Stig Brodersen  12:11  

Yeah. Because one thing that I was really surprised about was these trading companies had years and years of winning days. I mean, they didn’t even have one losing day. And how is that possible when you’re trading? I mean, you’re really betting against other people. And the only way you can win, like every day for four, five consecutive years is really to have information that the other party doesn’t have. So as you’re seeing in this example from Preston, the only way I can beat him is if I know exactly what’s going to happen before he knows. And I think that’s kind of like the underlying factor that you need to understand here. It’s a game of information and it’s a game of speed.

Preston Pysh  12:50  

And so, Stig has a great point. A fantastic point that was highlighted in the book. I think it was, I can’t remember the exact number but it was like around 800 days of trading and they only had one day that they lost money from the trading activity that they had. And that one day that they lost was because there was like a glitch in their system and they had like an air. It wasn’t because they just got beat. So to kind of give you an idea of how well their strategies are working, it’s pretty amazing. 

And something else that I want to highlight is, every day whenever the market closes, these high frequency trading companies have zero shares on their books. So they trade millions upon millions times a day. And then whenever the market closes, they don’t have one security sitting on their books at the end of the day. Just the proceeds of what they made from all their transactions. 

Some interesting stuff. I don’t even know how to possibly describe how interesting this book was and how I don’t even know how to describe it. It was just really cool and something that I think everybody would really enjoy. Yeah, go ahead, Stig.

Stig Brodersen  14:00  

Yeah, one thing that I think I’m with you Preston. I was really surprised about almost everything I read in this book is because it really puzzled me how these high frequency companies know which trade I was going to send in as an investor. 

And what’s happening is that if I’m an institutional investor on a big investor, and I’ll actually pay my broker to execute an order for me, that broker will actually sell the information. I have a big buy order for instance, to these high frequency companies, so that brokers actually paid twice, and I’m actually paying for it, twice. Partly because I’ll get a worse price and partly because I’m also paying commissions to my broker.

Preston Pysh  14:41  

So let’s talk about what was really in the book, Flash Boys. And so what happened was, there were really two main themes that I think Michael Lewis was trying to get across here. The first one revolved around this programmer from Goldman Sachs, Sergey Aleynikov. And so Sergey was a programmer for Goldman Sachs trying to implement a high frequency strategy for Goldman. 

And whenever Sergey left, and he went to go work for another business, Goldman Sachs brought up criminal charges against Sergey for stealing some of the code that he was working on whenever he was at Goldman Sachs. I think Michael Lewis does a really good job describing the full story on Sergey. And how the code that he had actually taken from Goldman was actually open source code. And open source code is nothing. It’s something you could just go find on the internet. It wasn’t like something that was proprietary for Goldman Sachs. At least, that’s the way that Michael Lewis describes it in the book. So it talks about a lot of the injustice and how this poor gentleman was really, I mean, he was thrown in prison. 

So this is the information that I got on Sergey. It says that Sergey is a former Goldman Sachs computer programmer. He immigrated from Russia to the US in 1990. In December of 2010, he was wrongfully convicted of two counts of theft of trading secrets and sentenced to 97 months in prison. But in 2012, his convictions were overturned by the United States Court of Appeals for the Second Circuit that entered a judgment of acquittal reversing the decision of the district court. So you can see that he was wrongfully accused. 

And I think it was really neat how Michael Lewis talked about how Goldman Sachs and maybe like their middle management brought up these claims because no one understood how this stuff worked. And you got these few technical type people that are writing code for this stuff. And they’re the only ones that truly understand how it’s implemented and used. And you got these big bank executives that are trying to enforce Hey, this guy stole something. But yet, they have no clue how any of it works. 

And I think that was really his point that he’s trying to bring up in the book. You got these big bank executives that are clueless how this stuff works. And they’re trying to bring up claims against different programmers that are implementing the strategies and then they’re not even actually stealing anything. They were just taking open source information. So stay Go ahead.

Stig Brodersen  17:06  

Yeah. And I think that another great point that Lewis brings up is that these managers, these big time sectors, they have to accuse Aleynikov for doing something wrong because if you can just take code that doesn’t have any value. What’s the reason why these managers are there anyway? 

