April 4, 2024 • 41 mins
Dive into the binary world of trading with Sean and Phil as they unpack the game-changing role of technology in this week's Rebel Traders Podcast. From the nostalgic hum of ticker tapes to the symphony of modern algorithms, discover how tech is transforming trader toolkits everywhere.
Master the art of making the market work for you, whether you're behind a desk or on the move. This episode is a treasure trove of insights – from Sean's hot takes on short-term chart strategies to Phil's rapid-fire idea validation tools that turn hours into minutes.
As tech reshapes our trading terrain, learn to automate without sacrificing control, tailored to your lifestyle and beat. Plus, get the skinny on how AI and machine learning are the new wingmen for the savvy trader, enhancing decision making without dimming the human spark.
Join the Rebel Traders for an essential lesson in leveraging technology for trading success. No fluff, no filler – just the bold, contrarian insights you need to stay ahead in the digital market race. Tune in to RT 284 and revolutionize your trading trajectory.
It's time to trade smart, trade savvy – Rebel Traders style.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:03):
You know, we were talking about embracing technology and all the
times that, we we got to press even record. You
know what? Hey. Technology can help. There's a little bit of a leap from the
past. We got a gimme a lorian. Rebel
Traders takes you inside the world of 2 underground master traders
who take an entertaining and contrarian look at the markets to cut through
(00:25):
the noise of Wall Street and help you navigate the trading minefield.
Together, Sean Donahoe and Phil Newton are on a mission to give you the
unfair advantage of a rebel trader. And now, here are your
hosts, Sean Donahoe and mister Phil Newton. Hey.
Hey. Hey. This is Shane Troop, and welcome to the
video and the video version of the Metal Figures
(00:47):
podcast. I'm joined by, the man with a plan, his finger
in a flamingo, mister Phil Newton. As we actually on the
compass. I was gonna say, we're actually redoing this one. We took a break
from last week because we had technology failure,
with the recording of the last one and spent a week trying to fix the
bloody thing. But, hey. You know what? This is version 2, I
(01:10):
would say part 2. We couldn't jump in the DeLorean, hit 88,
and go back in time and fix the bloody thing, but we'll do it
again one more time. Once more from the top, and we'll see how it
rocks. So technology. Alright, Phil. Where do you wanna start? It's
quite it's quite ironic, Sean, that we've hit multiple
technical snafus before pressing record on this one as well.
(01:32):
This is So the irony should not be lost on anyone listening, but if you'd
seen what you what we were doing behind the scenes before we got rocking and
rolling, we've had multiple
reboots, big hammers were involved, and maybe the occasional squeeze of swear words.
But nonetheless, technology, Sean, it's a it's a lot different to
what it was when we were nippers in trading.
(01:54):
Absolutely. I don't know about you, but I I remember if you wanted a live
data feed, you had to get a satellite dish and a
$2,000 or equivalent depends on the way where around the world.
I think it was £2,000. So it was almost almost $3,000 at the
exchange rate back then. That was the kind of the the live
data feed. And you you paid her feed as well, didn't you, Sean? If
(02:16):
you might might recall. So if you wanted to put so you wanna dock, she
want you now they kind of book them all together, and it was
pretty expensive just to get a live data feed. So, you
know, we should count our lucky stars compared to now
versus then. It's so easy. Just to get live data
shown, it is, in a lot of places, free,
(02:38):
which is you know, it just boggles the mind. You know, you had
to, what was I doing? I think I I was
did I ever tell you the story, Sean, of how I got currency trading? I
think this might be a funny thing. Sure. How I got currency how I got
started currency trading. I've not This was well, I was full time trading already, but
I was trading, futures, IBEX, which was the Spanish
(02:59):
index, primarily because it had the same type of
volatility as the Dow, but on European hours.
And I remember having a phone call with, one of the
very few trader friends who was actually trading at the time.
And he said, do you trade currencies? And I said, no. He said, you
should. And I said, okay. I will. That was that was how I got started
(03:22):
in the currency trading. And it was he said, is it any good? They went,
yeah. It's pretty good. And and okay. So the next day, it was a phone
call. You couldn't even just log on. You had a phone call, and then I
had to wait 48 hours for them to type it in
from wherever it came from. And then that's how we got
started, trading currencies. And I didn't know it
(03:42):
was 24 hour market. That's how naive I was about currencies back
then. But it was, a 24 hour markets. And what
I noticed was that it was very, very sideways for a long
period of time, and then you'd see this explosive movements,
about 9, 10 o'clock in the u UK hours. And I was
like, why is it for and then you look at the time scale across the
(04:04):
bottom, and it said, you know, 24 hour market. And it was about 2 or
3 days before I realized.
Oh, dear. Oh, it's funny. And I also started out as another
corker. I I also was trading 15 minute
charts on currencies back then because I was using a
charting platform whose intraday defaults was 15
(04:27):
minute charts. So when you opened an intraday, it was just automatically 15 minute charts.
So that's the only reason why I started up trading 15 minute charts. And then
the the the the the 15 minute breakout was born. And, you know, fast forward
a few years, and, you know, we've got a a futures version of trading the,
the the the premarket trading break or the premarket range
breakout as a variation. We do something very similar on SPX now by
(04:49):
today's standards. It's just funny how the the
evolution of things as it were, the kind of the style of trading is
dictated by complete ignorance and default settings.
It's funny. You know, we talk about technology and and, I mean, the the
leaps and bounds from now where we are as algorithmic traders and everything else
compared to back then. I started off with Teletext.
(05:11):
Teletext gave Yeah. Input the the closest you could get to
real time. It was obviously delayed a lot. But because it was
so delayed, I became interested as a as a
investor because I was getting that data, which if
for anyone who doesn't know what teletext was, back in the UK,
you press this wee button on your your television. This is smart television
(05:33):
before Internet and everything else, and you would get the
latest news. And what happened was they transmitted it
via RF radio frequency for all those,
predigital folks, and it was just this little line of
data in the signal at the top of the screen that was actually scrolled up.
You couldn't see it, but it was all the data, and you could then
(05:55):
access it, translate it, and you could get latest news,
stock market information, and everything else. And it was so much faster
than getting it through the newspaper where most people got
their stock information for the day, reading the sheets, you know, the
broadsheets and stuff like that. It was lightning fast. Yeah.
It was lightning fast. So because it was 20 minutes delayed in some
(06:18):
cases and maybe 2 up to 2 hours in other areas, wasn't it?
And I even I've completely forgot about that as well. I started off
15, 16. That was my hand drawn shots when I was doing that for
the going back a fair bit then. So yeah. Now
now that they did also go back to, like, Edward O'Fayr.
The date do do you do you remember the the I I know you've kind
(06:40):
of, like, not lived in the UK file, but do you remember the the newspaper,
The Daily Mirror, that classic red top newspaper?
It's a trash newspaper Yeah. Essentially. And there
was a a couple of stock and they wrote a book,
about stock tips and and such, and
(07:00):
how to kind of do almost like bed and breakfast type
trade. You put the trade on Friday, and you close it on a Monday. And
that that was kind of, like, the equivalent of it then. And
all they were doing was looking at the top 10 movers and shakers on Teletech.
That was that was their big reveal. And
whatever the leader or, you know, the top 2 or 3 leaders
(07:24):
on the Telitex on the Friday for the week,
you'd buy the shares and close them on the Monday.
And what they would do in the newspaper is they would put their picks in
the newspaper on a Friday, morning for the
morning edition on a Friday. So, obviously, all those orders went
in, but they got done
(07:46):
for front running the orders because they placed their trade
on the Thursday. So they
they were lit so they literally had a captive so it became a self
fulfilling property. And this this went on for about 2 years. You know? And these
these were the the gurus of the day, the pundits of the day, and it
turned out that they were front running or they were basically buying shares, you
(08:08):
know, pumping them in in the Daily Mirror Newspaper on the on the
Friday morning. All those orders would go in. They
they the people who got late in on the Friday saw that it had moved
on the Friday because everyone's, you know, buying. So then they pumped themselves
on the Monday, so they wanted to try and get some late action. And it
just became this little mini bubble that they were
(08:30):
creating courtesy of the the the circulation of print newspaper
of the Daily Mirror. And they did they they did a a short spell in
Her Majesty's that's
Her Majesty's pleasure, should we say. Yeah. I mean, the
thing is you that's a little bit of genius as
as bad as it is. It's a little bit of genius.
