All language subtitles for (46) The Man Who Cracked The Market Algorithm - Samir Varma PhD - YouTube

A rocket scientist turned trader ranked officially the 5th best in the entire United States.

You need to understand two things. How to lose money and what your reaction will be to the loss

and how you're going to act. And the second is you need to understand what it is about your logic

that went wrong that caused you to lose money and be able to distinguish bad luck from bad process.

Introducing Samir Varma, a PhD particle physicist turned 8-figure futures trader,

consistently beating the market for the last 30 years. In this episode, Samir reveals how

in designing algorithms he discovered that market manipulations are just hidden iceberg orders.

And how a leech on the whale strategy is the best way to catch a ride alongside the market movers.

Liquidity of the stock market at any given instant in time is not very big. An actual

retail stop order can move the market even though you wouldn't expect it to because at that moment

in time there isn't much liquidity. Liquidity exists over periods of time. At instance in

time it doesn't really exist. So I'll give you a perfect example. If you're holding a position

overnight, do you get nervous? Can you sleep? If you've had a bunch of losses in a row, do you

freak out? I think I'm pretty good at handling that. You're pretty good at handling that. Just

those two questions already suggest you could probably do intraday trend following. The place

that you would probably want to do this is opening range breakouts. And you could basically find like

a 10, 15, 20 minute range, wait for the breakout and trade in that direction the rest of the day.

It's funny in two questions you've described my approach. Just describing that price signature of

a predictable area, stops are likely below, price goes, grabs the stops and then goes in the

direction they predicted in a stop loss hunt. It's a dynamic I've explored a lot with many guests and

I've never come to a clarity of what's going on here because it gives the illusion that there is

a higher power in the market and they are coming to the inferior and exploiting them. What is the

mechanics of what is going on here because I see the signature all the time. That's a superb

question. Here's the answer to that. I've wondered about that for years. Hello, ladies and gents,

welcome back to another episode. I have to say, Samira, it's been a long time since I've been

this excited for an episode. Well, because I know I'm going to have a journey today with you and

we're going to explore a lot of things. I think it's a cocktail of a lot of insights and original

thoughts. Your career credentials, not only going from physicist to then publishing things to then

being a leading, I want to say, hedge fund manager, but then also being a non-conformist, which is a

wonderful mix. I'm proudest of the last. So it's going to make for a very vibrant conversation. I

want to kick off with a little bit of context on your journey because you've taken a career that is

not a typical route. The physics background that you have that you're still very much involved with

publishing and connecting that to finance and then obviously having success, whether it's

algorithmically and your strategy you want to explore. But you're going to have insights of

what's happened over the last few decades to arrive to this point. Yeah, so I actually started

off as an electrical engineer and I got my bachelor's in electrical engineering, but I

honestly didn't enjoy engineering very much and I really wanted to do physics. So I switched back to

physics, which is really what I wanted to do in the first place. I became a particle physicist at

the University of Texas and then we were building this thing called the superconducting super

collider, which is going to be a real physics experiment where we might discover something new.

The US Congress, as I say, Congress critters are infinitely wise in their infinite wisdom,

cancelled the project, which meant I didn't have a job and had to find something else to do.

So I became a trader. In October '93, I read this very beautiful article written by Matt Ridley in

The Economist called The Mathematics of Markets. And basically the article said that there's a

bunch of people now all of a sudden on Wall Street that are using mathematics to make short-term

predictions in the financial markets. And I said, "Ooh, that's interesting." And then it used the

buzzword chaos theory and I said, "Ooh, double ooh," because I'd published in Chaos Theory as a

graduate student. And I said, "Ah, this is fun." I'd read a lot of economics, so I said, "Well,

this sounds like nonsense. We know the efficient markets hypothesis. This can't possibly be true."

And of course I didn't have a job. So I started playing around with chaos theory in the financial

markets and very rapidly discovered that far from it not working, it worked very nicely.

At least theoretically. So since I didn't have a job, I figured, "Hey, I can do this." And so I

started my own trading company. And so the first thing I ever traded was the S&P 500 futures,

and I did that using chaos theory. And as far as I know, I was the first guy to algorithmically

trade the S&P 500 futures using some advanced mathematics, not just like moving averages or

something like that. And that worked quite nicely quite some time. So that's where I started as a

futures trader. Well, I want to begin with an open paradox I want to say, which is how can a trader,

the endeavor is obviously to make money, how can someone achieve consistent outcomes from

chaos theory, an inconsistent or a random market? So there are really two aspects to that. One of

them is psychological, and the second one is your edge. So the first thing you have to ask yourself

is everyone and his uncle is trying to make money in the market. So what exactly is it that you have

or that you think or that you can do that is different than other people? That then becomes

your edge. But the second problem is that you can, once you get reasonably good at this, you can find

more than one edge, but that edge then has to be congruent with your personality. If the edge is

not congruent with your personality, you will never be successful with the trading strategy,

even if it works. So I'll give you a perfect example. By and large, you can break trading

strategies up into two groups. They're either countertrend or trend, right? So breakouts are

trending, moving averages are trending. On the other hand, you have things like MACD and so on,

which are technical indicators that are countertrending. If something goes up, you short

it. Something goes down, you buy it. That's countertrend and vice versa. But the thing is that

when you have countertrend strategies, typically you make a lot of positive gains and the occasional

big loss. So you have a lot of positive trades. So maybe you're 65, 70% positive trades. On the

flip side, if you're trading, trend trading, you maybe make 30% positive trades or 25% positive

trades, but the positive trade will be like 19 times bigger than your losing trade. But some

people can't deal with being wrong five times out of six or four times out of five. So it wouldn't

work for them. So they'd get whipsawed in a moving average strategy, for example, and they'd just say,

"No, the seventh time I'm not going to take the loss." And that's the time it goes up 200%.

So you have to find the edge and then you have to find an edge that is congruent with whatever it

is that you can live with. And the reason the trading journey is so hard is that you have to

lose a lot of money to begin with to learn what A works and B works with your personality.

With this word congruency, what are the variables of types of trading personalities,

let's say swing trading, scalping or fundamental techno, all these variables,

but also then personality types of risk aversion or the ego to not being liking to be wrong.

How would you connect these so to know, "Okay, I'm X kind of person, I'm Y kind of person.

What should this lead me towards in terms of behavior?"

So the first question you can ask yourself is, if you're holding a position overnight,

do you get nervous? Can you sleep? Yeah. So then you would need to scalp or day trade.

The second question is, if you've had a bunch of losses in a row, do you freak out

or can you handle that? I think I'm pretty good at handling that.

You're pretty good at handling that. So you're probably in that case, just those two questions

already suggest that you could probably do intraday trend following. And most likely the

place that you would probably want to do this is opening range breakouts, which are fairly

successful in the equities. And we actually traded this for quite some time with Joe Ritchie in

Chicago, which was opening range breakouts on stocks. And you could basically find like a 10,

15, 20 minute range on many stocks, wait for the breakout and trade in that direction the

rest of the day. And you'd be on average profitable. It's funny in two questions,

you've described my approach, which is pretty interesting. Let's describe your personality

because I know you're pretty much the opposite. You're doing trades that are one year in duration

or maybe even longer. What is your personality and how have you connected that to your trading

behavior? Yeah, that's a great question. So my personality is that I actually hate having to

make decisions, which is a strange thing for a trader to say. And the reason I hate having to

make decisions is that I can always think of the nth variable that is not part of the n minus one

I just thought about. So I decided years ago that A, I'm a physicist, B, I like systematic stuff,

so I'd need to be a systematic trader. And so I've been a systematic trader forever. I started off as

a short term trader. But the issue is that I realized back in 2003 that alpha from short term

trading is going to become harder and harder and harder to achieve because there were more and more

people trying to do it. So efficient markets. Efficient markets. And there's only a limited

amount of alpha you can get anyway. And of course, the shorter term your trade is, the less money you

can run through it. Because you create the alpha decay. Exactly. You create the alpha decay by just

trying to take advantage of it. So I decided that I would try to become a longer term trader. And

then I said, you know, I hate having a majority opinion on anything, on any topic. It makes me

uncomfortable when people agree with me. Nonconformist. Nonconformist. Exactly. So what

is it that a systematic or a quantitative trader, equity trader would not do? And the answer is

twofold. One, increase that time frame to beyond a year. Nobody does that. And the second is stop

looking for alpha. And so I did both. And that's really what... Okay, let's begin with why is that

the majority consensus to not hold trades for that duration and so forth? Because by and large,

when you're trying to build a trading model as opposed to an investment model,

what you're trying to do is you're trying to find a dislocation in the market of some kind. And then

you're trying to find a signal of that dislocation. And then you're trying to find whether you can

put sufficient capital through that dislocation so as to be profitable. So I'll give you a perfect

example of this, by the way, which I think is still true. If you take, say, the S&P 500 ETF,

SPY, and you divide it up into its intraday return, open to close, and its overnight return,

close to open, you will find that more than 100% of the return of the SPY takes place overnight.

I.e., on average, the SPY goes down during the day. Interesting. Yeah, exactly. But taking

advantage of that is pretty difficult. And the reason is you can certainly buy market on close,

and then, yeah, no, buy market on close, sell market on open. You can do that. But there's

only a limited amount that you can do. That's the first issue, before you start to move the market

too much. And the second is, of course, that you are then subject to, the reason it's positive,

of course, is that you're getting paid for taking overnight risk. So that's an example

of an edge that exists in the market that's pretty difficult to arbitrage, and yet it's right there,

and you can see it in the data. Interesting. So on the other hand, if your trade is lasting more

than a year, whether it takes you an hour to get in or two hours to get in, or a whole day to get

in, you don't really care. And that's the arena I wanted to be in. We started to discuss with Joe

light speed limits, which is to say the amount of time it takes light to get from your computer to

the trading arena. And when we started discussing that, I said, I don't want to do this anymore.

