down. We’re just trying to make a tiny difference between where we buy it and sell it. That’s what I understand is a market maker.

I think that you’re describing that what you do is basically the same thing. Although in Lewis’s telling of it you’re doing something fundamentally different. Maybe that’s kind of the heart of the difference between Lewis’s version of high frequency trading and your version. Am I getting that right, that what you’re describing is exactly like a faster and narrower spread basis, but it’s exactly like what I witnessed and participated in, as a bond trading market-maker. Is there anything fundamentally different about what you guys are doing?

Peter:              Not particularly. One of the differences is that in the US equities market, unlike the bond market, there are even more constraints on the price that anyone can transact at in the market. For example, in the bond market different brokers might give you different prices. Where in the equity market, you as a customer, by law, are entitled to get the best price in the market. So it makes it extremely competitive and it also protects the consumer.

One distinction I would make with what Michael Lewis is saying is that he doesn’t actually distinguish among the many different types of trading strategies, so broadly looking at it, he never actually defines high frequency trading. He kind of casts a really broad net and if you look at that broad net, you’re basically saying high frequency trading is more of a technology or technique. It’s almost like saying e-commerce.

It sounded like it was a very specific label in 1996, but now pretty much every single company, even your brick-and-mortar boutique down the street has an ecommerce profile. Same thing with high frequency trading, where guess what, a lot of people are trading with computers. A lot of people are trading rather frequently.

There’s a whole variety of different strategies and approaches that are in the high-frequency trading world. Lewis kind of blurs the lines and smears them together and as a result he comes out with a message saying high frequency trading is bad.

But at other points in his book he says actually high frequency trading is good, but just a couple different aspects of it. So what I’m referring to here is market making. It’s what I know best. And I don’t think any credible person in the market would ever say that market making is a bad business. Althought, Lewis does make some allusions to market making having some nefarious aspect, but I’m not really sure what his point is there. Mainly, he’s targeting the high-frequency trading industry with his front running allegation.

Michael:          What you’re saying is one version of high-frequency trading is market making, trying to make the tiny spread between where you buy it and sell it, and essentially the service is providing liquidity to buyers and sellers, and the business model is to buy slightly lower than you sell.

But I think you’re also saying there’s an entire world of other strategies which involve buying and selling securities quickly, that aren’t providing liquidity in that same way.

Because some of the conspiracy ‑‑ the credible part of the conspiracy theory that Lewis is talking about rests on the idea that hardly any of us who are not in the world of high frequency trading can even grasp what the strategies are. Can you give an example of some strategies without giving up the secret sauce of your own firm, but give us something concrete that we can think about?

Peter:              Would you like a market-making strategy or something beyond that?

Michael:          Market making I’m going to describe as buy it here, sell it here plus a tiny bit.

Peter:              I’m most familiar with market-making strategies but I can kind of speculate on something else. Let’s say you had a strategy where you say whenever I see FedEx is increasing in value by 1% over the course of a day, then I’m going to buy UPS. That’s kind of a pairs type strategy where you’re trading two related companies and you’re saying based on one of these companies moving, another company is going to move.

fedex_ups_pairs_trading
An example of a pairs trade

It’s not necessarily a market-making strategies but it’s one where you’re saying I think that this other component of the market should move because its leading indicator is moving as well.

Michael:          The theory being FedEx and UPS are essentially in the same business. What’s good for FedEx is probably good for UPS. And FedEx is moving without UPS responding, so the logical thing is UPS should be moving in that same direction.

Peter:              Correct.

Michael:          The frequency with which you would need to purchase UPS, we’re doing this on a millisecond basis or a minute basis or over the course of an hour?

Peter:              That’s a great question. Let’s say you have this theory that FedEx should always be worth about two times UPS exactly. As soon as you see that it’s worth 2.01 times you’re going to buy UPS because UPS needs to increase in a bit of value to be on par with FedEx. In that example you’ll be watching and every time you see FedEx pick up a little bit more you say now I need to buy UPS. Or if FedEx kicks down you say FedEx is worth 1.99 [times] so now let me sell some UPS and kind of put that back into balance in terms of my portfolio. You wouldn’t wind up doing a lot of trades. But in the end ‑‑ this is a classic strategy that Wall Street has been running since the last century.