I mean, what’s the reason why they gain millions of dollars? What’s the reason why they’re building up a whole system? It is basically just open source code with a few tweaks here and there. So it’s kind of making their own position at justice if they’re accusing this poor person for stealing the code.

Preston Pysh  17:44  

And I think he liked the… something that was kind of neat, the way he did it in the book is I think he wanted to highlight the difference between this guy who’s making maybe $100,000 or $200,000, a year as a programmer writing the secret sauce for how all this stuff works for the bank to make billions of dollars. And yet there’s some executive that’s sitting above him making $3-4 million a year. And he has no clue how it works. But yet he’s the guy pointing the finger at, you know, one of these programmers. 

So the contrast there is I think what Michael Lewis was really highlighting in the book and it was kind of a very neat discussion and something that I think shed a lot of light on something that very few people had seen or even understood. So the next character in the book that we really enjoyed the discussion on and we’re in talks of trying to get this gentleman to come onto our show, and he’s responded to us. So we’re very hopeful that we’ll be able to bring him on in the future. But this guy’s name is Brad Katsuyama and he worked for the Royal Bank of Canada. Most of the book is centered around Brad and his adventure of debunking high frequency trading and what he ultimately did. 

So whenever he was working for the Royal Bank of Canada, he was working with these different traders and he would see these orders come in. And then the people from his bank that were trying to execute the orders would put in their order, a large volume order, just to see it. It changed and they weren’t able to get the hundred thousand trades in. They would only get maybe 20,000 trades in. And they’re trying to wonder, how is this happening? Before, we were always able to get the full hundred thousand trades in. 

He starts pulling back the onion on this and you start studying it and he’s realizing that he has high frequency traders that are beating him to all the other exchanges and all the other markets where they’re trying to process the hundred thousand share order. And so, it talks about how Katsuyama is going through and methodically trying to solve this problem. 

And so, this is a big generalization of the whole story, but in essence what happened was, whenever Katsuyama, as people were executing an order for let’s call it, 100,000 shares, they might get only 20,000 enough of them that come back at the price that they wanted, and then the rest wouldn’t get executed because the price of the stock had gone up. 

What was happening was they were able to snag those 20,000 orders at the first exchange that was closest, literally by distance, that was the closest distance to where they were executing the order. But then on all the other exchanges that were further away, because of the speed of the line, they weren’t able to get that price because they were getting beat by high frequency traders, just like the example that I had described with Stig and I tried to buy Apple. The same exact thing. And I’m just going to jump to the end here. 

So Brad Katsuyama, he’s trying to think of ways that he can basically beat the high frequency traders and not do it through investing in really expensive internet lines and ways to move the trade faster. 

So what he did is he had a bunch of programmers develop a software program called Thor. And what Thor did is it puts in automatic delay into the order, so that they would all be executed on different exchanges at the exact same time. So it kind of be like if we were going back to our original example, the apples. 

So let’s say that I was trying to buy 1000 apples, but I was trying to buy them on five different exchanges. So let’s say that there were 200 apples available on each exchange so that the scenario makes sense. So what I would do is I would effectively have, you know, five people, they would all go to each market, all at the exact same time. And then we’d all look at our watch, and whenever our watch would say that it was exactly 12 o’clock, all five of us would purchase our 200 apples at each one of the markets. So that way 1000 orders all were executed at the exact same time. 

And so Brad Katsuyama came up with this idea of basically putting a delay into, so it’s a little hard to do that because you don’t have five different people being able to walk to each one of these exchanges, but the way he did it was through software algorithms that he knew the time that it took for the order to get to another market. So what he would do is he’d send out the orders first to the markets that were really the farthest away, and then he would put a time delay into the markets that were closest to him so that all those orders were executed at the exact same time. 

So that was Brad Katsuyama’s Thor software solution. Now, where it got really interesting was Brad Katsuyama found out about all these, what they call dark pool exchanges that companies like Goldman Sachs, and all these big banks, Morgan Stanley had these dark pool exchanges where they were executing orders as well. 