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use the code TOT. Exploring this of extended time horizons, I'm not sure the correct way to phrase

it, but I want to basically say that as the time horizon extends, the degree of variance also

extends to the analogy of if I put a gun to someone's head and said, where is price going to

be in 10 minutes? You can have a 90% confidence it's a box about this big. If I say, where's it

going to be in one year? It's a much larger box. Because a lot of things can happen that are valid

today and you couldn't foresee as time goes on. How do you account for that? Okay, so that is an

absolutely brilliant question. And in fact, that's really the crux of, in my opinion, all of

trading. What I realized, I started off like essentially everybody else under the sun trying

to predict things. Short term market movements is in chaos theory. Alpha generation strategies for

scalping, breakout systems, whatever, these are all predictions. What I realized in my old age

with all this gray hair is you need to stop predicting things, you need to start reacting to

them. And so my system is actually reactive, not predictive. I don't predict anything.

But you're reacting to today's information and hoping that that today's information carries

through for maybe a year. Walk me through that. So what tends to happen, this is more true in

the equity markets than anywhere else. What tends to happen in the equity markets is the following,

this is not a well-known fact, but it should be. Take any line that follows the price of the equity

market at some distance. And the easiest is to just take a 200-day moving average because everybody

else under the sun does. It doesn't matter what you do. You can take any long-term line you want,

as long as it follows the price action. If you now ask what percentage of the return of the

market takes place when it's above that line, it'll generally be around 2/3. If you ask what

percentage of the risk takes place above that line, it'll generally be 1/3. And then vice versa,

if you look below the line, the risk will be approximately 2/3 and the return will be

approximately 1/3, more or less. These numbers are all approximate because it depends on the

line and so on. What that tells you is that the risk versus return trade-off is not constant.

And the mistake that I think large numbers of equity traders make, many times, by the way,

they know better, but they're forced by the risk management committees to do it anyway, is that

they are forced to take positions regardless of what the risk outlook is. And so you may say,

"What does that mean?" So I'll give you another example. I wrote a paper on this,

gosh, 20 years ago now. Supposing you take the correlation of all US stocks to the S&P 500.

So you take stock one and its correlation, stock two and its correlation, stock three and its

correlation, and you average it. And let's say the correlation is over the last, I don't remember

what number, it's 100 days, it doesn't matter. And you average the correlation today over the

last 100 days, and then you average it tomorrow and average and so on. As that average correlation

goes up, the rate of return of your long short strategies goes down automatically.

- Correlation to the S&P?

- Yeah. As the average correlation of the average stock to the S&P goes up,

the rate of return of any long short strategy is going to go down.

- Why? Because it's baked in, basically.

- It's baked in because when you're trying to make the difference in the return between the two,

as the correlation goes up, the difference in return comes down. But nevertheless, you are

forced very often by your investment committee or by your, what is the, I forget what the term is,

by the people that allocate money to you. That you're basically told, no, no, no, you can't take

advantage of this fact, you need to have your exposure on at all times. Similarly, the same

thing happens with mutual fund managers that are constantly frightened of being behind the index.

So they can't do things to actually actively manage the risk in that way. And so they don't.

- Does this imply a negative correlation to the S&P is favorable?

- Yes, if you could find one.

- Just trade non-correlated things?

- Yes. So the ideal thing would be, of course, to find a negatively correlated asset and stick

it in your portfolio along with the positively correlated asset, and the correlations will

offset. And in fact, the negatively correlated asset could even lose money.

But as long as it doesn't lose too much money, you're still better off. But that's very hard to

find. Very hard to find. So you try to find an uncorrelated asset, which is also, by the way,

pretty hard to find.

- What about this idea of being a non-conformist in strategy? What I mean by this is not necessarily

a non-conformist in price, because then you're just trying to pick the top, but more, let's say,

looking at the CO2 report, commitment of traders and seeing, okay, everybody is long, 95% of people

are long, therefore, who is going to carry that trend forward if everybody's already long? Therefore,

using positions as a reversal format, which would be, by definition, non-conformist.

- It would work if you could get the data fresh enough, number one. And number two, if the

imbalance was extreme enough that you would feel pretty confident about taking the opposite

position, 95.5 probably still isn't good enough, if I had to guess. I'm making this up right now

because I haven't tested it. I'd probably want it to be like 98.2 or something like that.

- Does that happen in real life?

- Very rarely. And in those very rare circumstances, like George Soros used to know this in

his gut, you take the opposite position. Like when he broke the Bank of England, remember, the

famous trade? That's exactly what he was doing, in effect.

- I want to explore the idea of self-fulfilling prophecy when it comes to the CO2 report, where

is the market truly random, or is it a law of cause and effect of human psychology, or is it a

law of cause and effect of the large money managers who, if they position a bias, that bias must play

out by virtue of the capital they put in?

- So all of the above is the answer. And so let's go through that in some detail. So the first is,

you have to, there's a guy, Joe Stieglitz, who won a Nobel Prize in economics, I forget when now.

Anyway, he came up with a, I think it's Sanford Grossman, I forget, anyway, Grossman,

the Grossman-Stieglitz paradox. And the Grossman-Stieglitz paradox is the statement that

the market, suppose the market was completely efficient. Well, then nobody would trade in it

because there'd be no point in doing so. So then no one would trade the market, which means it

would be inefficient, which means, of course, everybody would trade in it. So there has to be

a balance of inefficiency. Yeah, there's a pendulum, and the pendulum will presumably then

settle in some equilibrium where there's just enough inefficiency to make it worthwhile for

you to do the research to find the inefficiency, right? That's the Grossman-Stieglitz paradox.

So if you take that to its logical conclusion, the answer is, for your question, all of the above.

You have to do all of those things.

What is your thoughts on patterns, specifically, where, not necessarily pattern traders, but

in the randomness of the markets, there is predictable pockets because human nature at

certain extremes or certain situations will act in a predictable way. Is our job to find

inefficiencies or is our job to find pockets of predictability?

Both.

Okay.

It's our job to find anything that makes money. That's my position.

Which one do you prefer to exploit?

I generally try to prefer to exploit situations where I'm pretty sure that the statistical odds

are in my favor, whatever they are. It doesn't matter to me how I find them.

And also, I prefer not to exploit patterns that disappear when I exploit them.

Let's walk through what a pattern is, first of all, because a pattern can be correlation-causation,

but on top of that, it can also be something that is optically a pattern, but behind the

scenes in the orders, the behavior may be different to another time that pattern appeared.

What is your first of all thoughts on pattern traders?

So the first thing to think about is, as you just said, human psychology. So it is true,

and this has been studied quite a lot now in economics, people like to place trades

at round numbers. So you'll find more trades at zeros or fives or 2.5s than you will at

2.1. So 99.17 is going to have a lot less trades than 100.00, just as an example.

That's something you can exploit, no question. The second thing you can exploit is what the CEO

of Renaissance called "patterns that seem to repeat but have absolutely no good reason for existing."

Peter Brown, is that his name? He said these patterns are so completely illogical that if

you tried to get logic out of them, you would never trade them. And that's why we do,

and that's why they work. Now, maybe he's blowing smoke, I don't know, but it actually sounds like

it would work.

Does that imply a job of a trader is not to know why the market moves, it's simply to react

and not understand why it did?

Yes, because I think that we make a mistake as traders, and my biggest losses, by the way,

which we can talk about some of them, have come from thinking I understand things,

is from thinking that we need to understand stuff. Whereas it's a complex system, computationally

irreducible in the terms of my book, and because it is that way, it means that trying to understand

it is a futile quest, and you shouldn't try.

As a scientist, as a physicist who explores for answers, was this quite the confrontation

when you came into the finance world?

No, because I started off like everybody else, thinking there were explanations for things.

So I should actually tell you about my very worst trade. My very worst trade took place

during the dot-com bubble, and I may get the numbers slightly wrong, but the idea is roughly

correct. This was for my own account, because I was trading futures at the time, and stocks

was my hobby at the time. So I actually made 10% of my very worst trade, and you'll say,

"How can that be your very worst trade? What a ridiculous thing to say." Here's why.

I bought Siebel Systems, symbol S-E-B-L, at something like $5 split adjusted. I held it

to, I think, 120, I may be wrong, but something like 120 split adjusted, and I sold it at

550. Yeah, that's right. I was greedy on the way up, and then on the way down I kept saying,

"No, no, it's going to have to bounce. I'm just going to wait for it to come back up

before I sell it again." So I sold it at 550, when I essentially, to use a common term,

puked it out, because I couldn't take it anymore. That was the very worst trade I've ever done.

I've had losing trades which are not as stupid as that one.

Are you saying it's the worst because of the opportunity cost of what could have been?

Exactly, and also from the fact that psychologically I did everything wrong.

Everything. I identified the correct stock. I more or less identified the correct time to sell it.

I then didn't pull the trigger to sell it. Then I had regret over the fact that I didn't pull

the trigger to sell it, and then I kept having regret over the fact that the price was higher

the last week or two weeks ago or three weeks ago. As it plummeted down, I kept saying,

"No, I'm going to wait for it to bounce," and it didn't.

A very relatable story.

Absolutely. I've done it.

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I want to explore, therefore, on the back of this, an area that people don't maybe consider.

Obviously, everybody talks about risk, and they talk about my final take profit level,

but what happens in between, maybe it's a bell curve in the sense of it might go 5% to my target

and then reverse. It might go 99% and then reverse, and maybe it's a normal distribution.