Michael:          But in the case of algorithmic trading, it’s just sped up, and it could be done in the space of less than a second, in milliseconds?

Peter:              Exactly and it’s for much smaller quantities. Instead of someone saying I’m going to  wait until they diverge by 5%, and then I’m going to make a big bet on this, which is the way you would have seen it play out on Wall Street, say 30 years ago. Now you have someone saying I’m going to make a lot of smaller bets, when there’s a smaller divergence.

The advantage from a trading perspective is that a lot of these smaller bets you’re less likely to lose a lot of money if your bet goes south. For the market, you could argue that it’s keeping these prices a little bit more closely aligned because you’re doing more frequent adjustments rather than someone doing a large adjustment on a periodic basis.

Profitability

Michael:          Which brings up one of the examples I really liked about your book, which is a response to the claim from high-frequency trading critics, the fact that these firms are not unprofitable enough. Or that is to say that on almost every single trading day they’re reporting profit, which in the normal world you go “that’s impossible!” Nobody is that good without there being a trick. Show me the magic trick or the cheating. That’s the allegation.

large_numbers
Law of Large Numbers

What I really liked about one of your responses to that was here’s why it’s not cheating: We’re doing 1,000 trades, and even if we only have a 51% chance of making some money, when you apply the law of probability over 1,000 different trades, when you make money 51% of the time and lose money 49% of the time, you’re going to end up profitable pretty much every single time. I’m probably butchering your language around that, but maybe you can express that better than  me. That was one of the strongest arguments in favor of consistent profitability, was the law of large numbers and probabilities applied to small trades done many times.

Peter:              Thank you. You characterized that perfectly. Interestingly enough, just last week, there was a professor from the University of California Santa Cruz who did a research paper that was highlighted in the Wall Street Journal, where he went through one of the firms that Lewis had singled out for this winning record. He went through all their filings and said it’s actually incredible that they lost money on that day, given the law of large numbers.

As you said, the law of large numbers does explain this and it seems counterintuitive at first, but the way I like to explain it to people is if I think about baseball. Over the past 22 years the Yankees have won just 59% of the time. It’s a bit better than even but not much better. If you win slightly more often than you lose and you do it consistently for all of 162 games in the season, you’re likely to come out ahead. They’ve only had one losing season in the past 22 years. That’s kind of remarkable. It’s just 162 times with a tiny bias toward winning, and it comes out to a winning season every time.

The opposite is also true. During the same time the Pittsburgh Pirates won only 45% of the time. They had 20 losing seasons out of the past 22, applied over 162 games.

Now, if you’re trading not 162 times a day but 10,000 times a day, 100,000 times a day, it becomes more and more inevitable that you’re either going to be guaranteed to make money or guaranteed to lose money. The losing money is also another interesting side of the discussion because any firm that is around right now, who is doing this, and is doing it successfully, by definition is making money.

If they had a slight bias to losing money on their trades, they’re already gone. And that’s happened to a number of firms. Some of the people you’ve heard of because they were well known at one point and then they started to lose just slightly more often than they won, and they’re gone. The firms you hear about now of course are going to be the ones with consistent results.

Lastly, there’s another way to think about this, which is that if you are more of a service provider, as opposed to a speculative risk taker, then it also makes sense. If you’re a market maker you’re getting paid for the service of making a market. You’re not speculating on the markets and so the example I gave is if your entrée into the art world is selling greeting cards, you’re selling cards. You’re going to make a penny or two per greeting card. But you’re not going to really lose money. It’s greeting cards, not a high-margin business.

If you are an art investor, you may spend a couple million dollars on a piece of art. It may turn out that that piece of art in ten years is the hottest thing on earth. And now it’s worth 20 or 30-million dollars and you made a huge killing. Or it may turn out that it’s not worth anything at all. It’s a different business model.

When you’re comparing the results of an electronic market maker who’s doing the service repeatedly, 100,000 times a day, million times a day, whatever it may be, versus someone who is making multi-million-dollar bets on obscure derivatives, you’re going to come up with different results.