So Brad takes it to the next level. This guy goes out. He says, “You know what, I’m going to start my own stock exchange. And I’m going to do it in a manner so that high frequency traders cannot take advantage of the orders.”

And what he did is he actually put coils off line. So that whenever the orders would arrive, they would arrive at the exact same time and high frequency traders could not exploit the time dimension and the distance dimension between markets, which is just crazy. So, but go ahead, Stig.

Stig Brodersen  23:15  

Yeah, and Brad is a really unique person. I mean, not only because he’s standing up almost like a one man army against Wall Street and all the big banks, but at the point of time when he lost his bank, he was the only exchange out of 66 that actually disclosed the rules and the procedures of the exchange. 

Now, it’s not like I have read all the regulations for exchanges in the US. I mean, that’s probably going to take me a long time if I decided to do that. But I was just surprised when I heard that. I thought it was publicly available like everyone could go in and see if some trading companies got it known at advantage due to others. 

But apparently at Brad’s exchange, [they’re the] only one who chose to close. How they were treating investors and brokers, and what [were] the rules and procedure? And that was quite surprising to me. 

Preston Pysh  24:08  

So I think the thing that was probably most impressive for me about Brad Katsuyama was the fact that he was making a lot of money when he was working at the Bank of Canada. I mean, he was probably making I think I remember even like $2 million, is that right? So he’s making like $2 million. And this guy just decides, you know what, I’ve got to do what’s right, and I’m going to leave and I’m going to start my own exchange so that I can fix this problem. And so I give this guy a lot of credit. Like hats off to him. I really hope he comes on the show. Okay, so let’s go ahead and now conclude the book. And so at the end of the book, it was really, really comes full circle. And this just shows you how good Michael Lewis’ writing style is. If you’re a person who, you know, is interested in the stock market or investing, Michael Lewis is basically like the action novel writer. He’s like the Tom Clancy of investing books. So at the end of the book, he concludes by talking about that right now instead of them doing a hard land line between Chicago and New York, they’re now setting up conventional microwave links antennas between Chicago and New York, which follows an even straighter route than the spread networks 827 mile cable. 

And so, these microwave antennas are now shooting from one, and for microwave antenna, it has to be a direct line of communication. So they’re putting these things on top of mountain tops. And they’re basically shooting these signals from Chicago to New York, across the Appalachian Mountains through these microwave antennas. 

So whenever they set up these microwave antennas, they shaved another 4.5 milliseconds off of the speed between Chicago and New York. And I’m sure that they are charging these high frequency traders that utilize this line a hefty sum of money. And so, whenever we talk about that, and we think about that, that’s really going to lead us into our last segment here, which is our thoughts on high frequency trading. So my opinion on high frequency trading. First of all, I think this stuff is ludicrous. This is crazy. 

And I think that it has a limit. And I think the limit is the fact that this stuff is not cheap to do. Everyone wants to talk about the income, or the top line of the income statement of how much they’re making on this stuff. But what they’re not talking about is, number one, the cost associated with all the computers, the high powered computers that they put on each one of these exchanges in order to process all this stuff. They don’t talk about the expense of how much it is to run all these different lines and the fact that this was really my second point is that the competition is fierce. And the competition is only going to get fiercer. 

And the thing is if you’re not the fastest guy on the block, you’re probably going to get your lunch eaten. I mean you’re going to get taken for a ride if you’re not the fastest guy in the block. And so what you’re doing is, you’re in this fierce competition environment that’s a very high dollar threshold in order to enter. And so I think that this is something that as speed, you can only go so fast, okay. And you can only invest so much money to go so fast. 

And what I think you’re going to get is a point of no returns where after they invest all this money and they figure out the fastest way to get from one market to the other, I think it’s going to kind of devour itself over time. And so whenever I asked myself, where’s this going to be in 10 or 20 years? I really think that you’re going to be at a point where the margins and the growth on this stuff is going to deteriorate over time. Go ahead, Stig, I know you have a point.