Hence, people take partials at a certain point. How do you eradicate or minimize opportunity cost

in a system? Because it's very easy to say it's a breakeven, no loss, no harm. But then if you

have these pockets of 2%, 1%, 2%, that all went back to breakeven, at the end of the year, you've

got a huge amount of money that could have been. How do you navigate that?

The answer is you can go broke taking a profit. That statement is false, has always been false.

I don't know why people think this is a good idea. I think it's very stupid.

What you need to do is you need to... I'm a systematic trader now, completely. I know exactly

what's going to get me in, and I know exactly what's going to get me out, or rather my computer

does. But even if you're not a systematic trader, you need to know exactly what your exit

conditions are going to be before you enter your trade. You do not get to make it up as you go

along. That's the error. Anchoring back to what you previously said, does this not now bring on

the tones of predicting, not reacting at a level? No, you're reacting, you're saying in advance,

if you're trying to make discretionary trades, these are the types of conditions that if they

prevail are going to make me pull the trigger to get out. So the perfect example of this,

I don't trade like this, but the perfect example of this is William O'Neill's CanSlim system,

which is in a book I think called, what is it called, How to Make Money in Stocks.

I don't trade like this. It's not something I could do. But basically they have very specific

patterns they look for when they get in, and very specific patterns they look for when they get out.

And they have very specific rules for taking profits and so on and so forth.

The point is that if you have specific rules, even if those rules are things that you do

discretionarily, you can look back at your trade diary or whatever it is, you should always keep

one, to see what worked and what didn't work, and you can at least somewhat optimize what it is

you're doing or not doing. The problem is always when people don't have a clear plan. So this

happens with people that I advise all the time, friends, where they'll buy a stock and it goes

down and they say, oh, well, I bought it for a trade, but now it's an investment. No, I mean,

dude, it went down. It shouldn't have. Sell it. Some cause fallacy. Some cause fallacy.

Earlier when we were speaking before we started shooting, you were explaining how going through

data and sifting through financial data when you were a physicist and through your career had to

take that step. You uncovered certain things, patterns within the data. Can you share to me

what that was? Yeah. So, interestingly, the original system that I mentioned was using chaos

theory. And in chaos theory, what you do is you make the assumption that a physical system, if it

has behaved in a certain way historically in the recent past, then in the very near future, it's

going to behave the same way. It's a form of pattern matching, actually. And for chaotic systems,

which is a very specific definition, which I won't get into, but for systems that are technically

chaotic, that actually works reasonably well for short-term predictions. And that's what I was

doing in the financial markets on trading futures. Now, from having looked at large amounts of

financial data for more than 30 years, it becomes instinctive where you can look at the data and

you can say, hey, that's not noise. That is probably a pattern. So, like, for example, the

example I gave you earlier about the overnight versus intraday returns of the SPY, that's a

pattern. I mean, that's not noise. It's just not. Another one, by the way, is the congressional

effect, which has weakened over the years. But for the longest time, almost the entire return of the

S&P 500 took place when Congress was not in session, which tells you something about politicians,

but that's another story. But that was a real pattern. That was not something that was noise

again. Now, noise would be, for example, that again, for the longest time, stocks whose symbols

began with a vowel outperformed the market as a whole.

Wow.

Yeah, that's not a pattern.

No explanation.

No explanation. And that's not a pattern. I'm giving you simple examples, but if you do this

long enough, eventually you learn how to see a pattern. And so it turned out, this is what I was

telling you about earlier, that I have a physics paper coming out in a proper physics journal,

European Physical Journal, C, Particles and Fields, which I'm pleased to say will be out in

the next few weeks, accepted already, where I put my finance eye looking at a very peculiar set of

data, which is the mass of quarks. Quarks are the fundamental constituents of matter. They make up

the inside of protons and neutrons. And the pattern of their masses, the ratio of the masses of one

quark to another, there are six of them, has never been satisfactorily explained by anybody,

because they look at it and it's crazy. The heaviest quark is, I think, 13,000 times

heavier than the lightest one. No one knows why. And finance eye, believe it or not, I looked at

the pattern and I said, I think I get this. And it turned out, because the paper is now being

published and it's being peer reviewed, I was right. So I've actually found a pattern in the

masses of quarks as a physicist, yes, trained as a physicist with a PhD, but with a finance eye

applied to physics. I think that's pretty cool. Fascinating. And first of all, congratulations.

Thank you.

There's no small feat. What about the other way around, taking the physics mind and applying it

to finance? Any unique or certain insights you've had?

So the most important thing that you need to do as a physicist coming to finance,

well, you need to do two things. First is you need to be relatively humble,

which many physicists, me included, are not.

Why?

Well, because, you see, the reason you get into physics, in some cases, is because A,

you love physics, but B, it's because you are convinced in the very fiber of your being that

this is the highest intellectual challenge of mankind. And so you think of yourself as being

a pretty damn smart guy. And you probably are, for that matter. But the financial markets have

a way of humbling people that are pretty damn smart. And the reason is that there's what you

would call technically a lot of noise in the financial data. What looks like a pattern isn't.

And you need the humility to be able to understand that, unlike in physics, where if there's a

pattern, it probably is real, in finance, if there's a pattern, it probably isn't. And so you

need to study really hard to understand how to identify patterns that are real versus patterns

that are not real. That's the biggest thing that I would tell physicists getting into finance.

That's the place where you really have to be humble.

How do you also segment or come to the answer of what is a real pattern versus not,

if optically they are the same?

Yeah, so that requires an enormous amount of learning and background. So you need to read

a lot of books on economics. And you need to read a lot of books on finance. But then the

most important thing is you need to read them with a very skeptical eye to see where they're wrong.

And again, some of the stupidest things I've ever done in my life is when I've read an economic

theory and said, that makes a lot of sense, got it, I'm going to use that in the market,

and it blows up in your face every single time. Every single time.

Interesting.

You know, for example, people love to use risk models. So there's all kinds. There's

GARCH, and EGARCH, and REMA, and ARFEMA, and I could go on with all these silly names. And what

they're trying to do is they're trying to predict what the risk is going to be. See, we're back to

predicting it. And so basically, they're trying to tell you that the annualized risk of the S&P

is going to be 23% in the next month. Or they'll say, oh, it's going to be 6% in the next month.

There are two problems with this. Even though everyone and his uncle uses them, all the hedge

funds use them, the proprietary funds use them, the investment banks use them, the commercial banks

use them, it's crap. And it's crap for two reasons. It's crap, A, because those risk models work until

they don't. That is to say, until the shit hits the fan, they work great. When the shit hits the

fan, they blow up. And they don't react fast enough. That's the first problem. And the second

problem is that they are mistaking a exact prediction for reality. And I think it's Keynes

who said this. I'm not sure, but I think it's Keynes. These models would prefer to be exactly

wrong than approximately right.

Interesting.

It's a lot more important to be approximately right than it is to be exactly wrong.

And the way to deal with risk is to classify it, not to predict it. It doesn't matter.

The analogy I like to give is way back when Tiger Woods was in his heyday,

number two was generally Phil Mickelson. Question, was Tiger Woods twice as good as Phil

Mickelson, four times as good as Phil Mickelson, or eight times as good as Phil Mickelson?

Does it matter? No, he was just a hell of a lot better than Phil Mickelson. It's the same

thing. Is the risk high? Yes. Okay. Be frightened. Is the risk low? No. I mean, yes. Great. Be

aggressive. That's what you need to know. You don't care whether it's going to be 26% or 28%

or 29%. So technically speaking, what these people, the mistake they're making is that

they're trying to optimize what's called the root mean square measurement of error. And that's just

as silly because that's the wrong metric by which to measure things. Because what will happen then

is you're optimizing for getting things right 90% of the time, 92% of the time, 95% of the time,

but those 95% of the time don't matter. And the 5% of the time that do matter, you get wrong.

That's the issue. And that's just the wrong way to do things.

When we speak about risk, and off camera, you gave me a nice analogy of the

7% of funds and how in spite of that things happen. But I want to explore risk. You can

also look at it as each independent trade has an independent outcome. So therefore risk is

a collection of things that happen. But then when I bring the human element into it, well,

then there's conformational bias. There's a gambler's fallacy where the human connects the

string of losses to then affect future behavior. How do you factor that in?

That's hard to factor in unless you have a reasonably intelligent risk framework that

other people, i.e. not the trader, are running. But that has to be intelligent, not stupid.

And this is what I was telling you off camera. I have a paper coming out, I think this month,

in the Journal of Portfolio Management where I show that the most popular method of managing risk

at these pod shops, like Millennium is one of them and other places that hire pods of traders,

is just simply stupid. And it's stupid in the sense that it's statistically stupid,

they're leaving profits on the table. And I demonstrably show, so this is not even my opinion,

that in effect the reason they're successful is in spite of their risk management, not because

of their risk management. And so the issue is this. So the simple-minded way of managing risk

with traders is to say you have a drawdown limit and your drawdown limit is, pick a number, 8%,

10%, 7%, doesn't make any difference. And if you exceed that, you're out, goodbye.

You can show statistically that this is just dumb. And I do this in the paper by setting up

a scenario in which there is every advantage given to the rule and every disadvantage given to my

statement that this is a stupid idea. And I still show it's a stupid idea. And so what I did in this

is I took pairs of ETFs, I found specific periods with specific investment thesis for which ETF to

be long and which ETF to be short, and I picked the precise period where it was the most profitable

period for this pair of ETFs to be long one and short the other. So you just had to hold the trade

for whatever period of time it was profitable, trade it, and you would have a profit. And

remember, this is a perfect hindsight. And then I showed that if you imposed any kind of a drawdown

cutoff on it, you turned what was a certain profit, because you know it's going to be profitable,

into a loss more often than not. Why does that happen? Why is this a repeating thing?