Michael:          Makes sense. I’d like to return to your example of the Yankees. As a Red Sox fan that hurts. I’d like to say A-Rod was a cheater. And don’t mention Big Papi or Manny Ramirez and their PED scandals.

Peter:              Definitely no Bucky Dent.

Michael:          And please don’t mention Bucky Dent.

bucky_dent_aaron_boone
Bucky Dent and Aaron Boone. F- those guys. Somehow they must have cheated.

Front Running

Michael:          On the issue of cheating, Lewis’s main allegation is that a main part of profitability of high-frequency traders is you’re front running and front running is not super easy to define, but I’ll take a stab at it. You can correct me. It’s in the role of market maker a customer comes in to trade and you use the information you gain from their sale or purchase to anticipate that that security is going to respond to that flow. You can either buy ahead of them and sell it to the customer at a higher price or sell ahead of them and purchase from the customer at a lower price. In any case, using the information of the customer flow to make profitable trades. I don’t know if that’s the only definition but that’s my words for front running.

Lewis says this is the main business of high-frequency traders. They’re getting information in a millisecond that’s coming into the exchanges. They’re responding to it quicker than anybody else can. Getting in front of the customer flow, and making guaranteed profits. Tell me why this is wrong.

Peter:              First, I think you explain what front running is pretty accurately. Sadly, it did happen in the past and it can still happen today. But in a very different way, and that’s when a broker has a customer’s information on their order. And that particular broker who received the order trades ahead of the customer because they have that information.

What used to happen was the broker would get that information. They would look at the price and quantity on the customer’s order. And then they would go out and trade in the market for their own account, buying or selling ahead of the customer. And then they would turn around and then from their own inventory sell those shares back to the customer at a higher price.

The key things that they relied upon there was the ability to see the price and quantity of the customer’s order, and to be able to give the customer a different price than what the market price was. Those are the key things that they needed.

Lewis doesn’t try to explain how those elements could possibly be present in the current market. And the reason he doesn’t try to explain it is it’s probably because it’s impossible to do so. So you can’t explain how someone is determining the price and quantity of the shares you desire. In today’s market, the orders are anonymous. So if you submit an order to your broker, and that broker then submits it to an exchange, no one in the rest of the market ever knows the quantity of your order or the price of your order.

Even if your order trades against the market maker, that market maker still does not know what the price and quantity on your order were. All they receive is a report that says you transacted this many shares. That’s it. They don’t know what the price of your order was. They don’t know the quantity on your order. That information is never available to them.

As a result, they never have the information that will be a prerequisite to any front-running scam. Beyond that, the issue of manipulating the price to give the customer a different price in the market is also not possible. When Reg NMS came into effect, we have this requirement that the customer must get the best price that is displayed in the markets.

reg_nms_chronology
Evolution of Reg NMS and HFT

The only way someone can change that price is by buying every single share in the market. So just to be very specific here; if you place an order to buy Microsoft at $49, and Lewis is alleging your front runner is going out there and is going to buy all the shares at $49 ahead of you, and then sell it back to you a penny higher.

They would have to go into the market and on every single exchange buy every single share offered. They may wind up buying 30,000 shares, a million shares, in order to allegedly front run your order of 500 shares. That’s the only way to possibly move the share price. Obviously, that doesn’t make any sense. It’s ridiculous.

Further, if they did move the share price, guess what? There’s already another million shares behind that at the new price point, so they would be the ones selling them back to you. Someone else is already first in line to sell them back to you. It’s impossible for a would-be front-runner to be able to manipulate the price.

It used to be possible when the brokers had more discretion on the pricing. But in today’s market it’s simply not possible. And Lewis never took the time to understand how the market works, what these rules are about price protection in the market, which makes his allegations completely impossible.

I guess the last thing I would say is that he kind of justifies the whole thing by saying you can’t really prove or disprove this because the data doesn’t exist. It couldn’t exist to prove or disprove. And that’s completely false. The data is out there.

We would have a homework assignment for our trainees to look at a particular trade that a strategy did in the market, and explain exactly how the market reacted; what happened after it; what trades occurred after it. All the data is there.