(08:53):
I mean, look at it. I mean, crypto, Sean, pump it it's a pump and
nut scheme. That that's essentially what they're doing. It's just they they have their own
captive audience, with the the newspaper. But it goes
on even to this day in Facebook groups,
Discord servers, you know, Telegram groups or or WhatsApp
groups. Know, it's gonna go all all to be fair, John, the the the dotcom
(09:14):
bubble, courtesy of Reddit's Wall Street Bets. So
these things, technology allows this speed of
access. And the same things, you think this is all brand new,
but I've reread re reminiscence of the stock operator recently
a few times short as if we've covered before. And the same
thing was happening 100 and, you know, 120 years ago,
(09:36):
you know, at the 10 of 1900. You know, it's not a new concept.
Sorry. We're all talking about illegal activities there really, aren't we? But the this this
kind of pump and dump and creating hype arounds and
events, it's it's been going on a long time. And I think this this
technology has just sped up some of the bullshit on this industry.
(09:56):
It has sped up the bullshit, and it's also sped up the advantage we have
as well. I mean, when we think about speech information, we
have literally even, I mean,
because everything's really baked into the data right now.
As we get our feeds, there's an expectation, say, with the Fed or
CPI or FOMC or something else. The
(10:18):
speed of information is we know about these events. We don't have to read about
them in the newspaper, wait for a television announcement, or what have you.
We can read it in the charts literally, you know,
in real time. The story and we talk about how the news
is usually a reason to get out of a trade. We talk about all the
different things that happen, but the the speed
(10:40):
of information is really the stories on
the the data. I and we say this to our students all the time is,
you know, turn off the news. You can have an awareness and everything else, but
the real story is in the data.
And that's only true because of the speed of information,
the speed of everything that's coming in. And that's one of the reasons
(11:02):
we're really algorithmic traders. And,
you know, platforms like, yeah, TradeStation, TradingView,
they allow you to code in your strategy based
on the, speed of information, the
the price action, volume, or whatever else you're
doing. But you can use these platforms that
(11:26):
weren't available to us when we first started out
and create very sophisticated
algorithmic strategies and even and this is one of the the
the I think it's a slight difference between myself
and Phil in our styles of trading, which is
I I it was funny because when we first recorded this, I didn't call
(11:49):
Phil out on this or highlight the difference, I would say,
is Phil likes to be the final button pusher.
I like being able to step away and let the computer do
the work for me. But it's it doesn't matter whether it's
fully automated, semi automated, or you're
doing just your if then else for yourself. It's a
(12:12):
checklist bullet point system that you're doing. All
of this stuff allows us to be algorithmic in whether
it's, you know, neural or binary. You know,
like, I'm pointing at one of my monitors here. Whatever way it
is, that algorithm approach
allows you to do so much removing discretion,
(12:34):
emotion, the, you know, the the
I mean, that's the big reason that's the big reason
why I like the, I I I think it might all be
worth underscoring an algorithm. An algorithm is nothing to be scared of. You think you
need a a math PhD, or some coding script.
I like, I'm not the sharpest tool in the box. Like, I'm I'm pretty smart.
(12:56):
But, like, when it comes to software, when it comes
to, writing code, I'm completely clueless. I
I'm as much of a noob as the next person when it comes to that.
And I've got no interest in it whatsoever other than being able to
describe Slink 2, a programmer that I'm gonna hire.
Back when we started, it was trying to test and validate
(13:18):
these ideas just to get back on yours. Sorry. Sorry. I I saw a squirrel
and chased it, John. And the an algorithm, it's just a series of yes,
no decision. It's binary. And I find myself saying this a lot to our
students all the time. It's a binary decision. You know, coulda, woulda, shoulda, this
discretionary interpretation, whatever the question is. Well, no. It's a binary
decision. Has x happened? Yes or no? If yes, place
(13:40):
the trade. If no, wait. You know? There's no subjectivity
involved. And both myself and Sean, we we've been on parallel tracks for, you
know, 25 plus years trying to remove those discretionary
decisions. Again, I hate the subjectivity. But
the it it's the the self doubts when you've
got a question mark against whatever it is
(14:03):
you're looking at. And I think, again, just coming back to the the
algorithmic approach, the the binary decisions, the series of yes, no
questions, it just means that if I am unsure sure and I'm looking
at weird and funky market conditions, which will happen, and you've got
that startled rabbit in the headlights experience, you've
got a base strategy to fall back on a a decision tree,
(14:25):
a thinking process. There's lots of different ways to describe this. But it's just been
able to fall back and go, has this event happened? Has this thing happened?
Yes or no? Alright. Well, no. Well, why am I stressing
over the the coulda, woulda, shouldas, the ifs, buts, and the maybes? It's just
when that event happens or doesn't happen as the case may be, you're either taking
action or in waiting mode. And you're gonna be in waiting mode 95 plus
(14:47):
percent of the time. But to come back to, the
start on that scroll up, Sean, and chasing that down the, the road is
the trying to back test,
validate, create a strategy to get to that series of yes,
no questions. It it would take, if you're not a
programmer, you know, multiple months. I remember some of the first strategy. I would
(15:09):
spend months unscrew because they didn't
have to, it was live days for only. There was no,
rollback feature. You'd had to scroll through the charts 1 bar at a time on
whatever time frame you were looking at. And then if you decided that that time
frame is a little bit whippy and choppy, you had to go back to begin,
start again. And you could be many months going through
(15:30):
validating concepts, validating ideas, and then, you know, maybe, you
know, you're halfway through whatever data sample that you're looking through, and you just
go, you know, I think I've looked at enough iterations of
this to put a refinement in. And you're gonna go back to the
beginning, and then you gotta scroll more broadly with the new iteration. And then maybe
you've got 3 or 4 things. You're not sure which one's working. So then you're
(15:52):
trying to track 3 or 4 variables at the same time because, you know, you
think it's a little bit smarter. And then you forget what piece of paper that
you've wrote it down on. You know? And and you're shuffling. You know, you look
like that guy at memento, Sean, where you write numbers all over and little reminder
notes everywhere. And, you know, it was it was a hard,
long slog. Well, now, as Sean said, you
(16:12):
know, literally a few minutes ago, with the advent of technology,
you can quite literally put if this then that's. If you know a little bit
of code, you can write it. If you like me and you don't, then you
can go use a a tool like TrendSpider, which has no
code solutions. I think on the first iteration of
this podcast, we were also quite excited about the next version of chat
(16:33):
gbt, which had solved its ability to,
do simple math equations, which it was flummoxing itself
with, previously. So you can use basic
speaking language to talk through,
a potential code and get chat gbt or some, you know, more
(16:53):
dedicated programming version to spit a, a very simple code base
out that you can upload to TradeStation, that you can upload to Transpire, that you
can upload to TradingView, or, you know, insert the charting
platform of your choice. It is possible now, with a
very simple, set of rules of just to validate the
concept without necessarily having, you know, the the preferred
(17:14):
money management approach that you might like. But it it's just a a
wonderful place to be and a a time to live where we can, at the
push of a button, test an idea, which is, to be fair, where we came
with our new version, of our latest strategy, the
the the income strategy. That that's essentially what happened because we've just been through this
process ourselves. Last October, you know, quite
(17:36):
literally had an idea, and within an hour, we were able
to validate it by going back through a couple of weeks. Okay. This looks like
it's got legs, and then you can send it off to the programmer. And, you
know, within an hour, it came back. It was a you know, he he he
had a little bit of a time window. And then 2, 3 days later, through
a little bit of honing, a little bit of refining, a little bit of couple
of tweaks, we've got version 1 of what's turned out to be
(17:59):
a fucking awesome strategy to the point where I've stopped doing
everything else to focus more on this and the
variations that has come about from this strategy. So in a very short
space of time, you can find something that that you know, that
little golden nuggets, that is worth your
time and attention. And then the only thing is is does it suit your personality?
(18:21):
You know, can you practically do it? Do you have time to do it? Again,
because not everyone has the the the freedom of flexibility of time.
You know, so that's gonna dictate some of the approaches that you take or don't
as the case may be. And, certainly, both in both our cases,
Sean, we've had the, the approach here of, okay, what do I wanna do more
of? What do I wanna do less of? And we've both of us have come
(18:42):
through the the lens of, okay, I've got to run a
strategy through the lens of I need to have minimal screen time. You
know? And practically from your point of view, you're on the other side of the
world from the US now. So, you know, you've got that ever
present. You know, you can't check you know, you the regular market hours is
used your sleeping time most the time. I know you're a bit of a night
(19:03):
owl anyway. But, you know, practically, you've got to be able to apply the
strategy in real time within time constraints. So we've got to
run through the lens of that as well. And it's it's interesting because
this is where, again, necessity and technology
really fuse together. So one of the things that, I'm
focused on right now is automating it. Because as Phil correctly said,
(19:26):
I'm I live in Paris. I mean, Thailand. You know?
I like cruising the mountains on my motorbikes of
which I keep buying many, many, many. So that's you know, this weekend's
a long weekend. What's my plan? I wanna go and cruise somewhere.
Obviously, that's great for the, for the, you know, weekend.