The reason it's a repeatable thing is that you need to divide, you need to understand why a

drawdown occurred. So let's say, for example, you own a stock and some piece of really terrible

news came out, right? And the stock fell. Well, now, as the risk manager, you need to understand,

is it because this guy didn't do his due diligence, the portfolio manager? Is it because the news was

genuinely unexpected? Is it because this was some bizarre thing that happened to the supplier and

the person could never have anticipated it, etc. So I'll give you another example. Just not very

long ago, we had these, you know, strange tariffs that got imposed, right? All of a sudden,

overnight, seemingly by typing them into chat GPT, and then chat GPT gave some numbers and they

presented them in the Rose Garden, and the stock market, of course, collapsed. Now, if you've been

long the stock market, then, and you hit your 10% drawdown, were you a bad money manager?

The answer is obviously not. All of this needs to be nuanced. The problem is that the way these

people run their portfolios is not nuanced. It's silly. What I also mentioned to you off camera was

this perception that I and I think a lot of retail traders have is that the hedge funds have got it

all figured out. They have the insider information, they have all the resources, they have the top

talents, therefore, they know better than us. As I've spoken to more and more traders and people

that have the insight like yourself, the more I realize it's simply not the case. If you can shed

some light, like you have here on irrational behavior, what frameworks or disadvantages do

these large institutions have that work against them and things that we don't have to have to

deal with as an individual trader? Yeah, so that's a very good question. And I put this, if somebody

buys the Kindle edition of my book, in the back of it is three presentations, one of which is about

the future of AI and finance. And in one of them I say that one of the problems with traditional

finance, large hedge funds and so on, is that they hire the same people, trained by the same

professors, at the same schools, on the same strategies, and do the same thing at the same

time, and then they complain that they don't have anything unique. That's the fundamental problem.

What's happened to the hedge fund industry is that it used to be run by people like Michael

Steinhardt and George Soros and people like that, that A, were risking their own money,

B, understood something about the markets, and C, were very clearly people that had to and wanted

to take a specific position for a very specific reason, and they made concentrated bets, and they

basically bet that they knew what they were doing. And they applied good risk management, and they

were smart, and all the rest of it. What it's turned into is effectively, mostly, not always,

but mostly, a mechanism by which large pools of institutional capital are locked up into vehicles

that charge very high fees and do not produce any significant set of returns. And simultaneously,

what has also happened is that you now have this quote, "war for talent," unquote, where PMs are

getting these very large, guaranteed sums of money. But in most cases, you as the retail investor are

way better off than any of the institutions, because all you have to do to beat, essentially,

all of these hedge funds is buy the SPY and sit at home. And in the even medium term, you will beat

essentially almost, not all, but almost any hedge fund out there by just buying the SPY. So why

even bother investing in them? And that was that famous bet, which I've forgotten the details of,

George Soros and some hedge fund manager, you remember? Not George Soros, sorry, Warren Buffett.

He bet some hedge fund manager 10 years ago, 12 years ago, 15 years ago, some sum of money. I'll

get the details wrong. You can Google it. That this manager could pick any group of funds, and

Warren Buffett would pick the S&P 500. And then the bet was that over the next 10 years, this group

of funds would not beat the S&P 500. And of course, the S&P beat it by some ridiculous margin.

And this just keeps happening over and over and over. So the larger hedge funds are essentially

now vehicles for marketing and sales. They are not vehicles for actually making any money.

So an interesting inflection point I've reached in my career off the back of this is I've been

trading for next month will be a decade. And I've been through the whole journey and the whole human

experience of the market and everything it brings out of you. But after some time, I found a sense

of consistency. But my approach, as we explored earlier, is lower time frame, it's scalping,

it's in certain pockets of time. And it removed all the freedoms that I wanted from my life. But I

thought, look, this is the game. This is what has to be done. As I've got more financially mature,

I've taken an arm this year at investing quite significantly. One step that I did was,

let's say I had $100,000 in a trading account. Because I'm taking one trade at a time,

I'm never in two trades at once because I'm not swing trading. I was not utilizing the full

margin. And therefore, I realized 80 or 90% of my account is just dead weight, it's dead capital.

So I thought this year around the tariff time, why not take this portion out, maintain my lot

size or position size. So as a risk on the 10% that is left, obviously, I'm risking more. But

as an overall of my portfolio, I'm risking exactly the same. The reason I take this money and put it

into the S&P and Tesla, fortunately, gold and just diversified. And now that five months later,

after the tariff thing, I've realized on my 90% of my account that I just put into investments,

I'm up like aggregated about 25%. Obviously, it's a fortunate win. But it just makes me think,

why bother? Like all the effort that now I've also been a bit hands off in my trading,

because I'm making this money here, I no longer chase the market. And as I extend it out to the

conversations that I've had, and I reflect on certain conversations I've had with others,

the largest of money managers are not in the lower time frame, or in the scalp intraday,

they just take position trades. And then all of this, after you said all of this just makes me

think, why bother even attempting to day trade? Or why bother even to manual trade? When you have

the beauty of indexes and such forth? What is your reflection on that? I agree with it essentially

100%. And this is why in my own, in the funds that I run, we must be the only hedge funds maybe

that don't care about alpha. So, you know, it's pretty, pretty funny, but it is true.

What do you care about?

Risk, and only risk. So basically, my idea way back when, was 20, more than 20 years ago now,

that what is being arbitraged away is alpha. What cannot be arbitraged away is risk, because risk is

generally a pylon. A sells, so B gets a margin call. B sells, so C gets a margin call. C sells,

so D gets a margin call, and so on. You can't, there's no way of stopping that from occurring,

so there's no way of arbitraging it away. All you want to do really, is figure out periods of time

when that's likely to happen and be out of the market if you can. And so my idea was, I'll use

all of these risk models that I just spent 10 minutes criticizing, and I'll basically see what

the risk is, and if the risk is high, I'll be out of the market, and if the risk is low, I'll be

long and levered. That was the idea, and it would work every, you know, work two, three, four years

in a row, and then it'll blow up. So I, after a while, I got fed up of things blowing up, and I

would talk to people on Wall Street constantly saying, "Hey, dude, this blew up." And they would

always say, always, always, literally always, there wasn't a single exception to this, they

would say, "Yeah, that's a once-in-a-lifetime event." And I would always say to them, "The

lifetime of who? A lab mouse? I mean, seriously." And that's when the realization hit me that this

is the wrong way to do things. You shouldn't be forecasting risk, you should be reacting to it,

classify it. So first of all, are you referring to Black Swan events as the once-in-a-lifetime

thing? Well, they're not really once-in-a-lifetime events. They're like, for example, every so often,

the S&P will drop 30% for no reason at all, right? Well, okay, so you can identify a reason, but

like, for example, the COVID crisis hit, right? So you can say it's the COVID crisis, but on the

other hand, it's not like we didn't know that there was an infection that was about to go around

the world. So why did it drop 30% in 10 days? Why didn't it drop 30% over two months? Why didn't it

drop 40% over six months? I mean, it could have been anything, it just happened to drop 30% over

20 days, I think it was. Happy to say I was out of two-thirds of it. But that's the point, is that

if you had had a risk model and you'd been running it every day, and you had been basically trading

through the COVID crisis, you were dead. And even the very best hedge funds, Renaissance is a perfect

example, were not able to trade through the COVID crisis properly. They got out too late and they

got in too late. And that's again, because they're trying to forecast risk, they're not trying to

react to it. You mentioned a moment ago of something that is low risk and high risk,

which is a sense of prediction, or how are you correlating high and low?

In my specific case, what I'm worried about is the risk of a drawdown,

risk of a large drawdown in the S&P. Because that's what I worry about. But obviously,

if you're trading something else, it's the risk of a large drawdown in whatever asset you're trading.

So it turns out that risk is pretty predictable in the stock market, in the sense of not, I can

tell you what it will be tomorrow. But I can tell you that if certain conditions obtain,

then the chances that the S&P will fall a significant amount have just gone up.

And if those conditions don't obtain that the chances that the S&P will fall a significant

amount have just gone down. And that's predictable, and that's consistent, and you can see it

throughout history. And that's sort of my edge, is I know what those conditions are.

You told me through the dance that people do, where they bring in psychology, and then they

bring in mechanical systems or something objective, and then human discretion, subjectivity, intuition.

It creates a whirlwind of differences of opinions. What is your take on it,

specifically because you are quite systematic in your trade?

I don't like it. In my opinion, you need to either be a discretionary trader that has certain inputs

that you look at, and then you go with the psychology from, you know, there are lots of

people that teach you how to deal with trading psychology, how to deal with losses, and so on.

So you look at those indicators, and you try to be consistent. Whenever these indicators are in

a certain mode, I'm going to do a certain thing. And then you just do that. That's one way of doing

things. The other way of doing things is the way I do it, which is you write down very specific

rules, and those are rules you follow, and that's the end of the discussion. And if you don't like

the rules, well, then you've got to go back and change them. You don't get to say at the last

second, I don't like this trade, I'm not going to make it. That's not acceptable. And I've never

done that. So why have a system that is still manual, but systematic, as opposed to completely

automated and remove human elements? Yeah, so, well, it depends on what you mean by human elements.