You can get it from a Bloomberg terminal, you can get it from your own systems. This is the industry in the world that is the most awash in data, and it’s completely ridiculous to say that one cannot find any data to substantiate his claims. The only explanation that makes sense for that is that there isn’t any data to substantiate his claims.

Michael:          How about this; why do large buy-side firms believe the thesis? That if you’re Putnam or Fidelity and doing large-block trading, do they believe that high-frequency trader are front running them or do they not believe that? Or are they not sure?

Peter:              I think there’s no single answer because I think there’s a variety of opinions. That’s something that is very interesting and Lewis kind of glosses over that. For example, Vanguard came out and said all of these changes from electronic markets are good. We’ve seen that our price to complete a trade has decreased by half a percentage point. It’s incredible for them to say this is how much more efficient the markets are nowadays.

vanguard

The SEC has estimated that for institutional investors, the people you’re talking about, their cost has fallen by about 40% on their trades since 2003. That’s the cost of actually transacting in the market, not the processing after the fact. Literally, the pricing they’re getting in the market versus what they desire has improved by that much. I think on the whole the industry realizes the benefits of the current market structure, and of electronic market makers.

You do have people who are complaining and I think that’s unfortunate, but it’s also understandable. People do have a tendency to blame someone else when things go wrong. It’s very convenient when you take a little risk on your trade, and it goes against you ‑ it’s much more convenient to blame someone else than it is to take responsibility for it. It’s kind of the mantra on Wall Street.

flash_boys_not_so_fast

Michael:          Yeah, if things go badly it’s the fault of the market. If things go well, it’s because of my brilliance for sure. That’s the only way to get paid.

[1] Actually, the book came out almost a year ago at this point, but I have been slow in uploading this interview! My apologies all around.

Please see related posts:

Book Review of Flash Boys by Michael Lewis

Book Review of Flash Boys Not So Fast, by Peter Kovac

Book Review of Inside The Black Box, by Rishi Narang

Are HFTs a force for good?

What D&D Alignment are HFTs?

and upcoming audio interviews:

with Peter Kovac, Part 2 – Dark Pools, IEX, Disruption, Blowups

and Peter Kovac Part 3 –  Cheating and Morality

 

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High Speed Trading – And DandD Alignments

half_elf_bard
Apparantly this is me in D&D, except I think minus the pony tail

I’m trying to figure out where electronic and high frequency trading firms fit with respect to Alignment, and how I feel about that.

Alignment

I mean “Alignment” the way a Dungeons and Dragons (D&D) player means it (full disclosure: I’m a Lawful Good Half-Elf Bard in real life. I mean, in the game. I mean, outside of my writing. Whatever, you know what I mean.) All D&D characters are either Good, Neutral, or Evil, and act either Lawfully, Chaotically (law-breaking), or Neutrally (in between).

So, on our quest to understand electronic trading, it is helpful to know which alignments electronic traders fall under, including high frequency traders (HFTs)?

But First: A Definition

Instead of making human judgments about when and how much to trade stocks (or bonds, or currencies, or commodities or derivatives) electronic traders program computers to make those decisions, usually based on some set of conditions that indicate a momentarily profitable opportunity. Electronic, or ‘algorithmic’ trading, is about 25 to 30 years old. High frequency trading is a subset of electronic trading, except done at a humanly unimaginable pace – like 1,000 to 10,000 buy or sell orders per second. High frequency trading is about 10 to 15 years old. In recent years electronic trading accounts for between 50-75 percent of all stock market trading. Like SkyNet or Hal 9000, this naturally makes the humans nervous. But are they good or evil or neutral? [1]

Google_as_skynet
They slyly dropped “Don’t Be Evil” from their corporate motto

Are HFTs Chaotic Evil?

If you read Michael Lewis’ 2014 book Flash Boys the most widely read story about the high frequency trading industry to date – you would develop the strong impression that these firms hew to chaotic evil on the D&D alignment compass.

In Lewis’ story, HFTs operate as predatory sharks attracting unwitting investors inside broker-sponsored ‘dark pools,’ all the better to extract trading profits through quick-strike trading against slow-footed prey. These evil creatures also use ‘spoofing’ subterfuge and aggressive ‘front running’ tactics. I expand on these tactics below.