There's no trading. But during the weeks, like Phil says, I
(19:48):
gotta sleep. I gotta do that. So the evenings here, I can catch
something in the first few hours of the market and get signal. I can
set up an, you know, again, algorithmic
approach, coded it all up. If the
specific condition happens, I get an alert on my phone. I get an alert
in the house. It lets me know, hey. You've got a
(20:11):
condition set up at the beginning of the market. Let's have a look. Both
myself and my girlfriend will then open up our laptops, go play some
trades, close them again, get on with the movie or
whatever else we're doing for the evening. And that's great, but then the ultimate
goal is to take the other stuff that we do. And then, again,
could do this several years ago, but now building a platform. I mean, I'm
(20:33):
even building a platform. This is, again, difference between film myself. I am a
code. I have software development companies, yada yada yada. So we're building a
platform for, you know, Trade Canyon and everything else and our
students, which will allow them to automate all
of our strategies and literally just
say, okay. Here's my risk profile. Here's the strategies that I
(20:56):
want to trade. Boom boom boom. Go.
And it's literally as as simple as logging in,
setting up your parameters, logging out, and letting the
algorithmic approach do everything. Now I
built that originally for myself because I
enjoy sleeping. I don't wanna and I know people who's, you know, even
(21:18):
here, there are traders who are up trading SPX all night,
and they sleep during the day. I'm like, that's that's not my flavor of
ice cream. That's great to have you. Doesn't sound like a fun
time, does it, Sean? You're living in paradise. You don't wanna sleep through the best
part of the day. You know? Yeah. And I was gonna say, I'll give a
shout out to Scott. You know who you are. Who's
(21:39):
specifically, I was thinking of with that. But, again,
the solutions that are available to everyone just
could you can find your particular favor of ice cream. Even applying the same
damn rules and strategies, you can find which way you want to trade based on
your situation. For me, I wanna be if I can be,
completely hands off, fan freaking tastic.
(22:02):
If I have to, you know, noodle a couple of things here and there,
like, you know, crypto markets, 247365,
that's great. Do that any time of day. But for some of the
stuff I do in the US market, which is more
timely, short term 30 minute charts, SPX,
you need to have something going during market hours. Other
(22:25):
strategies, I can set them up during the day
here. For the next day, I I don't even have to look
at them, and then I'm just doing it aftermarket stuff for the longer
term trend trends. So all of it is algorithmic,
though. And, yeah, like Phil mentioned, there are no code solutions to help
you not only test your ideas,
(22:47):
analyze them, you know, and do backtesting.
It just give you a broad scope of is this does this
idea have legs? And then, you know, with real time data
access and access to developers and everything else, you can
then go and create whatever you want. I mean, I regularly
hire different I've just actually spent a bloody fortune,
(23:10):
on hiring developers for this new platform that we're building
and managing that and everything else. You don't have to go that far. You can
go find a freelancer once you have a valid idea and an
algorithm that works, Be it our strategy, your strategy,
freaking, I don't know. I I don't know. Bungle book? I was gonna
say, bungle from rainbow or something like that. It's got a great strategy
(23:32):
or Zippy. You know, whatever it is, go you
can go find someone to code it up and then make
that either an indicator based on your idea
or even a full blown automated trading system with
Python that runs on your laptop. You know, there's so many
different approaches that, again, just open
(23:55):
up an entire world of trading. Right. I
mean, to me also It's it's the most exciting time to be a
trader right now. I mean, we're between machine learning,
AI, all the real time information, everything
else. I mean, this this to me this this is what fires
me. Other than motorbikes, which everyone who knows me, I'm bloody
(24:16):
crazy about. Trading and trading automation and the
technology behind all this, that's the second thing that fires me.
I'm just gonna say, Sean, one of the things that would would both of us
are dancing around is that
technology is not a replacement for some of the
fundamental skills. No. Like, you don't now I'll I'll say
(24:39):
along the same vein, you don't need to have
multi decades of experience on the hard right edge of the charts. You
just need to have base level of competency to
make this work and the confidence to go and and kind of
explore developing your own strategy. So it's not a case if you've
gotta know down 3, 3, 3, all the other kind of nonsense, the wiz bangs,
(25:01):
the tools, the red blue indicator, whatever the the the flavor of the day is.
You just need to know one thing reasonably well. And like with
anything, you just need a certain level base level of competency
to kind of start down this road. In fairness, we
because it's ever present on our mind, we've kind of focused on the
strategy development side more than anything. But there
(25:24):
there's a whole world of data analysis. I mean, one of the things that we
were both quite excited about when we've spoken privately
is the ability to oh, what's the what's the right word I'm looking for?
To to talk with data via, a a
chat gbt type plug in. You can wear and air in data.
(25:45):
It's the data. There we go. Interrogate. That's the word I was looking for. You
can kind of interrogate the data whether it's your own personal trading,
whether it's some data analysis that you wanna do, you don't have to be a
pro in this. You can just ask basic questions of, okay,
what am I you know, know, for example, let's just say that, you know, I've
got my, brokerage accounts. I've uploaded all the, the data in a
(26:06):
spreadsheet to, ChatGbt, and you can start to
have a conversation with the data, effectively. Okay. What are
the the the best trades? What are the worst trades? What are the win streaks?
All the base information that you can get. But maybe you can start saying, well,
what day of the week is my best day? What's the worst day? You know,
are there any, outliers that you may you that you might need to know? You
(26:27):
can start to kind of have conversation with the data. And it sounds a little
bit crazy saying that, doesn't it, Sean? But you can have this conversation with the
data. You don't have to be able to insert. You can ask these,
chat plugins to talk to you, explain
the data to you. And if you've got a question, you know, you don't have
to feel silly about, you know, asking a financial adviser. You can ask, you
(26:49):
know, an anonymous, plugin in simple language and have it spit
back to you. Hey. Explain this to me in layman's time. Hey. You know, go
a little bit deeper on this. You know, is there any anything that should be
worried about? Some best days, worst days, what's the best trade? You
know? Whatever question that you've got about the data, it can
come back at you even if it's a generalized, hey. Interpret the
(27:09):
data for me and give me pros and cons. You know? You can be very
open ended with some of the the things that you can do now with these,
the the technological advancements. Yeah. No.
Absolutely. I mean and you touched on something I wanted to highlight as
well. And this is teddy bear, Sean.
There you go. I'm not a swipe your line for a change.
(27:32):
You're right. That's what she said. Yeah. So
one of the things that this
environment and being algorithmic as well is
shortcuts the need for experience. You talk about the the far right edge and
the experience there. When you have an algorithmic approach
and this is something that I I tell a lot of our newer students who've
(27:54):
never traded before and who are just learning the the process and and
this world is it doesn't
matter if we if we're looking experience doesn't
matter. If we're looking at the same information,
the, you know, we're looking at the same rule set and
we've got, you know, this thing happening, this crossing here, whatever the
(28:16):
rule is, we're gonna get the same
result regardless of our experience. If we're following the same
algorithm, we're going through the same checklist, and we're doing the same
thing, We're gonna get the same result. Now,
obviously, it depends on the money you're putting in and that that that that. I
don't mean exactly the same numbers, but we're gonna get the same
(28:38):
output in terms of if we're looking at the same information, you
know, like, we we've got our rebel income system that,
is absolutely fantastic we're doing right now, which is 30 minute SPX
system. Again, if we're looking at the same
information, doing the same execution, we're gonna
get the same results. Whether it be a 100% return on capital, return
(29:01):
on risk, etcetera, whether we're having if we have a win, we have a
loss, we'll get pretty much the same. Now, obviously,
there's some nuances in that, but the the reality is if you're
following a system that has a
positive expectancy and you follow that
exactly, you're following the rules, you're following the algorithm,
(29:23):
then those results are gonna be the same
for everyone else following that same system. So it eliminates
the need for experience and
then, thus, all the emotion, discretion, the
learning in the trenches, boot you know, boots on the ground type environment
and, you know, like, the you know, all the other things that you need from
(29:45):
a psychological perspective, it's minimized.
Because you're straight to the the sorry, Sean.
Sean's a kind of we used to call it,
very regularly a production line process. Like, it was a factory because
it's replicatable regardless of experience. And
that that's the key point there that I just wanted to underscore. It's replicable. And
(30:08):
and to be fair, this is what pleases us most about the way that we
approach trading. It's not a discretionary viewpoint. It's not an opinion.
It's not a or I you know, there was a 5 wave, but, you know,
on a 1st day, it was 6 waves, and, you know, you can interpret it
differently if you have the start point there. You know, there's a little bit of
whimsy involved with some of the processes. And it's not that they don't
(30:29):
work. It's just that the interpretation well, there's
there's the word. It's open to interpretation.