So in my case, the system is, it tells me what to do. I just have to actually enter the trade to do

it. But there is that last thought of, should I? And the human filter. Yeah, I don't do that. And

that's a lens of emotion. I don't do it. Okay. I absolutely, over the years, I've trained myself

out of it. If the system says to do it, I just do it. If I have deep misgivings about what the system

is telling me, I'll still do it. Then I'll go back and I'll do the research and see if my misgivings

are justified. If what I'm saying is correct, if there's a way of improving the system, whatever,

that's a different question. That's a research question. It's not something that you're allowed

to do at the moment of making a trade. That's wrong. So easier said than done. Easier said

than done. How do you have the discipline or the mental frameworks to be able to act when maybe

your gut is saying otherwise? Very, in my opinion, it's very simple in one sense and very difficult

in another. The very simple aspect of it is you have to write down the rules yourself. You have

to program the rules yourself and you have to test the rules yourself. And you have to test them

every single which way you can think of, try to break them in the nastiest way you can think of.

And I'll give you some examples of how to be nasty to your own trading rules in a second.

But you need to be really nasty to them and try to break them. And just keep trying to break them

until you really throw your hands up and you say, "I can't take this anymore. I can't break them."

That's what you really have to do. So I'll give you some examples of how you try to break trading

rules. So one easy way of trying to break trading rules is to add noise to your inputs. So

essentially, let's say that you've got, I don't know, three pieces of data. You're going to take

the difference between the Fed funds rate and the 10-year treasury. You're going to take the current

trading volume in the S&P 500. And you're going to take, what's another good one, the distance

from the 50-day moving average. Just making this up, right, just on the spot.

Now, all of those require inputs. Take the inputs, which are presumably sitting in CSV files or

something like that. Write a little program that adds noise to each day, random noise,

from some reasonable distribution. Now you've got a data series that has noise added to it.

Now run that through your system. What you should find is that your returns should

with small amounts of noise, it should be unaffected. And with large amounts of noise,

it should start to degrade. And what you should see is that there's a curve that degrades as you

add more and more noise to the system. That's what you really want to see. What you don't want to see,

and this is what happens with most systematic systems, is something like this, where some

amounts of noise produce a good result and other amounts of noise produce a bad result. That doesn't

fly. - Why would that happen?

- From the fact that your original system is not real. You fitted noise, you didn't fit data.

- You fitted noise, you didn't fit data. - Yes. Which means you never really had an

advantage. So the classic example of this, which people still do, beginning traders particularly,

is they'll take, say, some agricultural commodity, and they'll say, "I'm going to trade a

moving average system, a moving average crossover system." And then they'll try every single

combination of the two moving averages until they find the quote "optimal moving average."

That is almost never going to work. And you can see that from the fact that if you just added

some noise to the system, that optimal moving average wouldn't work anymore. And you'd get

something that looked like this. So that tells you that the system has a problem. That's just

one example. So you have to stress, you have to really say, "I'm going to try to break my system.

I'm going to really try to destroy it in any way that I can." And once you've run out of ideas for

ways of how to destroy your system, you probably have something that will work.

I think off the back of that legwork that you have to do, you're only left with confidence

because you've got so much data behind you. You've got so much testing behind you that when

it comes to an opportunity in the market, you probably won't think twice because you've done

the foundation work, probably what most avoid, and therefore feel the emotions in the moment.

Have you done a lot of things specifically for your psychology or is it all the data behind you

and all of the numbers behind you that enable you to act in a sound way? It's entirely the fact that

I've done the work. I think it's sort of like being a professional athlete. You go into a match,

you don't know whether you're going to win or lose. But if you've worked hard enough on whatever

it is that you're trying to play, at the end of it, that's all you can do. And whatever's going

to happen is going to happen. You always have to be careful how much you risk, obviously. That's

obvious. You should never be risking 100% of your portfolio, sorts of things. That's stupid. All the

people do it. And you have to be willing to basically be very upset. I mean, I've had losing

periods. I had a losing period in 2022. In 2022, I had seven straight trades where it looked to me,

to the system, I say me, but it's the system, that it's time to get back into the market.

We missed the first drop by the way in 2022. It was great. It looked seven straight times, like

this was time to get back into the market. We took a small position and then the small position would

get hit by a 7% drop the next day or a 5% drop the next day. And it happened seven straight times.

I was tearing my hair out by the end, but I wasn't, I was just upset, but it wasn't like I was

not going to take the next trade. - Because this is a point where the beginner trader and someone

with experience shines. And that is, it's better to do the right thing and get a bad outcome,

than do the wrong thing and get a good outcome. - Yes. - Explore why that is so dangerous,

because I know even myself, I used to do it all the time. I took a trade I shouldn't have taken,

ended up being a win, confirmation of bias, I'm going to do that again, because you're incentivized

to. - Yes. Actually, you just said it. That's the real reason. The thing is that you have to

understand that trading is meant to be a business. It's meant to be something you make money from.

It's not meant to be exciting. I want my life to be as boring as possible. I hate excitement. I

don't want any, nothing, thank you, nothing. I don't want to be happy, I don't want to be sad,

I don't want anything. I just want to essentially be able to ignore everything as much as I can,

for mental equanimity. And if you have not put yourself in that state, that's when you're going

to run into problems. You have to be in a state where your system is set up, your risk controls

are set up, your trading rules are such and so on, that you basically just trade it and move on.

Do you believe there can be an idea of, a trade idea that is setting up,

systematically in your case, that you can call a high conviction play?

And would you modify your risk in a high conviction play?

Yes, but what I would tell you is that you should have already built that into your rules.

And I have.

So you would have categories of trade types, say this is my A plus and so forth down.

And how do you, do you maintain risk and allow large numbers to play out?

Or do you say high conviction equals higher risk, worse off set up, it still has an alpha,

less risk?

Yes, that's exactly what you do. So basically based on the expected reward and the expected

risk, you have to do your position sizing. And so the most important thing there is figuring out,

based on whatever it is that you're doing, what your sizing is going to be.

And generally speaking, the best way to do this is to use the Kelly criterion,

which is the optimal trade sizing criterion, and then take a very small fraction of that.

What is this?

So the Kelly criterion is basically, if you have a series of trades, a series of wins and losses,

what percentage of your capital should you risk on each trade to get the maximum growth?

The problem with the Kelly criterion is that if you actually follow it,

your drawdowns are like 95%. No one's going to live through 95% drawdowns.

But the nice thing about the Kelly criterion is that it is in some sense statistically reasonable.

And because it's statistically reasonable, what you can do is say, I don't want 95% drawdowns,

but I'm willing to live with 45% drawdowns, say. If you're long the stock market,

you're willing to live with 55% drawdowns, actually.

So you say, fine, I'm willing to live with 55% drawdowns, so I'm going to have my position set

up such that my maximum expected drawdown when lots of things go wrong is 55%, say.

So that's how you size your positions.

So you've already thought about your worst case, series of trades going wrong, everything not

working out the way you want it, and you've sized your position such that

you're not happy, but you can live with it.

And why not take the opposite approach, which is just standardized risk for every trade type

to kind of even out the highs and lows?

So that's effectively what you're doing when you do that.

So the issue is the following.

When you're a long only money manager, for example, or even if you're a long short money manager,

one of the problems that you've got is you're not sizing your gross position size

based on what the market risk is.

So if you're a mutual fund manager, you're expected to be 100% invested all the time.

So there's no position sizing taking place there.

All you can do is move your stocks around.

That's sort of the wrong way to do it.

You have to actually be free to vary your position sizes.

And the reason you're varying your position sizes is what you're trying to keep constant,

in some sense, is the expected drawdown of your portfolio.

So to give you a perfect example of this, remember I said 2/3 of the risk, roughly speaking,

is generally when the market is below some long-term line?

What that means is that even if you have a positive expected value trade

below that long-term line, if you're trying to keep your drawdowns limited,

you should actually be limiting the size of your position when you're below that long-term line.

So if you were going to invest, say, 50% above the line, you should be investing,

I don't know, 25% below the line.

Because what you're trying to do is to keep the risk, roughly speaking, constant.

So there's standard deviations on where prices, how you modulate risk.

I try not to use standard deviations.

And the reason I try not to use standard deviations, although sometimes you're just

forced to, is because that assumes that the returns are normally distributed, and they're not.

And they are most certainly not.

They are what's called in the industry leptokartotic.

And what leptokartotic means is that if you overlay the distribution of returns

over a Gaussian distribution, the peak will be thinner and the tails will be fatter.

That's leptokartotic.

Extreme things happen more often than you expect,

and little things happen less often than you expect, versus the normal distribution.

So that's the issue.

That's why you have to do it that way.

So I try not to use standard deviation, because standard deviation is really a measure of the

width of a Gaussian distribution.

It's not a good measure of a leptokartotic distribution.

And there's also some good evidence, by the way, to suggest that the standard deviation

of the stock market is not defined.

It might be infinite.

Should I go there?

What does that mean?

What it means is that there are all kinds of technical mathematical points that come

with trying to define what the width of a distribution is, because it's like this,

and there is a certain point at which you say what the width is.

But if the width can go out almost any distance, then it's not clear what its width actually is,

or what you should really be measuring.

And so a stock can only go down 100%, but it can go up--

Infinite.

--infinitely, right?

If you were short Tesla all this time, you're crying, right, unless you got the timing exactly

right.

So what good would standard deviation have been to you when trying to measure the risk

in Tesla?

The answer is it wouldn't have done you any good at all.

When you are operating a hedge fund, there's a lot of things to do.

And in this city where we are right now, there's the flash offices and the excessive teams and

everything that goes on.

And that's how they justify their management fee, I'm sure.

But then obviously it means you can't be as adaptable.

Changes come slow.

There's a lot of bureaucracy.

The approach you've taken is, it seems like, it's a very lean team.

Dare I say it's just a handful of people, maybe less.

Yes.