‘Spoofing’ – in which electronic trading firms send large numbers of false orders to market exchanges, only to cancel them immediately, is a ploy (I admit I can’t explain in plain English exactly how this would work) to manipulate markets, and is clearly chaotic. It’s also illegal, and would lead to enforcement action against any firm doing this and getting caught.[2]

‘Front-running’ – in which an electronic trading firm uses prior knowledge about a customer order to buy or sell ahead of a customer for its own profit is also evil, as well as clearly illegal.[3]

And Flash Crashes

Many blame recent occurrences of “flash crashes” on algorithmic trading. Flash crashes are exactly the kind of mess that chaotic evil-doers would wish on markets.

Increasing the frequency or severity of flash crashes is the most likely way in which electronic trading causes chaotic evil effects. I don’t mean intentionally, but rather as an unintended consequence of numerous market players pursuing their own strategy. Something like: All market signals indicate to the algorithms the need to sell – all at the same time – which becomes a self-fulfilling downward spiral for prices. That type of unintended effect, however, predates the rise of HFTs. The 1987 Crash, for example, stemmed from the rise of ‘portfolio insurance’ that caused many institutions to suddenly need to sell securities, all at the same time, to limit losses. In the absence of real news, prices drop on such rush-for-the-exits stampedes.

On the issue of crashes and market glitches, there’s the not-too-infrequent case of human traders – not only computer traders – doing a bad job of ensuring orderly markets. This happened in August in a high-profile case of the floor trader on the NYSE who halved the value of publically traded KKR, a company whose markets he was responsible for trading, for about 15 minutes, for no apparent reason. The right standard for comparing human trader to computer trader is probably not “error-free,” but rather frequency and severity of mistakes and glitches like this. My point here is that human traders can probably screw up markets just as badly as programmed computers.

Or Lawful Good?

My friend Peter Kovac wrote a book last year – Flash Boys: Not So Fast, as a response to Michael Lewis’ book, in which he argues not only that Lewis got many details of the industry wrong, but perhaps the HFTs should be regarded instead as something like Lawful Good (my words, not Kovac’s.)

I’ll explore some of Kovac’s reasoning in follow-up posts, but for the moment I have in mind what I wish, and perhaps think to be true, regarding electronic traders.

Lawful Neutral

As a Dungeons and Dragons player (as well as a greedy capitalist,) I would hope for Lawful Neutral alignment among high-speed electronic traders. I mean, I don’t expect a trader to be saving the whales or reducing carbon emissions when he or she programs a computer algorithm to buy and sell securities at light speed. Their goals, as for-profit companies, are to make a profit. But I do expect them to always follow the law.

What Lawful Neutral means to me is that as long as they follow the rules – avoid conscious or even unintended evil-doing – then I’m ok with extraordinary profits accruing to electronic traders. That’s because I believe the profits of an algorithmic trading firm will mostly come at the expense of legacy Wall Street trading firms (the “old guard”) which are slower, or which operate at less efficient (meaning, wider) margins. I’ll write more about this next week as well.

 

A version of this post ran in the San Antonio Express News.

Please see related posts:

Book Review: Flash Boys by Michael Lewis

Book Review: Flash Boys Not So Fast by Peter Kovac

Book Review: Inside The Black Box, by Rishi Narang

 

 

[1] Assigning corporate alignments in D&D fashion is not necessarily new. Google’s previous corporate motto “Don’t Be Evil” is a seemingly simple standard, for example, from which to begin to evaluate high frequency trading. I’m not sure Google founders Brin and Page ever played D&D, but let’s just say it’s not unlikely that they know their way around a 20-sided die, right? Also, did anybody else notice Google dropped “Don’t Be Evil” as a corporate motto? Do you think it means what I think it means?

[2] My sense is that while this has happened in the past, it’s not normal market practice among electronic trading firms, any more than spamming is normal market practice among marketing companies. Sort of like: there are spammers, and there are marketers, but these are different types of firms with different business models

[3] Incidentally, front running as a business practice is probably as old as any stock brokerage business, it just happens that speedy trading could make it more easily perpetrated, and more easily hidden, at least for a time. Any firm shown to front-run as a business practice, however, would be fined and regulated out of the trading business.