Stig Brodersen  27:46  

Yeah, I would like to talk about, like from the investor’s point of view. But first, I would like to say that I feel really sad about that. It doesn’t create any value. I mean, you have so many brilliant people. So many PhDs in engineering, scientists, and they can do so many good things for humanity. 

And then they were just sitting programming to try and beat each other in a completely hopeless game. And that was actually the thing that was said to me the most. I don’t know what your take was, Preston. 

Preston Pysh  28:17  

So it’s amazing that you said that. Because my exact same thought. I kept thinking back to that Charles Koch book where he talks about what value are you adding to society. The more value you create, the more wealth you’re going to create for yourself. And that just kept coming up in my head as I was reading this book was like, “What are they doing? What value are they creating for society?” The fact that they can beat somebody else’s order to another market in four milliseconds, I mean, that’s crazy. 

That does nothing but drive up the price and just yeah, it was a little frustrating. So that’s, I guess when I look at it from an investing standpoint, I totally agree with you that even if the numbers made sense, what value are we creating here? 

And I think that that’s the thing that I think a lot of investors need to have at the forefront of their mind. Whenever they’re buying something because I think you’re always going to get burnt if you’re investing in something that does not create value for society. I think that that’s just probably the golden rule here. But to backup our claim on the fact that they’re going to devour their selves. 

So when you look at the numbers, the profit margins from 2009, the estimate is that high frequency trading made $5 billion. In 2012, though, the estimate of how much profit was made through high frequency trading, it was $1.25 billion. So [it] went down effectively. It’s at 20% of the level it was back in 2009 already. And that was in a 2012 number. We’re already in 2015. So who knows how much it’s gone and deteriorated since then. 

So some interesting things that you wonder, you know, what’s the direction of this stuff? Now if you disagree with us, and you think that this is value added to society or whatever, guess what, there’s publicly traded companies that do this stuff. For example, Knight Capital Group, their ticker is KCG. If you want to invest in high frequency trading, there’s a company to do it. So if you want to be an owner of this stuff, you can do it. I would steer away from this. That’s just my personal opinion. I have zero interest in this stuff. And I think that it’s very interesting, extremely interesting, but it’s not something I’m interested in investing.

Stig Brodersen  30:26  

You know, my take, because you know, I was also thinking, what does this mean to me as an investor? Can I trust the financial markets? What should I be cautious about? And I gotta say that even though it is disturbing for me that you might be in there be paying a few cents more per share because of this high frequency trading, and I don’t think if you are a small time investor, which I am, and if you’re only trading a few times a year, 10, 15, 20 times, perhaps? I don’t think it’s that big a problem. 

I think It can be very costly and it can be a problem if you’re trying to go in and out of the market all the time and you’re trying to compete with these guys. But if you are a value investor, a long term investor, I think that you shouldn’t be too worried about this high frequency trading.

Preston Pysh  31:15  

Yeah, I completely agree with what you just said Stig. Alright, so this is the point in the show where we’re going to go ahead and play a question from our audience. So our question today comes from Satish Austin. And he has a very good question. So we’re gonna go ahead and play it right now.

Satish Austin  31:29  

Hi, this is Satish thanks *inaudible* for your course on YouTube. As I understand, value investing is based on making financial positions based on business fundamentals. However, I also hear that both institutions and individuals make large profits are fairly making trade positions based on technical analysis of the charts. Should I not use both fundamental and technical analysis? If yes, then how do I balance between them? Thanks.

Preston Pysh  32:07  

Okay Satish, this question, I really like this question because a lot of people out there feel like they’ve got to do one or the other, and you’re asking, Why don’t I do both? And so what you’re really getting into is do I use statistical methods through charting, through candlesticks, all those types of things you see a lot of day traders execute. Or do I use the value investing approach where I’m looking at the fundamentals of the business and owning it forever? Why not mesh those two approaches together and you know, invest that way? 

And I think that that’s a fantastic question. But with that said, here’s my here’s my opinion. I haven’t been able to execute an approach using technical analysis which is the chartology, candle sticking, and that kind of stuff, successfully. I have not been able to do that. I don’t know any day trading billionaires out there. And I kind of use that as my benchmark for, is there a way to be successful at doing this? And I look at how many people out there have been successful in a major way. 