Explore to me your philosophy on being a hedge fund and competing in the same arena,

but doing it in such a different way down to team and resources in terms of you could

hire the best talent and you could do a lot of things.

Why do you choose not to?

Well, for multiple reasons.

The first is I'm frightened of groupthink.

And as I said to you earlier, I get very uncomfortable when people agree with me.

It's just my nature.

And then if somebody says to you, well, I'm also contrarian, so we'll agree to disagree.

Well, then I'll want to disagree with that too.

So I like to disagree with myself as well.

So put that aside.

That's the first thing.

I'm very scared of groupthink.

The second thing is that to launch a hedge fund in that way requires, as you just said,

a fancy office, $200 million of capital, a large team, huge expense on Bloomberg,

Tumblr, and all the rest of it.

And at the end of it, no great guarantee that you're going to succeed.

So what ends up happening in these cases is that essentially what people are doing is

they're playing with what I call OPM, other people's money.

If you're good at raising OPM, then essentially what you do is you pick up pennies in front

of steamrollers.

Now, what does that mean?

What that means is you try to make bets such that the upside is all yours and the downside

is the client's.

So effectively, let's say you're down for the year, swing for the fences.

Who cares?

If you're down 10% or you're down 30%, it doesn't make any difference to you.

You're not getting your incentive fee anyway.

And if it's down 50%, you shut the fund and go raise the money for somebody else the next

time.

That's what they all do.

That's a way of maximizing, in some sense, your own some sort of expected utility.

But that's not the way of somebody who's a lifetime trader like me or some of the people

that I worked with like Joe Ricci.

For us, this is what we do.

We're traders to fiber of your being sort of thing.

And we can't do that.

So I don't want to be in a situation where I have to do things because a risk committee

said I have to do them or because there was some mandate that said you need to be 100%

invested or whatever.

I want to do that which makes sense, is statistically palatable, where the risk is tolerable,

where I'm not doing anything insane.

And I want my clients to think that because I'm in the same boat with them, my capital

is at risk too, that I'm never going to do anything that's going to be nutty.

And so far, so good.

I mean, it's worked very nicely.

But that's why I don't want to do it that way.

Should trading or let's say should optimal trading be a lone wolf sport where you don't

allow an echo chamber of group thinking?

Or should you and can you benefit from accountability or externalizing risk and the kind of benefits

that may come from a trading floor environment?

It depends on your personality.

OK.

Very much.

It doesn't fit my personality.

The reason it doesn't fit my personality is that in the past, I worked with some people

where they were very smart people.

I liked them.

We got along very well.

But they liked to argue.

But the problem is that when you have a trading idea, even if it's going to be a systematic

trading idea, it's very nebulous.

It's not at the moment well-formed.

It's somewhat intuitive, whatever it is, until you've tested it and stress tested

and all the rest of it.

And the argument for me doesn't help.

I don't need somebody to be skeptical.

I'm already being skeptical.

I don't want to lose money.

Thank you very much.

What I need is somebody to tell me if I'm forgetting something important or something

that I may not have thought of.

Blind spots.

Yeah, blind spots.

And so one of the problems with the institutional structure is it's actually designed for cookie

cutter outcome.

It's not designed for really nuanced thinking.

And so what my business partner and I do now is very different.

I can't remember the last time we ever had an argument.

We're basically just trying to think through everything in the most rational way we possibly

can and then do the best we possibly can and then move on.

And that's it.

That's really all you can do.

And I don't think the institutional environment, for me anyway, is conducive to that.

The other problem is that pretty frequently in one of the institutional environments,

you are made to do things that you know are a bad idea.

And that would drive me bananas.

I couldn't take it.

I'd scream.

Can you elaborate on that?

So a perfect example is a set of papers written by Andre Schleifer in the 1980s, early 1990s,

economist at Harvard.

For the longest time, there was this company, Royal Dutch Shell.

And I'll get this wrong again.

Royal Dutch, I think, perhaps was traded in the Netherlands.

Shell, I think, was traded in London.

I think that's right.

I could be getting this wrong, but the idea is right.

You would have situations where the two prices-- and it's the same company--

were massively different.

So you had what looked like a free arbitrage.

But here's the problem.

Many people did the arbitrage.

Many people had their heads handed to them.

Here's the problem.

Just because it looked like a free arbitrage doesn't mean it was one,

because you needed to ask the question, why did this arbitrage open up in the first place?

What are you missing?

And in an institutional environment, that doesn't happen.

And so another great example of this is long-term capital management.

You remember in '97 when they blew up and basically blew the world up?

The reason that they blew up, despite having a Nobel Prize winner on their team,

is that they were arbitraging on-the-run and off-the-run treasuries.

And basically what happens is the Treasury issues, say, 30-year bonds

and issues them periodically.

And whatever one it just issued is the fresh bond, and that's called the on-the-run Treasury.

The instant a new set of bonds is issued, that's the bond now that everybody trades.

And everybody stops trading the old bond, even though it's essentially identical assets.

And so what happens is that the two assets diverge in their yield.

And so the idea in long-term capital management was these are two identical assets.

Financial theory tells us they're exactly the same.

They're trading at different prices.

We should arbitrage this and leverage it at 40 to 1, which is what they did.

What they forgot is that there's a liquidity risk.

And the liquidity risk is that because no one's trading the off-the-run bond,

it can go off to some other random price, and there's nothing you can do about it.

And if you're short it, you're dead.

And so that's exactly the point.

And so one of the problems in institutional-type money management is that

because they have cookie-cutter processes, they're not able to deal with the nuances

of actually how you handle real-life risk situations.

And that's why my paper in the Journal of Portfolio Management,

you have a 7% or 8% or 9% drawdown cutoff,

because you can't be bothered to actually do things properly.

And if it works, it works, I guess, but it's silly.

What is the difference between a trading plan and the systematic rules you may have

versus what you're referring to here as cookie-cutter mentality that is holding you back?

Um, yeah, that's a good question.

The answer is that trading rules are set in a specific time frame

for a specific asset in a specific way to produce a specific outcome.

The cookie-cutter rules are not like that at all.

The cookie-cutter rules are not specialized for a given market.

They're not specialized for specific volatility.

They're not specialized for a given market.

They're not specialized for any of this.

They're just cookie-cutter rules.

And so what the other thing that, of course, happens, as you would imagine,

you know, people rationally say, "Okay, well, I can't lose more than 7%

and they've allocated me, you know, $500 million.

So I tell you what, I'll pretend the portfolio is $50 million.

So then I'll never lose more than 7%."

But that's just dumb again.

Why would you do that?

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Can you give me some examples of what could be deemed a cookie-cutter approach,

but in terms of a retail trader?

Just to give an insight of what maybe is coming to my head of,

you know, you're told always do 1% risk,

or buy and demand, sell and supply,

or, you know, there are certain rules that you hear very often,

which seem like they're embedded in logic or truth,

but that can actually be holding someone back.

Yeah, so the problem with all of those truths is,

what is the indicator of demand and supply?

What are you going to look at?

What is it that's going to tell you

that there's an excess demand or an excess supply?

Previous price points.

Maybe, maybe not. Have you tested it?

Do you know that it's true?

Have you looked at a thousand charts?

Have you made sure that this always is the case,

or frequently is the case, or whatever?

So that's the first question.

The second question in terms of don't risk more than 1%,

don't risk more than 2% or whatever,

is again, you need to, let's say that you're going to be a chart reading trader.

Then you need to have a thousand charts,

two thousand charts, five thousand charts,

and you need to go through them by hand,

each and every one of them,

and without bias, which is hard,

figure out what your entry and exit points would be

and write down why you thought that was the entry point,

why you thought that was the exit point.

Don't worry about the P&L yet.

Then take the thousand charts

and then look at what the sequence of trades was,

what could have gone wrong,

you know, what your reasoning was, all the rest of it.

That's hard to do.

That's why it's better to do it via computer.

But if you want to do it by hand,

you can absolutely look at a thousand charts.

William O'Neill did, you know,

how to make money in stocks, the guy that I mentioned.

I don't do that.

But he looked at something like a thousand charts, probably,

to figure out his trading system.

How can someone use now AI to their advantage

to do this kind of heavy lifting?

Yeah, so that's a very good question.

It's a little hard to get started,

but once you're started, AI is a massive help.

So what do I mean by that?

You have to have some direction in which to point the AI.

So what are you going to ask the AI, number one?

And number two, how are you going to judge

if the AI's answers make sense?

Right, those are your two conflicting goals.

Those are your two conflicting problems.

And to be able to even ask the AI questions

and judge the answers, you actually need to know something.

Now, how do you know something?

Well, there's only two ways of doing it.

First is to read lots and lots and lots of books.

Which I did when I started.

And economics papers.

And the second thing that you need to do after that

is you need to start actually trading with real money

in the market.

There's no substitute for that.

And expect to lose money, period.

For what game?

Just market experience?

Market experience.

You need to understand two things.

You need to understand how to lose money

and what your reaction will be to the loss

and how you're going to act.

And the second is you need to understand

what it is about your logic that went wrong

that caused you to lose money.

And be able to distinguish bad luck from bad process.

And this is why we come back to what you just asked earlier.

This is why bad process is such a disaster.

It's because you didn't learn anything from it.

In fact, you learned the wrong thing from it.

And undoing things is much harder

than doing them in the first place.

Or you may focus on building good psychology.

But if you're building good psychology on a flawed system,

you're corrupting yourself in essence.

Yes.

What about the third one that came to my mind here

of like a valid loss, where you have wrong behavior,

right behavior, wrong outcome, and then just a valid loss?

How do you navigate that in a system?

Or how do you identify that compared to the other two?

So the way you identify a valid loss is by asking,

did you follow the set of rules

that you were supposed to be following?