Unless you've got an algorithmic approach, a rule set, an if this,
then, that that is replicable and repeatable by
anyone regardless of experience. You know? There's obviously a learning curve with anything. You gotta
learn some technology. You gotta learn, the process itself just like you would
(30:52):
do at a factory. You've gotta learn how the the the factory, where all the
component parts, you know, which parts are put together with what bit first. It's an
IKEA flat pack system. You've got to put, you know, socket a
with socket b. You know what I mean? You've gotta do that for there's always
always gonna be a learning curve. But when you've got that, it's really simple. You
know? You can follow that process. It is repeatable, and you're gonna get a
(31:13):
comparable results because we're all looking at the same thing, the same process, and
we're all getting the same outcome, which is wonderful. And that that really
does, lift my spirit, Sean, when we get the
feedback from our students. I love that. And the other thing as well, which I
think is is very important, is
eliminating the coulda, shoulda, would. Again, this
(31:35):
is something I was actually talking with a student about earlier on. Lit literally
today, just talking about how
important it is to remove a lot of
that indecisive phrasing. When you have a
checklist production line process, however you want to refer to
it, when you have that process in place with the rules
(31:58):
you follow, there's no ambiguity
about what you kinda shoulda, woulda, woulda. When you hear yourself
saying that language, I should have or I would
have if when you hear any of the
as I call them, You know? Could've showed the odors. When you have any of
the odors coming into your vernacular, you're fucking something
(32:21):
up. You hear some bovine come into this. Yeah. There's
no other come into this. Yeah. The cows orders. Exactly. I
was thinking that even as I said it, I'm like, there's a joke. You say
that I was smiling. I knew you were thinking the same thing. But yeah. So
I he's expecting it to be in a limited fashion. It really is,
at the end of the day. So alright.
(32:42):
With that being said okay. I mean, we've kind of danced around
a lot of the different ways that tech comes into as as an assistant,
not a replacement. And this is the same I I we
could get on a soapbox about AI because a lot of people ask me one
of the first things people ask me when we develop systems is like, oh, is
there AI on this? Like, it's the holy grail of trading.
(33:04):
Look. Machine learning, AI, and everything else,
they are assistants. They're data interpreters. They
do analysis. They can assist you in a lot of different ways. But just
like people are worried about AI taking over, their
jobs and replacing them and everything else, there's some things that
AI will do better than humans. It's gonna be,
(33:27):
you know, all sorts of different ways that AI is gonna influence and change. I
mean, this is really, to be honest, this is like the industrial
revolution all over again. We have the computer revolution, the industrial
revolution, and, yes, we're having the AI revolution. But those
are gonna get ahead before I get on you know, anyone else gets on the
soapbox and you know? I've got a lot of creative types
(33:49):
in my audience and in my, inner circle as
well who who don't like AI because they feel
it's gonna replace creativity. Honestly, it's not. It's
an assistance. Right. And this is even That's an interesting point there,
Sean. It's not gonna there's some things that we'll get rid of completely, but at
the same time, it's also gonna create I mean, when you look through technologies through
(34:10):
history, from the Luddites back in, you know, 17 fifties, he was
smashing up, weaving machines. He thought that their
jobs were being replaced. Actually, created more jobs than it re that it
replaced. And that's the the new job side of things.
And I think just, piggyback on your comments, I don't think it's gonna replace
the markets. I mean, if you had AI and everything was
(34:33):
perfectly driven, the markets would suddenly cease to exist as a
fear that I've heard a few people mention, an irrational fear for that matter. But
if you think about it, like, everyone's got different concepts and ideas.
Everyone's got different requirements. There's lots of hedge funds, big
institutions that do things at certain times because
it makes sense from either from a tax point of view or an investment point
(34:54):
of view. They've got certain ways that they've got to approach things from legal
standpoints. Individual traders have got different personal preferences,
perspectives. We've spoken about the personality of a trader in the past, Sean,
and that is gonna be reflected in the way that systems and
and that these tools are used. For example, you know, we've mentioned a few of
them today, haven't we, Sean? Where our personal preferences, it's the the number
(35:16):
1 needs to be minimal screen time. Number 2, it needs to be rule based
so I could so I don't have subjectivity. You know? And they're the the
top two criteria that we're always thinking about. Then it needs to be
practical. I don't wanna be up at 3 o'clock in the morning, you know, doing
the the you know, putting the trades on. You know? It has to be realistic
with its approach. And then personal preferences, you
(35:38):
know, maybe someone's more aggressive, maybe someone's more conservative. You know? And these
are all gonna be footprints and inputs into the way that the market moves
and the machinations around that. So it's not going to, suddenly
get rid of the stock market. If anything, it's probably gonna make it more
efficient because of the, again, the speed of information,
the technology. In a perfect world, we'd be
(36:00):
thinking that more traders would be making smarter decisions, but we know that's not
true. Because, otherwise, some of the technological
advancements in the past would have, you know, assisted
that. So the market's not gonna cease to exist, and this isn't gonna replace the
trader because everyone's got different perspectives, viewpoints, and
objectives when it comes to trading. Absolutely.
(36:22):
Absolutely. So at the end of the day, yeah, it's an assistant.
It's you know, those are gonna get ahead, know how to use AI,
know how to use your chat tbts, your sunos, your your
all your your mid journeys. Whatever
AI is going to help you, like, Google. I mean,
they use Gemini as it's now. It was Bard now. Not calling it
(36:45):
Gemini. They're integrating that into all the Google Docs and
your work you know, Google, your emails, your anything you're
doing, for your day to day. So same as Microsoft's integrated
into their search engine. It's there. I can
ping, Bing in real time, get
information about today's stock market. I can query
(37:07):
the world and get exactly back what I need refined
down. I can go tell it, oh, I need this, this, this, and
this, and I need it in an Excel,
table, and it'll give it exactly that. So the
Copilot, your Geminis, and everything else, you know,
they're they're there. You've got VR. You've got, you
(37:29):
know, social trading platforms. You've got all sorts of nonconventional
technologies plus the conventional technologies. They're all
assistance, but nothing can replace
the human trading element in a lot
of what we do. And at the end of the day, we are all individual
(37:49):
traders. We're, you know, most of our audience are retail traders. We got some institutional,
investors and everything else in our audiences and listening to
a lot of this. But most of our audience are retail
traders, which is individuals with their laptop or their computer or their
phone looking to make money in the market. So all this tech is
literally right there to assist you move forward and do
(38:12):
it. Don't be afraid of it. Embrace it.
Learn it. Whatever you need to do. But, again,
the advantage now is the advantage we did
not have when we first came up. We kinda grew into a lot of
this, you know, really dating ourselves here. It sounds like we went
to school uphill both ways, you know, and in the
(38:35):
snow, had to paint our toes brown and you know, so we had to paint
our feet brown and tie our toes to pretend we had decent shoes, you know,
all the rest of that kind of shit. But when we first started I
thought I thought you were one of the first to have a ticker tape in
your own household. You were that, well endowed. Yeah. Pretty
much. See, even then, you know, that was revolutionary technology.
(38:56):
You know, the the the wire. It was called the wire because it was a
data delivered on a wire through Morse code. You know? It it's you know? And
that was revolutionary, you know, 120, 130 years ago. You know? It
it's it's it is a wonderful world we live in, and it's only gonna improve.
I think if we always look on the positive side rather than default to negative
is equal. I think sometimes, Sean, human nature, it we kind of
(39:17):
default to the worst or the negative side of things. I think if we
embrace the positivity behind it, and move with the
times, You know, it it can only be seen as a positive,
addition to, you know, anyone's trading routine.
Absa bloody lutely. So I think that's a good place to put a pin
in the show notes and say done. Put a big x to it.
(39:40):
We actually got a successful recording this time. So, again,
appreciate your time and attention. Do tune in next week. We're gonna be talking about
the psychology side of trading in this kind of, like, epic series
where that's number 7 of 12 that we're you know, of
topics that we're gonna dive into. And I think that one's gonna be a
very interesting twist because a lot
(40:02):
of people honestly, just to kinda give a preview, a
lot of people skim over this aspect, and we try and minimize a lot of
the psychological aspects to help people
navigate this, but you can't ignore the psychological aspects. You can have the
best strategy in the world, but if your head isn't in the game, you ain't
gonna be able to do it. So I'm looking forward to that one. Any last
(40:24):
comments from you, Phil? No. That's it. It's a good place to finish up.
Technology, it is the future, not the past.
There you go. Rock and roll. Alright. Thank you for your time and attention.
See you same bat time, same bat channel. And Phil?
I think you stole my line, have we? I was oh, there we go. I'm
too late. I don't remember where we are. There you go. Too late later. Bye,
(40:45):
Finn. I'll see you at same time next time next week. Thank you. Or from
our point of view, in 5 minutes. No. You're alright. Alright.