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Ask an Ex-Banker: Algorithmic Trading

A version of this post appeared in the San Antonio Express News

Algo-Trading

Dear Mike,

I spotted something on algorithmic trading on your blog, and finance and investment are a bit of a hobby of mine. I am sending you a press release about a Canadian trader who has worked out a successful trading technique based on an algorithm, and a new trio of former Harvard fellows have made an app allowing you to do it yourself.

Here’s an excerpt from the link he sent me:

AlgoTrades, the leading provider of automatic investing systems for individual investors, and EquaMetrics Inc., the leading provider of algorithmic trading systems and their Intuitive, drag-and-drop interface that lets you quickly build and edit complex algorithms – in a matter of minutes, today announced a strategic partnership that will arm both active traders and investors with the ability to have the AlgoTrades investing system traded for them, and build trading systems of their own[…]
Algotrades is seeing increased demand for its existing automated trading systems. The Algotrades futures system is hitting at 100% accuracy for the first 6 months of this year with a ROI of 12.3% to date. Max peak-to-valley drawdown is 2.4% and many of our clients are asking for more diverse and active automated trading solutions to expand their portfolios.

This intrigues me: My question is: What is your gut feeling about this? Apparently some of the big news journals like Barron’s and the Wall Street Journal gave this coverage, so it might be something, or not? Any ideas about it?

–Willem from the Netherlands

Dear Willem,

You probably saw on my site that I’ve written reviews of three books on this topic: Rishi Narang’s Inside the Black Box and Michael Lewis’ Flash Boys, as well as a review of a book by a friend from a high frequency trading firm who says Lewis got it all wrong, Flash Boys: Not So Fast.

As for the opportunity described in that announcement:
I would run, not walk, away from anything like that.

I have a long list of reasons for this advice, but I’ll just name a few.

1. Algorithmic trading typically involves high volume trading activity. For an individual investor the trading costs and – equally importantly – the tax bill make this extremely tax and cost inefficient. Brokers and certain types of professional institutional investors get trading costs lowered dramatically, and are not subject to the same capital gains tax laws as individuals (at least in the US) based on high volume buying and selling of stocks, so they don’t have that inefficiency problem. But for you, high volume trading is likely deathly to your individual account, due to costs and taxes.

2. The ROI (Return On Investment) claim in that press release makes me very wary. Even assuming its true, this is an extremely short time horizon, and barely tells us anything, except the juicy part, namely 12.3% ROI in just 6 months’ time.

In my experience, professional investors who can consistently achieve 12.3% ROI over 6 months (24.6% per year, annualized) never, ever, (ever!), seek to share that technology with others. They don’t market secrets like this. Why should they? Instead, they just quietly compound 24.6% per year for a few years and they can get extremely wealthy all by themselves.

3. Be skeptical of groups or strategies that claim high returns over short time periods, and market their services and technology to the general public. Many strategies can make (or lose) impressive amounts of money over a short time frame. If the strategy could – reliably, provably – earn that kind of return over 10 years, now I might be interested. But again, see point #2 above, because those folks wouldn’t be interested in sharing the strategy with you or me if they had a 10 year track record of 24.6% annual returns. They’d already be extraordinarily rich without us.

4. The successful institutional algorithmic and high frequency traders that make money have extraordinary advantages over individuals trying to mimic their techniques. The kind of traders described in Michael Lewis’ Flash Boys for example, invest tens to hundreds of millions of dollars in software and hardware to give them every technological advantage over the kind of individual traders targeted in this press release. I simply do not believe this ‘algorithmic app’ for individuals could possibly compete with the knowledge, technology, and capital of established firms in this competitive space.

In sum, and to recap: Don’t walk away.

Run!

 

 

Please see related posts:

 

Book Review of Flash Boys by Michael Lewis

Book Review of Flash Boys: Not So Fast by Peter Kovac

 

Book Review of Inside The Black Box by Rishi Narang

As well as:

Would You Like to Understand High Frequency Trading?