And if the answer is you did,

then really you just have to be upset about it, but move on.

So what's the point of market experience to that,

then try and train an intuition

or notice subconsciously patterns,

but then stop yourself to actually act upon it in any way

because that would introduce an invalid loss.

No, it's more that you want to train your intuition

to figure out what the valid patterns are.

Okay, it's in the building phase.

It's in the building phase.

And you don't want to build your building on shaky foundations,

let's put it that way.

And the purpose of losing the money is to find out

where the foundations are shaky.

Because you never learn anything really from making money,

you only learn it from losing money.

That's what I've learned in my years.

What is your thoughts on traders that you often use

justification of a trade, or probably you see it

in the professional money management space too,

to justify behavior and say it was my market experience

or my intuition led me to take that behavior,

which is why I can't fully explain why I took that behavior,

and it was a positive outcome, so what does it matter?

That's most, well, it depends who it is,

depends why they're saying it,

depends, very context dependent,

but it's not necessarily a wrong answer.

It could actually be the right answer.

See, that's the thing I was saying

about nebulous trade ideas.

It can be something you can't really explain,

but you do it anyway.

Like George Soros used to say that when his positions

were bad, he got a backache.

And whenever his back hurt, he knew he had to exit

his positions.

This is his famous story.

But to get to that state, you need to have had

a lot of practice.

It's not something that is gonna come to you

without having done a lot of trading and practice

and learning and so on.

In general life, in pursuits of mastery,

you end up arriving at subconscious competence.

You end up in a flow state, some may call it,

where you, like I'm having this conversation with you,

I'm not necessarily focusing on how I move my hands.

It just intuitively happens.

Is this something you can arrive to in the markets?

And if you do have any subconscious competence,

is that not also a way to describe,

it's a gut feeling that I can't explain,

so I haven't bought or haven't got enough clarity

on my thinking process, because if I can't explain it,

maybe I don't truly understand it.

What is the difference between flow state,

subconscious competence, and you haven't quite

understood it enough yet to define it?

That's essentially unanswerable,

except by looking at your returns.

So it's exactly the same problem that, say,

a tennis player has when they're trying to climb the ranks.

Are they ever going to be good enough to be world number one?

They don't know until they're world number one.

There's just no way of knowing, can't be done.

You don't know that until you look at the results,

and the only thing that tells you

if you're any good is your results.

And if your results are good,

and they're reasonably consistently good,

then you need to develop the confidence that,

"Hey, my intuition does know kind of what it's doing."

And then what you have to do is

you have to be very careful of two things.

You have to be very careful of overconfidence,

which will lead to over-trading and too much leverage.

And the second is allowing that confidence to become fragile.

What is the place of ego in the markets,

where, as you just mentioned, overconfidence,

overzealous, over-risking,

but then there's also the side of ego,

which is self-preservation,

but then it's also identity of, "I want to be right."

How do you harness ego

as opposed to letting it be to your detriment?

That's a great question.

I forget who said this,

but it's one of the market wizards' interviews.

And he said, "Everybody gets from the market

that which they want."

And I think that's really true.

So your ego has to be focused, really,

on what it is you want from the market.

Are you looking for excitement?

Are you looking for a diversion?

Are you looking for a gamble?

What are you looking for?

Are you just looking to make it

as literally boring as you possibly can?

And my personality is,

I have a hundred other things I would like to do.

I want to make my trading life as literally boring as it can.

On almost any day,

you should not be able to tell

whether I'm making a loss or a profit.

I shouldn't even be able to tell

whether I'm making a loss or a profit.

And I should just be able to ignore

what's going on completely.

That's the state you want to get into.

If you're going to make trades,

forget about whether they made a profit or a loss.

Just make the trade because it made sense.

Hard to do.

How long have you spent building your system?

Because you mentioned earlier to me off camera,

the idea of you spend years building it,

testing it, and trying to break it.

And then you have a viable product.

And then you're continually adding and refining

until it's like marginal gains

and you reach a plateau.

Thereafter, does the market evolve?

Have you seen market changes or alpha decay?

Or certain things that means

you have to now go back to the building blocks.

And if that is the case,

upon what time horizon versus,

this is a valid loss versus no,

this is my edge decaying?

Yeah, that's a good question.

So because I'm really risk focused

as opposed to edge focused,

that's much easier for me than it would be otherwise.

Because alpha decay is the hardest thing

in the world to figure out, by the way.

It's really difficult to know,

particularly when you're running a long short portfolio,

which I've done obviously in the past,

why it's not making money.

It's really hard.

You can make up stories,

you can do tests,

you can run regressions,

you can do all kinds of things.

But at the end of the day, it's just a story.

You really don't know.

That's the truth.

It's a little bit easier

when it comes to figuring out risk.

And the reason is that the drivers of risk

more or less remain the same in the market,

more or less over the long term.

They don't really change.

The only thing that I have seen recently

over the last couple of years,

where you sort of scratch your head and say,

"Huh?"

is the yield curve.

I think it's Campbell Harvey that discovered this

like 25, 30 years ago.

Whenever the yield curve is inverted,

a recession invariably follows.

And also because the recession invariably follows,

the S&P invariably goes down.

We've had an inverted yield curve now

more or less for two years.

Not a whole hell of a lot has happened.

Yes, we did have the market decline,

but that was identifiably because of the Trump tariffs,

nothing to do with the recession.

So that doesn't count.

And then the COVID decline,

was that a recession decline

or was that a COVID decline?

I don't know because the yield curve

was inverted at the time.

So is that a successor of failure?

I'm not sure.

That is the one indicator,

which is a risk indicator that we do look at,

where you look at it like that and say,

"Hmm, I'm not entirely sure."

So that's one we're just seriously looking at

and thinking about as hard as we possibly can.

The safest thing to do is to not ignore it.

So we don't ignore it.

But that is one where there's been some change in the market

for which I can give you a hypothesis,

but it's merely a hypothesis.

But here you're basically trying to differentiate

correlation and causation.

Yes.

Was it COVID or was it the yield curve?

Yes.

Okay.

How do you, in general,

what is the process to differentiate

in many, for example,

in forms of technicals, correlation and causation?

Usually economics.

Okay.

You need to really focus on what the economics,

and I mean economics,

proper economics, academic economics,

what the rationale is from economics

for whatever statement it is that you're making.

And you also need to understand

which particular school of economics it comes from.

So you'll have people that are very good traders

that are Austrian,

follow the Austrian school.

You have very good traders that follow the Keynesian school.

They're very good traders.

They're neo-classical or whatever.

But what they've done is

they've taken whatever insights you can get

from that form of economics,

and then they've used that to inform

their view of the world,

but still understanding what the limitations

of that view are.

So you really have to use economics

to figure out whether something is real

or whether something is not real,

because finance will not tell you.

I think it's very clear to say that

fundamentals or economics, geopolitical factors

on a long-term horizon will drive price.

On a short-term horizon,

can technicals,

in a self-fulfilling prophecy kind of way,

determine what price will do?

Define technicals.

We came to a level of support,

and therefore a herd mentality.

A lot of people may buy on that support

or a trend line or a demand area.

And therefore that will happen

not because of fundamentals,

but because of the technicals.

Yes, it can.

Our studies suggest that it does,

but it is, as best one can tell,

a fairly short-lived effect.

So for example, if you find a channel,

and there's been a lot of times

when the price has bounced off a certain level,

there's a very good chance

that there's going to be a bunch of stops below.

So if the market drives through those stops,

it's a nice short-term scalp to short here,

wait for it to fall a bit,

and then buy it back.

Great.

Absolutely.

That's true.

It's much harder to justify that

as being a long-term statement.

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So just describing that price signature

of a predictable area,

stops are likely below,

price goes, grabs the stops,

and then goes in the direction

they predict any stop-loss hunts.

It's a dynamic I've explored a lot with many guests,

and I never come to a clarity of what's going on here

because it gives the illusion

that there is a higher power in the market,

and they are coming to the inferior

and exploiting them.

Yes.

If we are to assume that premise,

is it even worthwhile for them

to put the liquidity to move the price,

to grab the crumbs,

what it seems of what those stops could be?

What is the mechanics of what is going on here?

Because I see this signature all the time.

That's a superb question.

Here's the answer to that.

I've wondered about that for years.

Those advantages are taken by trade placement algorithms.

What does that mean?

Exactly.

So now imagine that you have,

how do I explain this?

Let's say that you are a person

that's writing an algorithm

that is going to do VWAP,

Volume Weighted Average Price.

And you are given a buy order

for a large number of shares.

And it's going to last a few hours.

What you're going to try to do

is if you have a smart algorithm,

you're going to try to find those regions

where there's this weakness.

And you're going to try to use those

to do more buying.

Because since you can be relatively certain,

higher than 51%, whatever,

that some of the triggering of the stops

is going to produce the price going down.

You can use that as a way of getting a better price

than you otherwise would.

So it's a way of improving your execution.

Who's creating the cause?

The cause is somebody, an institutional guy

that wants to buy a million shares of IBM

because he wants to invest in IBM.

He doesn't care about stops and things going up and down

and all the rest of it.

But there is that demand.

But that demand is not all going to come in at one moment.

Is it a matching algorithm to minimize slippage?

Yes.

And to get the better price.

And so you know that if something is collapsing,

during that period of time,

you're getting a better price than you would otherwise.

So get in there and take advantage of it

as much as you can.

And therefore, how do they engineer it?

Because the logic makes sense.

There's a bunch of stops.

I've got a guy with a big order.

Might as well drive down price.

A lot of things happen.

Liquidity is found.

But who is creating or engineering that?

I can tell you how we did it.