Cheers. For
more cutting edge trading advice and a free trader workshop to help you build
a personalized trading plan and make smarter trading decisions,
go to tradecanyon.com now. Futures, options off futures. Stock
(41:07):
and stock options trading involves a substantial degree of risk and may not be suitable
for all investors. Past performance is not necessarily indicative of future results. Trade Canyon
Incorporated provides only training and educational information. If you actually understood and listened to this,
then that means you are awesome. Congratulations and well done. Notice, this product
may contain nuts.
You know, we were talking about embracing technology and all the
times that, we we got to press even record. You
know what? Hey. Technology can help. There's a little bit of a leap from the
past. We got a gimme a lorian. Rebel
Traders takes you inside the world of 2 underground master traders
who take an entertaining and contrarian look at the markets to cut through
(00:25):
the noise of Wall Street and help you navigate the trading minefield.
Together, Sean Donahoe and Phil Newton are on a mission to give you the
unfair advantage of a rebel trader. And now, here are your
hosts, Sean Donahoe and mister Phil Newton. Hey.
Hey. Hey. This is Shane Troop, and welcome to the
video and the video version of the Metal Figures
(00:47):
podcast. I'm joined by, the man with a plan, his finger
in a flamingo, mister Phil Newton. As we actually on the
compass. I was gonna say, we're actually redoing this one. We took a break
from last week because we had technology failure,
with the recording of the last one and spent a week trying to fix the
bloody thing. But, hey. You know what? This is version 2, I
(01:10):
would say part 2. We couldn't jump in the DeLorean, hit 88,
and go back in time and fix the bloody thing, but we'll do it
again one more time. Once more from the top, and we'll see how it
rocks. So technology. Alright, Phil. Where do you wanna start? It's
quite it's quite ironic, Sean, that we've hit multiple
technical snafus before pressing record on this one as well.
(01:32):
This is So the irony should not be lost on anyone listening, but if you'd
seen what you what we were doing behind the scenes before we got rocking and
rolling, we've had multiple
reboots, big hammers were involved, and maybe the occasional squeeze of swear words.
But nonetheless, technology, Sean, it's a it's a lot different to
what it was when we were nippers in trading.
(01:54):
Absolutely. I don't know about you, but I I remember if you wanted a live
data feed, you had to get a satellite dish and a
$2,000 or equivalent depends on the way where around the world.
I think it was £2,000. So it was almost almost $3,000 at the
exchange rate back then. That was the kind of the the live
data feed. And you you paid her feed as well, didn't you, Sean? If
(02:16):
you might might recall. So if you wanted to put so you wanna dock, she
want you now they kind of book them all together, and it was
pretty expensive just to get a live data feed. So, you
know, we should count our lucky stars compared to now
versus then. It's so easy. Just to get live data
shown, it is, in a lot of places, free,
(02:38):
which is you know, it just boggles the mind. You know, you had
to, what was I doing? I think I I was
did I ever tell you the story, Sean, of how I got currency trading? I
think this might be a funny thing. Sure. How I got currency how I got
started currency trading. I've not This was well, I was full time trading already, but
I was trading, futures, IBEX, which was the Spanish
(02:59):
index, primarily because it had the same type of
volatility as the Dow, but on European hours.
And I remember having a phone call with, one of the
very few trader friends who was actually trading at the time.
And he said, do you trade currencies? And I said, no. He said, you
should. And I said, okay. I will. That was that was how I got started
(03:22):
in the currency trading. And it was he said, is it any good? They went,
yeah. It's pretty good. And and okay. So the next day, it was a phone
call. You couldn't even just log on. You had a phone call, and then I
had to wait 48 hours for them to type it in
from wherever it came from. And then that's how we got
started, trading currencies. And I didn't know it
(03:42):
was 24 hour market. That's how naive I was about currencies back
then. But it was, a 24 hour markets. And what
I noticed was that it was very, very sideways for a long
period of time, and then you'd see this explosive movements,
about 9, 10 o'clock in the u UK hours. And I was
like, why is it for and then you look at the time scale across the
(04:04):
bottom, and it said, you know, 24 hour market. And it was about 2 or
3 days before I realized.
Oh, dear. Oh, it's funny. And I also started out as another
corker. I I also was trading 15 minute
charts on currencies back then because I was using a
charting platform whose intraday defaults was 15
(04:27):
minute charts. So when you opened an intraday, it was just automatically 15 minute charts.
So that's the only reason why I started up trading 15 minute charts. And then
the the the the the 15 minute breakout was born. And, you know, fast forward
a few years, and, you know, we've got a a futures version of trading the,
the the the premarket trading break or the premarket range
breakout as a variation. We do something very similar on SPX now by
(04:49):
today's standards. It's just funny how the the
evolution of things as it were, the kind of the style of trading is
dictated by complete ignorance and default settings.
It's funny. You know, we talk about technology and and, I mean, the the
leaps and bounds from now where we are as algorithmic traders and everything else
compared to back then. I started off with Teletext.
(05:11):
Teletext gave Yeah. Input the the closest you could get to
real time. It was obviously delayed a lot. But because it was
so delayed, I became interested as a as a
investor because I was getting that data, which if
for anyone who doesn't know what teletext was, back in the UK,
you press this wee button on your your television. This is smart television
(05:33):
before Internet and everything else, and you would get the
latest news. And what happened was they transmitted it
via RF radio frequency for all those,
predigital folks, and it was just this little line of
data in the signal at the top of the screen that was actually scrolled up.
You couldn't see it, but it was all the data, and you could then
(05:55):
access it, translate it, and you could get latest news,
stock market information, and everything else. And it was so much faster
than getting it through the newspaper where most people got
their stock information for the day, reading the sheets, you know, the
broadsheets and stuff like that. It was lightning fast. Yeah.
It was lightning fast. So because it was 20 minutes delayed in some
(06:18):
cases and maybe 2 up to 2 hours in other areas, wasn't it?
And I even I've completely forgot about that as well. I started off
15, 16. That was my hand drawn shots when I was doing that for
the going back a fair bit then. So yeah. Now
now that they did also go back to, like, Edward O'Fayr.
The date do do you do you remember the the I I know you've kind
(06:40):
of, like, not lived in the UK file, but do you remember the the newspaper,
The Daily Mirror, that classic red top newspaper?
It's a trash newspaper Yeah. Essentially. And there
was a a couple of stock and they wrote a book,
about stock tips and and such, and
(07:00):
how to kind of do almost like bed and breakfast type
trade. You put the trade on Friday, and you close it on a Monday. And
that that was kind of, like, the equivalent of it then. And
all they were doing was looking at the top 10 movers and shakers on Teletech.
That was that was their big reveal. And
whatever the leader or, you know, the top 2 or 3 leaders
(07:24):
on the Telitex on the Friday for the week,
you'd buy the shares and close them on the Monday.
And what they would do in the newspaper is they would put their picks in
the newspaper on a Friday, morning for the
morning edition on a Friday. So, obviously, all those orders went
in, but they got done
(07:46):
for front running the orders because they placed their trade
on the Thursday. So they
they were lit so they literally had a captive so it became a self
fulfilling property. And this this went on for about 2 years. You know? And these
these were the the gurus of the day, the pundits of the day, and it
turned out that they were front running or they were basically buying shares, you
(08:08):
know, pumping them in in the Daily Mirror Newspaper on the on the
Friday morning. All those orders would go in. They
they the people who got late in on the Friday saw that it had moved
on the Friday because everyone's, you know, buying. So then they pumped themselves
on the Monday, so they wanted to try and get some late action. And it
just became this little mini bubble that they were
(08:30):
creating courtesy of the the the circulation of print newspaper
of the Daily Mirror. And they did they they did a a short spell in
Her Majesty's that's
Her Majesty's pleasure, should we say. Yeah. I mean, the
thing is you that's a little bit of genius as
as bad as it is. It's a little bit of genius.
(08:53):
I mean, look at it. I mean, crypto, Sean, pump it it's a pump and
nut scheme. That that's essentially what they're doing. It's just they they have their own
captive audience, with the the newspaper. But it goes
on even to this day in Facebook groups,
Discord servers, you know, Telegram groups or or WhatsApp
groups. Know, it's gonna go all all to be fair, John, the the the dotcom
(09:14):
bubble, courtesy of Reddit's Wall Street Bets. So
these things, technology allows this speed of
access. And the same things, you think this is all brand new,
but I've reread re reminiscence of the stock operator recently
a few times short as if we've covered before. And the same
thing was happening 100 and, you know, 120 years ago,
(09:36):
you know, at the 10 of 1900. You know, it's not a new concept.
Sorry. We're all talking about illegal activities there really, aren't we? But the this this
kind of pump and dump and creating hype arounds and
events, it's it's been going on a long time. And I think this this
technology has just sped up some of the bullshit on this industry.