The Rise of the Machines

 

 

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Would You Like To Understand High Frequency Trading?

My friend Pete Kovac got so peeved about Michael Lewis’ Flash Boys that he wrote a response, in the form of a book, called Flash Boys Not So Fast – An Insider’s Perspective On High Frequency Trading.

fight clubThe highly unusual part about this book is that high frequency trading up until now has basically been like Fight Club, in so far as the first rule of high frequency trading is that nobody talks about high frequency trading.

Well, here’s Pete actually talking (ok, writing) about it. He agrees with my objection to Flash Boys, which is that Lewis appears to have not gotten any access to actual real live high frequency traders, in the course of investigating his book. Which is kind of a problem.

Pete’s formal bio is as follows:

Kovac was COO of the electronic market making firm EWT from 2004 to 2011, managing regulatory compliance, risk management, finance, trading operations, and portions of the technology teams. During his tenure, EWT grew to one of the largest market making firms in the U.S., trading hundreds of millions of shares daily, an, together with its affiliates traded in over 50 markets worldwide. Kovac has been a frequent commenter to the SEC on regulatory issues.

And Pete’s informal description of his role:

“I am an industry insider, the kind of person who could have saved Lewis from making some really basic mistakes. I started programming trading strategies in 2003. After years in the trenches, I moved into management and ultimately became chief operating officer of my firm, EWT. I handled regulatory compliance, risk management, finance, trading operations, and a portion of the IT and software development teams – and I had to know every aspect of the stock market inside and out. By 2008, our company was one of the largest automated market-making firms in the U.S., trading hundreds of millions of shares of stock daily, and had expanded into many other asset classes domestically and internationally. I left it all three years ago when EWT was sold to Virtu Financial (in which, in the interest of full disclosure, I still retain a small stake).

Those eight years at EWT provided me with a front row seat to all the events described in Flash Boys, and much more. During that time, I shared my experience and perspective in discussions with regulators and lawmakers here and abroad, advocating for the continued improvement of the markets discussed in the book. Many of my comment letters on these topics are publicly available on the SEC website. Even though I no longer work in trading, I can still get answers from a diverse set of close sources when a truly new question arises.”

So – If that’s intrigued you – you can download the book here.

 

Please see related posts

An Excerpt of a Quant Trader’s Critique of Flash Boys

The Rise of The Machines

The Katsuyama Revolution Continues

Please see related book reviews:

Inside the Black Box, by Rishi Narang

Flash Boys, by Michael Lewis

 

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The Katsuyama Revolution Continues

Katsuyama & Team at IEX
Katsuyama & Team at IEX

The Wall Street Journal carries an update this morning on the main protagonist of Michael Lewis’ recent book Flash Boys, Brad Katsuyama and his newly launched (October 2013) exchange known as the Investor’s Exchange (IEX).

One of my main questions left after reading the book is the viability of this newly launched exchange. Katsuyama & his team seek nothing less than the irrelevance of both dark pool equity trading and high frequency trading on equity exchanges, a mighty set of targets. Because Lewis published Flash Boys just a few months after the exchange’s launch, we’re left wondering whether Katsuyama’s revolution will happen or not.

As of today’s article, Katsuyama carries on, applying to expand the IEX into a full-fledged stock exchange. Most importantly, he has set the rules of the IEX so that traditional broker-dealers (The Goldmans and Morgans of the world) trade for free – to encourage them to bring their trade flow in high volume to the IEX, while outside firms – most pointedly we assume high frequency trading firm – all pay fixed commissions per trade.

This second part is a key feature of IEX, which is built to counteract the conflicted cost and fee structures of other equity exchanges which pay for order flow in a convoluted – but probably investor-unfriendly – way.

The main thesis of Flash Boys is that the combination of dark pools – in which broker-dealers did not disclose who had access to deal flow and in what manner – and the complicated set of fees paid or received in different equity exchange – seems to have benefited high frequency traders at the expense of slower market participants.

From what we can glean from the article, the Katsuyama revolution rolls on.

Please see related book review for Michael Lewis’ Flash Boys

also see related book review for Rishi Narang’s Inside the Black Box

 

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