When I was helping Joe with his trading algorithms,

what we were doing is we were actually

using what we call trader logic, Joe's term.

And the idea was to do exactly that.

Write in a computer program what a trader does,

visual identification of areas of supply and demand

or areas of support and resistance and so on and so forth.

And basically say, we're going to adjust

our trading algorithm where we're getting orders

from customers.

And we're going to adjust the trading algorithm

to take advantage of these particular periods

where something interesting might be happening in the market.

So another one, for example,

what I mentioned earlier was opening range breakout.

So you knew, for example, that statistically speaking,

if there was a breakout from the opening range,

the stock was likely to go that way for the rest of the day.

So you speeded up your rewarp on the all day rewarp.

OK.

So I want to speak to you in my language.

And hopefully you understand.

But I'm a purely technical trader.

And I'm down in the lower time frames,

on in and out within a couple of hours.

And what I'm looking to exploit is what we're describing here.

Market open where I see more liquidity, more orders.

And then I'm looking for predictable areas.

Could be an Asia low range.

It could be a support level.

I love taking out a demand area.

When I see that is getting swept,

and then in the right time, usually open,

I see a sense of confirmation.

Could be as simple as a break of structure in my direction.

I'll look to long stop loss at the low of that sweep.

I look to a session high or something like that.

And very often I can get a one to three

or one to four risk to reward in the space of an hour.

And that became my system.

Can you help me understand the why of what I do?

Because I've seen it a million times.

So I can believe in it because I've tested it, seen it.

But I rarely understand why it's working.

And therefore the valid losses that I take

that optically appear the same,

I don't understand why it was a loss.

I just accept it was a loss.

Think of it as an iceberg.

Basically, when there's an institutional order,

what you see is some number of shares.

But in fact, there's a giant iceberg below them.

That trigger upon the first one.

And that's why you get the drift in that direction.

And all that's happening to you when you get losses

is that something else happened

and either you made a mistake

or something else looked like the iceberg

but it wasn't the iceberg.

What you're taking advantage of is you're saying,

"Listen, I'm the, you know, what is that little fish

that eats the parasites on top of a shark?"

- I know you're referring to, well, I say like a leech.

- Yeah, right.

So that's the idea.

So that's what you're doing.

- Yes, yes.

- You're basically saying, "Okay, I know there's a whale out here.

He's gonna be trading in this direction the rest of the day.

I want to be trading in his direction

and I want to just basically, whenever I can, take some--

- Catch a ride.

- Yeah, exactly, catch a ride.

And what you're trying to do is you're trying to identify

when that ride might occur.

And what you found in your trading rules

is when that ride might be occurring,

presumably more often than 50% or whatever,

and you're basically making a nice profit from it.

And one thing you could do, by the way,

to help with your P&L

is don't put your stops at the obvious places.

- Am I not safe to assume that the area

where the predictable stop losses were,

that then got taken out,

that for some time, that should be the protected law of the day?

- Yes, yes, that's great.

- And therefore, is that an obvious place to put it or not?

- No, that's not an obvious place to put it.

But an obvious place to put it is,

here's the market going like this.

Here's a line I can draw across the low support level.

Fine, I'm gonna put it one tick below the support level.

Bad idea, don't do that.

- Or if it's a round number,

please don't put it on a round number.

- Okay.

What's the story, though?

Because when I try and understand it further,

I feel like I'm getting into a conspiracy world

where they are hunting the stops of the retail.

- No, they don't have to hunt the stops.

- But visually, that seems what's going on.

- It seems that way.

But they don't have to actually hunt the stops

'cause they know they're there.

And so what they're doing--

- But are there not stop losses everywhere in the market?

- No, because--

- Or are they concentrated?

- Yes, because people psychologically put them

at specific levels.

- And this is, I'm really gonna explore this

because I struggle-- - Please do.

- With every other guess, I never get an answer.

- Please do.

- These predictable areas are retail predictable areas,

and therefore, are they not a drop in the ocean

in terms of the stops and liquidity?

- Yes, but that's a very good question.

So let me say two things to you about that.

Fractional shares, if I forget, let's get back to that.

But let's talk about that issue first.

So the thing to understand is that the liquidity

of the stock market at any given instant in time

is not very big.

- Hmm.

- So an actual order, an actual retail stop order

can move the market even though you wouldn't expect it to

because at that moment in time, there isn't much liquidity.

Liquidity exists over periods of time.

At instance in time, it doesn't really exist.

- Interesting.

- I forget who's, there's a guy, Olson and Associates,

way back, he used to call it a camel going through

the eye of a needle.

- Okay.

- So basically the camel is the big order.

- And this--

- And you've got to push it through the eye of the needle.

At the eye of the needle itself has very little liquidity.

- Hmm.

- That's why those orders matter.

And the second thing you want to do, by the way,

is when you're putting your orders in to go in the direction

of the flow of the whale, please don't use round numbers, ever.

- Hmm.

- Use something really stupid, make yourself look like an idiot.

So put an order for 96 shares or, you know, 221,

some really crazy number, use prime numbers, that's even better,

that don't end in five, because prime numbers and also numbers

that don't end in five and zero.

- When I, this signature that I'm describing,

where we get predictable area, sweeps it,

- Yes.

- bounces up, gives me a confirmation, I get in.

- Yep.

- A lot of the times, which is happening more now than it ever used to,

- Yep.

- I wonder why, that protected low, that is only a protected low for me,

gets swept once again.

So it comes into a, where the stop losses should be,

taps once, taps once again, and then goes.

- Yep.

- This didn't used to happen, I didn't see it five years ago or 10 years ago.

I'm seeing it more and more now.

What is going on here?

- Same thing, targeting.

The expectation is that that area may have some stops.

And so what you're doing then is as an algorithm,

you're basically slowing down your buying.

And if you slow down your buying, of course, the stock's gonna fall.

- Mm-hmm.

- Because it's your buying that's been propping it up.

And you wait to see if you can get it at a cheaper price by slowing down how you buy.

- Can this be a victim to spoofing?

- Absolutely.

- Hmm.

- No question.

- And nothing to be done about it, like, the game is the game, I guess.

- The game is the game.

- Hmm.

What was the other thing you wanted me to bring back to about fractional?

- Yes, fractional shares.

So the thing is, one of the things that gets you picked off

is when people think you're an institutional order.

So what they're gonna do then is they're gonna try to get in front of you.

So don't look like an institutional order.

So you want your order to always look like a non-institutional order.

- What does that mean?

- So an institutional order will generally be with round numbers.

It will be steady.

It will come in at regular predictable intervals and last an entire day or whatever

because they're not honestly that concerned about slippage

because they're more or less expecting that they'll have slippage.

But what they do is they give the algorithm, excuse me,

they give the order to an algo provider.

And then they rate the algo provider on how good their execution was.

So the algo provider is basically trying to execute that algorithm in the market

with the least slippage they possibly can,

which is where the trader logic comes in.

So if you, on the other hand, are a retail trader, right,

you want to advertise you're a retail trader.

You want to advertise that you're not somebody to be picked off.

And so you do that by having round numbers, sorry, non-round numbers.

- Yes.

Super fascinating conversation.

Honestly, I think I could go on for hours,

but I want to just wrap up with an open question.

Maybe taking a portion of your book,

because I wanted to bring this into the conversation,

that would be particularly relevant for a viewer,

especially if we can try and bridge the wealth of knowledge you have

towards a beginner trader.

What kind of advice could you give to bridge that gap?

- Okay, so the book is called "The Science of Free Will."

And basically I go through, and this is relevant to trading actually,

you're made of atoms, I'm made of atoms,

this microphone's made of atoms, that camera's made of atoms.

All those atoms are following a mathematical law.

We know that mathematical law.

And if every atom in your body is following a mathematical law,

then what's the difference between you and a machine?

That's the question.

And the answer in the book, which you can read,

is that it all comes down to something called

computational irreducibility, which is a mouthful.

But it's a very simple idea.

And it's the simple idea that

if you see complex things going out in the world,

you would expect that the rules that generate that outcome

are also complex.

But what computational irreducibility says is that,

no, in many cases, the very simplest possible rules

you can imagine can produce output that can never,

ever, under any circumstances, be predicted.

So I like to say that these are rules

that even a five-year-old can follow,

but whose output is not predictable.

And I go through in the book to show how that might occur.

And so the most important thing that a beginner trader,

I think, needs to understand,

particularly in the context of the book,

is that a lot of market movement genuinely is random,

i.e. it is unpredictable.

Even though it's coming from a deterministic process,

it's not predictable.

It can't be predicted.

And so your job as a trader

is not to try to outthink the market

or outfox the market or whatever.

It's to do what you just ably mentioned

in the last five minutes,

is that you need to find an area of the market

where you can be reasonably confident

that you have some edge.

And you need to be able to identify what that edge is,

and you need to be able to say something sensible

about the edge before you ever trade that edge.

That's the most important thing.

And you also need to be very careful

that you don't train yourself on randomness

and basically, as you said earlier,

have a bad process that luckily produced a good result.

Because if you do that,

you're never going to learn how to trade properly.

It is always better to have a good process

and a bad result and a bad process with a good result, always.

That I think is the key.

Find a process, find an edge,

find where it is that in the market

there is some element of...

It's not even necessarily predictability.

It's an element of consistency.

That's an easy way of thinking about it.

Something tends to consistently happen.

Find that and trade that, and you can exploit that.

That's the best way to do things, I think.

Beautiful.

Honestly, I think that was one of my favourite episodes.

This was a blast, a very stimulating conversation.

So I just want to thank you for the opportunity and your time.

Thank you. I enjoyed it.

Thank you so much. It was great fun.