(09:56):
It has sped up the bullshit, and it's also sped up the advantage we have
as well. I mean, when we think about speech information, we
have literally even, I mean,
because everything's really baked into the data right now.
As we get our feeds, there's an expectation, say, with the Fed or
CPI or FOMC or something else. The
(10:18):
speed of information is we know about these events. We don't have to read about
them in the newspaper, wait for a television announcement, or what have you.
We can read it in the charts literally, you know,
in real time. The story and we talk about how the news
is usually a reason to get out of a trade. We talk about all the
different things that happen, but the the speed
(10:40):
of information is really the stories on
the the data. I and we say this to our students all the time is,
you know, turn off the news. You can have an awareness and everything else, but
the real story is in the data.
And that's only true because of the speed of information,
the speed of everything that's coming in. And that's one of the reasons
(11:02):
we're really algorithmic traders. And,
you know, platforms like, yeah, TradeStation, TradingView,
they allow you to code in your strategy based
on the, speed of information, the
the price action, volume, or whatever else you're
doing. But you can use these platforms that
(11:26):
weren't available to us when we first started out
and create very sophisticated
algorithmic strategies and even and this is one of the the
the I think it's a slight difference between myself
and Phil in our styles of trading, which is
I I it was funny because when we first recorded this, I didn't call
(11:49):
Phil out on this or highlight the difference, I would say,
is Phil likes to be the final button pusher.
I like being able to step away and let the computer do
the work for me. But it's it doesn't matter whether it's
fully automated, semi automated, or you're
doing just your if then else for yourself. It's a
(12:12):
checklist bullet point system that you're doing. All
of this stuff allows us to be algorithmic in whether
it's, you know, neural or binary. You know,
like, I'm pointing at one of my monitors here. Whatever way it
is, that algorithm approach
allows you to do so much removing discretion,
(12:34):
emotion, the, you know, the the
I mean, that's the big reason that's the big reason
why I like the, I I I think it might all be
worth underscoring an algorithm. An algorithm is nothing to be scared of. You think you
need a a math PhD, or some coding script.
I like, I'm not the sharpest tool in the box. Like, I'm I'm pretty smart.
(12:56):
But, like, when it comes to software, when it comes
to, writing code, I'm completely clueless. I
I'm as much of a noob as the next person when it comes to that.
And I've got no interest in it whatsoever other than being able to
describe Slink 2, a programmer that I'm gonna hire.
Back when we started, it was trying to test and validate
(13:18):
these ideas just to get back on yours. Sorry. Sorry. I I saw a squirrel
and chased it, John. And the an algorithm, it's just a series of yes,
no decision. It's binary. And I find myself saying this a lot to our
students all the time. It's a binary decision. You know, coulda, woulda, shoulda, this
discretionary interpretation, whatever the question is. Well, no. It's a binary
decision. Has x happened? Yes or no? If yes, place
(13:40):
the trade. If no, wait. You know? There's no subjectivity
involved. And both myself and Sean, we we've been on parallel tracks for, you
know, 25 plus years trying to remove those discretionary
decisions. Again, I hate the subjectivity. But
the it it's the the self doubts when you've
got a question mark against whatever it is
(14:03):
you're looking at. And I think, again, just coming back to the the
algorithmic approach, the the binary decisions, the series of yes, no
questions, it just means that if I am unsure sure and I'm looking
at weird and funky market conditions, which will happen, and you've got
that startled rabbit in the headlights experience, you've
got a base strategy to fall back on a a decision tree,
(14:25):
a thinking process. There's lots of different ways to describe this. But it's just been
able to fall back and go, has this event happened? Has this thing happened?
Yes or no? Alright. Well, no. Well, why am I stressing
over the the coulda, woulda, shouldas, the ifs, buts, and the maybes? It's just
when that event happens or doesn't happen as the case may be, you're either taking
action or in waiting mode. And you're gonna be in waiting mode 95 plus
(14:47):
percent of the time. But to come back to, the
start on that scroll up, Sean, and chasing that down the, the road is
the trying to back test,
validate, create a strategy to get to that series of yes,
no questions. It it would take, if you're not a
programmer, you know, multiple months. I remember some of the first strategy. I would
(15:09):
spend months unscrew because they didn't
have to, it was live days for only. There was no,
rollback feature. You'd had to scroll through the charts 1 bar at a time on
whatever time frame you were looking at. And then if you decided that that time
frame is a little bit whippy and choppy, you had to go back to begin,
start again. And you could be many months going through
(15:30):
validating concepts, validating ideas, and then, you know, maybe, you
know, you're halfway through whatever data sample that you're looking through, and you just
go, you know, I think I've looked at enough iterations of
this to put a refinement in. And you're gonna go back to the
beginning, and then you gotta scroll more broadly with the new iteration. And then maybe
you've got 3 or 4 things. You're not sure which one's working. So then you're
(15:52):
trying to track 3 or 4 variables at the same time because, you know, you
think it's a little bit smarter. And then you forget what piece of paper that
you've wrote it down on. You know? And and you're shuffling. You know, you look
like that guy at memento, Sean, where you write numbers all over and little reminder
notes everywhere. And, you know, it was it was a hard,
long slog. Well, now, as Sean said, you
(16:12):
know, literally a few minutes ago, with the advent of technology,
you can quite literally put if this then that's. If you know a little bit
of code, you can write it. If you like me and you don't, then you
can go use a a tool like TrendSpider, which has no
code solutions. I think on the first iteration of
this podcast, we were also quite excited about the next version of chat
(16:33):
gbt, which had solved its ability to,
do simple math equations, which it was flummoxing itself
with, previously. So you can use basic
speaking language to talk through,
a potential code and get chat gbt or some, you know, more
(16:53):
dedicated programming version to spit a, a very simple code base
out that you can upload to TradeStation, that you can upload to Transpire, that you
can upload to TradingView, or, you know, insert the charting
platform of your choice. It is possible now, with a
very simple, set of rules of just to validate the
concept without necessarily having, you know, the the preferred
(17:14):
money management approach that you might like. But it it's just a a
wonderful place to be and a a time to live where we can, at the
push of a button, test an idea, which is, to be fair, where we came
with our new version, of our latest strategy, the
the the income strategy. That that's essentially what happened because we've just been through this
process ourselves. Last October, you know, quite
(17:36):
literally had an idea, and within an hour, we were able
to validate it by going back through a couple of weeks. Okay. This looks like
it's got legs, and then you can send it off to the programmer. And, you
know, within an hour, it came back. It was a you know, he he he
had a little bit of a time window. And then 2, 3 days later, through
a little bit of honing, a little bit of refining, a little bit of couple
of tweaks, we've got version 1 of what's turned out to be
(17:59):
a fucking awesome strategy to the point where I've stopped doing
everything else to focus more on this and the
variations that has come about from this strategy. So in a very short
space of time, you can find something that that you know, that
little golden nuggets, that is worth your
time and attention. And then the only thing is is does it suit your personality?
(18:21):
You know, can you practically do it? Do you have time to do it? Again,
because not everyone has the the the freedom of flexibility of time.
You know, so that's gonna dictate some of the approaches that you take or don't
as the case may be. And, certainly, both in both our cases,
Sean, we've had the, the approach here of, okay, what do I wanna do more
of? What do I wanna do less of? And we've both of us have come
(18:42):
through the the lens of, okay, I've got to run a
strategy through the lens of I need to have minimal screen time. You
know? And practically from your point of view, you're on the other side of the
world from the US now. So, you know, you've got that ever
present. You know, you can't check you know, you the regular market hours is
used your sleeping time most the time. I know you're a bit of a night
(19:03):
owl anyway. But, you know, practically, you've got to be able to apply the
strategy in real time within time constraints. So we've got to
run through the lens of that as well. And it's it's interesting because
this is where, again, necessity and technology
really fuse together. So one of the things that, I'm
focused on right now is automating it. Because as Phil correctly said,
(19:26):
I'm I live in Paris. I mean, Thailand. You know?
I like cruising the mountains on my motorbikes of
which I keep buying many, many, many. So that's you know, this weekend's
a long weekend. What's my plan? I wanna go and cruise somewhere.
Obviously, that's great for the, for the, you know, weekend.