And you know what, I don’t know of any. But I do know that high frequency trading implements some of these tactics. So I think that the way that we can say that [is] there aren’t billionaires out there now. But there are billionaires that have executed high frequency trading. 

They’ve implemented in a way that’s utilizing these high speed internet connections in order to defeat and beat other people to the trade. And I think that is probably the only way that a person can be highly successful using technical analysis. That’s my opinion. I might be wrong about that. But based on the fact that you look at how many people out there that are billionaires that have been successful with this, there’s a few. 

For example, there’s Vincent Viola who’s the owner of Virtu Financial. I tried to get Vince to come on our show. Vince actually responded to me. And he said, no. He’s a West pointer. So I was able to contact them through the Alumni Association and he said that he was not interested in doing any interviews. 

But he is one of the only people that I know of that’s a billionaire through executing these strategies of technical analysis and using high frequency trading as the vehicle in order to do that. 

So my opinion is, unless you are somebody that could stand up a company that could compete in this high frequency trading realm using technical analysis methods, I just don’t see how you could do it successfully. So as a result, I see that you have to rely on value investing maybe is a better approach in order to capture gains successfully in the long term. So Stig, I know you definitely have some points on this.

Stig Brodersen  34:50  

Yeah, I think that you know, I completely agree with you, Preston. But I think I have two main reasons why I’m not going into this whole technical analysis thing. The first one is definitely time. To me, to sit down and look at these charts and make all this work. I don’t know if it’s just me being too lazy, but it just seems much more appealing to me to read a few annual reports, track a company, buy the stock, and just wait for 10 years. 

I mean, that really works for me. If I had to run to the market every day, I probably couldn’t do anything else. So I mean, from a time perspective, I don’t think it’s the right procedure. And I might not be too persuaded into how it actually works. 

And there’s a few reasons for that. One is the whole fee structure. So if you start to use as a personal and private investor, if you start to trade on exchange, you might be paying something like $5 to $10 for every trade you do. To beat the market when you have to pay fees every time and do hundreds or thousands of trades, I think that’s really, really hard. Because on the other hand, you’re competing with companies that’re getting what’s called the critical rebates. 

And what that actually means is that they can buy a stock at $10 and sell the $10 and actually make a profit because they’re actually getting something back from the exchange of Ryan liquidity. So while you’re paying $5 to $10, they’re actually getting paid to trade at the exact same price. So it’s a really unfair game. Also given they have more, you know, manpower, a lot more computer power than the common investor. So I just think it’s a game for the biggest stock, and this definitely is not [a] stock in your favor.

Preston Pysh  36:35  

So I completely agree. Satish, I’m not sure if that answered your question. But we’re of the opinion that a value investing approach is probably the best way to go for the common investor. Just because of the pure capital that is required in order to compete in a market like this, the infrastructure that’s required, and the fact that I just don’t think that you can go out there and find somebody who has successfully implemented technical analysis and has been able to show, “Hey, I’m worth 100 million dollars, and I was implementing technical analysis from the very beginning.” 

I don’t think you’re going to be able to find that person. And if you do, I’d love for you to shoot us their name and maybe we could get them on the show or whatever, and study the person and bring that to light. But I haven’t found that person. 

So that’s what we got for you today. We really appreciate everybody joining us. Satish, we’ll be sure to send you a free signed copy of our book, the Warren Buffett accounting book. And for anybody else out there, send us your questions. We love getting these questions. And I think that they’re very beneficial to the audience. So go to asktheinvestors.com and record your questions there. 

But that’s all that we have for you today. We’ll keep you updated on whether we can get Brad Katsuyama on the show on a later date, and we can discuss his investor’s exchange more potentially in the future as well. So thankful for everybody joining us and we’ll see you next week. 

So one of the things that Stig and I are very strict about is not endorsing any kind of service or product that we don’t personally use ourselves. So with that said, we give our full endorsement of our sponsors content realvisiontv.com. Real Vision is a site that Stig and I personally use ourselves, and it has had a profound impact on the way that we view the financial markets. 

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Outro  39:42  

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