There's no trading. But during the weeks, like Phil says, I
(19:48):
gotta sleep. I gotta do that. So the evenings here, I can catch
something in the first few hours of the market and get signal. I can
set up an, you know, again, algorithmic
approach, coded it all up. If the
specific condition happens, I get an alert on my phone. I get an alert
in the house. It lets me know, hey. You've got a
(20:11):
condition set up at the beginning of the market. Let's have a look. Both
myself and my girlfriend will then open up our laptops, go play some
trades, close them again, get on with the movie or
whatever else we're doing for the evening. And that's great, but then the ultimate
goal is to take the other stuff that we do. And then, again,
could do this several years ago, but now building a platform. I mean, I'm
(20:33):
even building a platform. This is, again, difference between film myself. I am a
code. I have software development companies, yada yada yada. So we're building a
platform for, you know, Trade Canyon and everything else and our
students, which will allow them to automate all
of our strategies and literally just
say, okay. Here's my risk profile. Here's the strategies that I
(20:56):
want to trade. Boom boom boom. Go.
And it's literally as as simple as logging in,
setting up your parameters, logging out, and letting the
algorithmic approach do everything. Now I
built that originally for myself because I
enjoy sleeping. I don't wanna and I know people who's, you know, even
(21:18):
here, there are traders who are up trading SPX all night,
and they sleep during the day. I'm like, that's that's not my flavor of
ice cream. That's great to have you. Doesn't sound like a fun
time, does it, Sean? You're living in paradise. You don't wanna sleep through the best
part of the day. You know? Yeah. And I was gonna say, I'll give a
shout out to Scott. You know who you are. Who's
(21:39):
specifically, I was thinking of with that. But, again,
the solutions that are available to everyone just
could you can find your particular favor of ice cream. Even applying the same
damn rules and strategies, you can find which way you want to trade based on
your situation. For me, I wanna be if I can be,
completely hands off, fan freaking tastic.
(22:02):
If I have to, you know, noodle a couple of things here and there,
like, you know, crypto markets, 247365,
that's great. Do that any time of day. But for some of the
stuff I do in the US market, which is more
timely, short term 30 minute charts, SPX,
you need to have something going during market hours. Other
(22:25):
strategies, I can set them up during the day
here. For the next day, I I don't even have to look
at them, and then I'm just doing it aftermarket stuff for the longer
term trend trends. So all of it is algorithmic,
though. And, yeah, like Phil mentioned, there are no code solutions to help
you not only test your ideas,
(22:47):
analyze them, you know, and do backtesting.
It just give you a broad scope of is this does this
idea have legs? And then, you know, with real time data
access and access to developers and everything else, you can
then go and create whatever you want. I mean, I regularly
hire different I've just actually spent a bloody fortune,
(23:10):
on hiring developers for this new platform that we're building
and managing that and everything else. You don't have to go that far. You can
go find a freelancer once you have a valid idea and an
algorithm that works, Be it our strategy, your strategy,
freaking, I don't know. I I don't know. Bungle book? I was gonna
say, bungle from rainbow or something like that. It's got a great strategy
(23:32):
or Zippy. You know, whatever it is, go you
can go find someone to code it up and then make
that either an indicator based on your idea
or even a full blown automated trading system with
Python that runs on your laptop. You know, there's so many
different approaches that, again, just open
(23:55):
up an entire world of trading. Right. I
mean, to me also It's it's the most exciting time to be a
trader right now. I mean, we're between machine learning,
AI, all the real time information, everything
else. I mean, this this to me this this is what fires
me. Other than motorbikes, which everyone who knows me, I'm bloody
(24:16):
crazy about. Trading and trading automation and the
technology behind all this, that's the second thing that fires me.
I'm just gonna say, Sean, one of the things that would would both of us
are dancing around is that
technology is not a replacement for some of the
fundamental skills. No. Like, you don't now I'll I'll say
(24:39):
along the same vein, you don't need to have
multi decades of experience on the hard right edge of the charts. You
just need to have base level of competency to
make this work and the confidence to go and and kind of
explore developing your own strategy. So it's not a case if you've
gotta know down 3, 3, 3, all the other kind of nonsense, the wiz bangs,
(25:01):
the tools, the red blue indicator, whatever the the the flavor of the day is.
You just need to know one thing reasonably well. And like with
anything, you just need a certain level base level of competency
to kind of start down this road. In fairness, we
because it's ever present on our mind, we've kind of focused on the
strategy development side more than anything. But there
(25:24):
there's a whole world of data analysis. I mean, one of the things that we
were both quite excited about when we've spoken privately
is the ability to oh, what's the what's the right word I'm looking for?
To to talk with data via, a a
chat gbt type plug in. You can wear and air in data.
(25:45):
It's the data. There we go. Interrogate. That's the word I was looking for. You
can kind of interrogate the data whether it's your own personal trading,
whether it's some data analysis that you wanna do, you don't have to be a
pro in this. You can just ask basic questions of, okay,
what am I you know, know, for example, let's just say that, you know, I've
got my, brokerage accounts. I've uploaded all the, the data in a
(26:06):
spreadsheet to, ChatGbt, and you can start to
have a conversation with the data, effectively. Okay. What are
the the the best trades? What are the worst trades? What are the win streaks?
All the base information that you can get. But maybe you can start saying, well,
what day of the week is my best day? What's the worst day? You know,
are there any, outliers that you may you that you might need to know? You
(26:27):
can start to kind of have conversation with the data. And it sounds a little
bit crazy saying that, doesn't it, Sean? But you can have this conversation with the
data. You don't have to be able to insert. You can ask these,
chat plugins to talk to you, explain
the data to you. And if you've got a question, you know, you don't have
to feel silly about, you know, asking a financial adviser. You can ask, you
(26:49):
know, an anonymous, plugin in simple language and have it spit
back to you. Hey. Explain this to me in layman's time. Hey. You know, go
a little bit deeper on this. You know, is there any anything that should be
worried about? Some best days, worst days, what's the best trade? You
know? Whatever question that you've got about the data, it can
come back at you even if it's a generalized, hey. Interpret the
(27:09):
data for me and give me pros and cons. You know? You can be very
open ended with some of the the things that you can do now with these,
the the technological advancements. Yeah. No.
Absolutely. I mean and you touched on something I wanted to highlight as
well. And this is teddy bear, Sean.
There you go. I'm not a swipe your line for a change.
(27:32):
You're right. That's what she said. Yeah. So
one of the things that this
environment and being algorithmic as well is
shortcuts the need for experience. You talk about the the far right edge and
the experience there. When you have an algorithmic approach
and this is something that I I tell a lot of our newer students who've
(27:54):
never traded before and who are just learning the the process and and
this world is it doesn't
matter if we if we're looking experience doesn't
matter. If we're looking at the same information,
the, you know, we're looking at the same rule set and
we've got, you know, this thing happening, this crossing here, whatever the
(28:16):
rule is, we're gonna get the same
result regardless of our experience. If we're following the same
algorithm, we're going through the same checklist, and we're doing the same
thing, We're gonna get the same result. Now,
obviously, it depends on the money you're putting in and that that that that. I
don't mean exactly the same numbers, but we're gonna get the same
(28:38):
output in terms of if we're looking at the same information, you
know, like, we we've got our rebel income system that,
is absolutely fantastic we're doing right now, which is 30 minute SPX
system. Again, if we're looking at the same
information, doing the same execution, we're gonna
get the same results. Whether it be a 100% return on capital, return
(29:01):
on risk, etcetera, whether we're having if we have a win, we have a
loss, we'll get pretty much the same. Now, obviously,
there's some nuances in that, but the the reality is if you're
following a system that has a
positive expectancy and you follow that
exactly, you're following the rules, you're following the algorithm,
(29:23):
then those results are gonna be the same
for everyone else following that same system. So it eliminates
the need for experience and
then, thus, all the emotion, discretion, the
learning in the trenches, boot you know, boots on the ground type environment
and, you know, like, the you know, all the other things that you need from
(29:45):
a psychological perspective, it's minimized.
Because you're straight to the the sorry, Sean.
Sean's a kind of we used to call it,
very regularly a production line process. Like, it was a factory because
it's replicatable regardless of experience. And
that that's the key point there that I just wanted to underscore. It's replicable. And
(30:08):
and to be fair, this is what pleases us most about the way that we
approach trading. It's not a discretionary viewpoint. It's not an opinion.
It's not a or I you know, there was a 5 wave, but, you know,
on a 1st day, it was 6 waves, and, you know, you can interpret it
differently if you have the start point there. You know, there's a little bit of
whimsy involved with some of the processes. And it's not that they don't
(30:29):
work. It's just that the interpretation well, there's
there's the word. It's open to interpretation.
Unless you've got an algorithmic approach, a rule set, an if this,
then, that that is replicable and repeatable by
anyone regardless of experience. You know? There's obviously a learning curve with anything. You gotta
learn some technology. You gotta learn, the process itself just like you would
(30:52):
do at a factory. You've gotta learn how the the the factory, where all the
component parts, you know, which parts are put together with what bit first. It's an
IKEA flat pack system. You've got to put, you know, socket a
with socket b. You know what I mean? You've gotta do that for there's always
always gonna be a learning curve. But when you've got that, it's really simple. You
know? You can follow that process. It is repeatable, and you're gonna get a
(31:13):
comparable results because we're all looking at the same thing, the same process, and
we're all getting the same outcome, which is wonderful. And that that really
does, lift my spirit, Sean, when we get the
feedback from our students. I love that. And the other thing as well, which I
think is is very important, is
eliminating the coulda, shoulda, would. Again, this
(31:35):
is something I was actually talking with a student about earlier on. Lit literally
today, just talking about how
important it is to remove a lot of
that indecisive phrasing. When you have a
checklist production line process, however you want to refer to
it, when you have that process in place with the rules
(31:58):
you follow, there's no ambiguity
about what you kinda shoulda, woulda, woulda. When you hear yourself
saying that language, I should have or I would
have if when you hear any of the
as I call them, You know? Could've showed the odors. When you have any of
the odors coming into your vernacular, you're fucking something
(32:21):
up. You hear some bovine come into this. Yeah. There's
no other come into this. Yeah. The cows orders. Exactly. I
was thinking that even as I said it, I'm like, there's a joke. You say
that I was smiling. I knew you were thinking the same thing. But yeah. So
I he's expecting it to be in a limited fashion. It really is,
at the end of the day. So alright.
(32:42):
With that being said okay. I mean, we've kind of danced around
a lot of the different ways that tech comes into as as an assistant,
not a replacement. And this is the same I I we
could get on a soapbox about AI because a lot of people ask me one
of the first things people ask me when we develop systems is like, oh, is
there AI on this? Like, it's the holy grail of trading.
(33:04):
Look. Machine learning, AI, and everything else,
they are assistants. They're data interpreters. They
do analysis. They can assist you in a lot of different ways. But just
like people are worried about AI taking over, their
jobs and replacing them and everything else, there's some things that
AI will do better than humans. It's gonna be,
(33:27):
you know, all sorts of different ways that AI is gonna influence and change. I
mean, this is really, to be honest, this is like the industrial
revolution all over again. We have the computer revolution, the industrial
revolution, and, yes, we're having the AI revolution. But those
are gonna get ahead before I get on you know, anyone else gets on the
soapbox and you know? I've got a lot of creative types
(33:49):
in my audience and in my, inner circle as
well who who don't like AI because they feel
it's gonna replace creativity. Honestly, it's not. It's
an assistance. Right. And this is even That's an interesting point there,
Sean. It's not gonna there's some things that we'll get rid of completely, but at
the same time, it's also gonna create I mean, when you look through technologies through
(34:10):
history, from the Luddites back in, you know, 17 fifties, he was
smashing up, weaving machines. He thought that their
jobs were being replaced. Actually, created more jobs than it re that it
replaced. And that's the the new job side of things.
And I think just, piggyback on your comments, I don't think it's gonna replace
the markets. I mean, if you had AI and everything was
(34:33):
perfectly driven, the markets would suddenly cease to exist as a
fear that I've heard a few people mention, an irrational fear for that matter. But
if you think about it, like, everyone's got different concepts and ideas.
Everyone's got different requirements. There's lots of hedge funds, big
institutions that do things at certain times because
it makes sense from either from a tax point of view or an investment point
(34:54):
of view. They've got certain ways that they've got to approach things from legal
standpoints. Individual traders have got different personal preferences,
perspectives. We've spoken about the personality of a trader in the past, Sean,
and that is gonna be reflected in the way that systems and
and that these tools are used. For example, you know, we've mentioned a few of
them today, haven't we, Sean? Where our personal preferences, it's the the number
(35:16):
1 needs to be minimal screen time. Number 2, it needs to be rule based
so I could so I don't have subjectivity. You know? And they're the the
top two criteria that we're always thinking about. Then it needs to be
practical. I don't wanna be up at 3 o'clock in the morning, you know, doing
the the you know, putting the trades on. You know? It has to be realistic
with its approach. And then personal preferences, you
(35:38):
know, maybe someone's more aggressive, maybe someone's more conservative. You know? And these
are all gonna be footprints and inputs into the way that the market moves
and the machinations around that. So it's not going to, suddenly
get rid of the stock market. If anything, it's probably gonna make it more
efficient because of the, again, the speed of information,
the technology. In a perfect world, we'd be
(36:00):
thinking that more traders would be making smarter decisions, but we know that's not
true. Because, otherwise, some of the technological
advancements in the past would have, you know, assisted
that. So the market's not gonna cease to exist, and this isn't gonna replace the
trader because everyone's got different perspectives, viewpoints, and
objectives when it comes to trading. Absolutely.
(36:22):
Absolutely. So at the end of the day, yeah, it's an assistant.
It's you know, those are gonna get ahead, know how to use AI,
know how to use your chat tbts, your sunos, your your
all your your mid journeys. Whatever
AI is going to help you, like, Google. I mean,
they use Gemini as it's now. It was Bard now. Not calling it
(36:45):
Gemini. They're integrating that into all the Google Docs and
your work you know, Google, your emails, your anything you're
doing, for your day to day. So same as Microsoft's integrated
into their search engine. It's there. I can
ping, Bing in real time, get
information about today's stock market. I can query
(37:07):
the world and get exactly back what I need refined
down. I can go tell it, oh, I need this, this, this, and
this, and I need it in an Excel,
table, and it'll give it exactly that. So the
Copilot, your Geminis, and everything else, you know,
they're they're there. You've got VR. You've got, you
(37:29):
know, social trading platforms. You've got all sorts of nonconventional
technologies plus the conventional technologies. They're all
assistance, but nothing can replace
the human trading element in a lot
of what we do. And at the end of the day, we are all individual
(37:49):
traders. We're, you know, most of our audience are retail traders. We got some institutional,
investors and everything else in our audiences and listening to
a lot of this. But most of our audience are retail
traders, which is individuals with their laptop or their computer or their
phone looking to make money in the market. So all this tech is
literally right there to assist you move forward and do
(38:12):
it. Don't be afraid of it. Embrace it.
Learn it. Whatever you need to do. But, again,
the advantage now is the advantage we did
not have when we first came up. We kinda grew into a lot of
this, you know, really dating ourselves here. It sounds like we went
to school uphill both ways, you know, and in the
(38:35):
snow, had to paint our toes brown and you know, so we had to paint
our feet brown and tie our toes to pretend we had decent shoes, you know,
all the rest of that kind of shit. But when we first started I
thought I thought you were one of the first to have a ticker tape in
your own household. You were that, well endowed. Yeah. Pretty
much. See, even then, you know, that was revolutionary technology.
(38:56):
You know, the the the wire. It was called the wire because it was a
data delivered on a wire through Morse code. You know? It it's you know? And
that was revolutionary, you know, 120, 130 years ago. You know? It
it's it's it is a wonderful world we live in, and it's only gonna improve.
I think if we always look on the positive side rather than default to negative
is equal. I think sometimes, Sean, human nature, it we kind of
(39:17):
default to the worst or the negative side of things. I think if we
embrace the positivity behind it, and move with the
times, You know, it it can only be seen as a positive,
addition to, you know, anyone's trading routine.
Absa bloody lutely. So I think that's a good place to put a pin
in the show notes and say done. Put a big x to it.
(39:40):
We actually got a successful recording this time. So, again,
appreciate your time and attention. Do tune in next week. We're gonna be talking about
the psychology side of trading in this kind of, like, epic series
where that's number 7 of 12 that we're you know, of
topics that we're gonna dive into. And I think that one's gonna be a
very interesting twist because a lot
(40:02):
of people honestly, just to kinda give a preview, a
lot of people skim over this aspect, and we try and minimize a lot of
the psychological aspects to help people
navigate this, but you can't ignore the psychological aspects. You can have the
best strategy in the world, but if your head isn't in the game, you ain't
gonna be able to do it. So I'm looking forward to that one. Any last
(40:24):
comments from you, Phil? No. That's it. It's a good place to finish up.
Technology, it is the future, not the past.
There you go. Rock and roll. Alright. Thank you for your time and attention.
See you same bat time, same bat channel. And Phil?
I think you stole my line, have we? I was oh, there we go. I'm
too late. I don't remember where we are. There you go. Too late later. Bye,
(40:45):
Finn. I'll see you at same time next time next week. Thank you. Or from
our point of view, in 5 minutes. No. You're alright. Alright.
Cheers. For
more cutting edge trading advice and a free trader workshop to help you build
a personalized trading plan and make smarter trading decisions,
go to tradecanyon.com now. Futures, options off futures. Stock
(41:07):
and stock options trading involves a substantial degree of risk and may not be suitable
for all investors. Past performance is not necessarily indicative of future results. Trade Canyon
Incorporated provides only training and educational information. If you actually understood and listened to this,
then that means you are awesome. Congratulations and well done. Notice, this product
may contain nuts.
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