[00:01] trading industry has sold us an absurd and very dangerous idea that you as a increasingly complex strategies with very cool, eh, very strange names, with concepts that seem very sophisticated, with an
[00:15] all, obviously, without using indicators, because indicators are years.  Or you might even need to use tools that Strategy One, to generate thousands or millions of strategies in just
[00:30] a few weeks, so you can select the most successful ones. Currently, those are the two approaches that exist and that most traders use of these things obviously work, especially if done correctly, the reality, what
[00:43] traders, which is making money, is that some of the most successful strategies you'll ever find have been right under your nose for decades in where to find them you wouldn't waste your time on all this.  But practically
[00:57] considered old.  Well, one of these old strategies that nobody uses because it's not as complex, many others out there today, has generated what you 're seeing on screen right now
[01:10] , from 1987 to 2026, to May 2026, right now .  And as you can see, he hasn't stopped winning for a single moment. 5 years ago, for example, you would have a lot of money today.  And it's a
[01:24] a day on area candles.  You only need to look at the chart once a day when the market closes.  Only that in oil would have given you this curve you see on your screen.  And not only that, but it's a strategy that only uses
[01:37] moving averages.  Nothing else.  I know this is going to blow many of your oil [music] has been working for 30 years, winning, as you can see here on screen, just by using moving averages.  And since I know many of you won't
[01:51] Servi Sánchez, a professional trader and manager of Darwin Sy, who manages over $17 million on Darwinex with his trading algorithms.  Someone who has been in the markets for 20 years and uses strategies in his portfolios of
[02:06] are generating absurd amounts of money for him today, is going to explain to us what its rules are, he will show us the code directly so that we can see it, he he has carried out in Trade Station since 1987 applying commissions and slippage
[02:23] so that you can see that the strategy, if applied to the letter, is a here to the channel every so often, every month, so that he can teach us one of the strategies they use, one of the ones they look for, one of the ones they find in places where
[02:36] he himself, who is a professional trader and has done thousands of backtests, can do it on his own platform and share it with us. want to do backtesting, you don't want to check if the strategies work, you
[02:49] that they win with their strategy and then you apply it, right?  Because if someone wins, it means in reality, most of the strategies you use and see on the internet we're going to try to bring Sergi, who is a professional, here to teach us
[03:02] strategies that actually win, that have been tested through all their filters, have seen and evaluated, so that if you've been losing money in trading for a while, find the winning strategy, at least you'll have a path to follow.  But what's
[03:15] here on screen and which we'll see in this video with Sergi, aren't even strategy that has a very simple entry point.  He's going to show us different very simple inputs that he's applied, with an output that's always the same.
[03:28] want to improve this strategy that can be improved, on May 27th of this a live stream here on the channel for all of you, using all our strategy.  It will teach us step by step how to create it, how to optimize it,
[03:44] how to know if what we do in backtesting can then be passed on to the real thing, trying to keep the results more or less the same.  And in general we're going to do an advanced live stream to create trading strategies using this
[03:56] same strategy.  There you can see the code again, the rules, you'll see what's we'll chat, I'll be talking to you in the chat.  So I'll see you there on the create profitable trading strategies with a real professional trader.
[04:10] the landing page that I've included below in the description of this video.  Click down there email and your stuff and when the live stream is on we'll let you know so you can talk to Sergi so he can explain the rules of this strategy and
[04:23] show us how we can use it. Enjoy.  Hi Sergi, how are you? Welcome. How are you, Victor?  How are you?  It's a pleasure to .  Thank you for coming.  We weren't talking, were we?
[04:35] going to tell you that, I don't know when the last time was.  I think you came for strategy we discussed might have been the ORB, does that ring a bell? handsome, huh? Yes, people like it.  In fact, as a
[04:48] the students and there is one student who has come up with a That's the key.  That's the key.  Seriously, seriously, a give an idea and from Arturo, in fact I have an interview,
[05:00] , I have an interview published with video. No, there are no real stars, really.   Well to try and encourage people to do this again. And
[05:15] this, because when I told you I think you did, and from there to this video, the whole strategic trading thing, the builders, is becoming very fashionable. A lot of the world of algorithmic trading or trading in general through
[05:30] As if it were a solution, well, I don't know, simple or quick for creating many times about how that might not be the best way to you guys.  So, I wanted to bring you here so we could talk
[05:46] a little bit about that and so you could teach people the process of creating a strategy from scratch without needing to use some kind of builder.  Do you want to Hey, what do you think about this? Yes, well, in case anyone doesn't know, I
[06:00] mean, the builders aren't bad.  Ultimately, builders are tools, right?  And in the end, like all tools, if you learn to use it well, it can be useful to you.  OK?
[06:14] What I don't like, and those who follow me will have heard me say this many times, is what you were just saying, right?  In other words, to learn or for that to be your entry point into algorithmic trading, okay?  It's
[06:27] calculator without having any idea about mathematics.  So, well, I don't like it, and it's true that there's a lot of training, a lot of academies focused on it,
[06:40] because it's a very attractive idea because it apparently solves that barrier that many people tell us, "Hey, I have to learn to program, how will I find ideas?"  You were just saying, that is, it
[06:54] solves things, apparently it solves things that people are worried about and think that's why it ca n't do it for you.  OK.  So, they're not really barriers, they're not real barriers, or to put it another way, they're
[07:09] not barriers that anyone can't overcome, okay?  These are nowadays; that is, languages ​​are very easy.  AI, for example, now I'm entirely with AI.  So, it's probably getting better and better and it helps us.  It doesn't
[07:26] replace judgment, that is, in the end you have to have a basis, understand, that is, in order to be able to decide if what she has done makes sense Completely. Understand.  So, but if you have good
[07:39] Understand.  So, but if you have good judgment, it helps you a lot, and to program more and more, I mean, for example, the whole project very briefly, because I can open a big can of worms
[07:51] issue of the small caps that we made several videos with you, that Isaac programmed there, well, everything, obviously Isaac is a professional programmer, he knows it, he knows how to program, but obviously he has
[08:05] used the help in a huge way connect it to Kitc te, meaning you can set up a whole architecture, okay?  In other words, it helps you a lot, it helps you a lot, but it's important to have good
[08:19] I'm going back to builders, I'm going back to builders. So, what you're saying happens. So uneven approach, but there are many people who crash and burn
[08:37] very easy to just put systems out there, and they do, it's true, they do come up with a lot of systems, but then you put them into practice and they don't work, you know what I mean?  In reality they fall, so they fall.  And that happens to a
[08:50] lot of people.  Because? because in the end they don't start from an idea, because in the end they don't start from an idea, from an advantage that is ours in our methodology, what we believe is best.  OK?
[09:04] And well, based on that, I've prepared a strategy like almost from a book. Fantastic.  Yes, yes.  Um, can you explain a little bit what the idea behind the strategy is or what asset it is?  What did you base it on?
[09:20] Well, look, I decided and it was like that because I said, very fashionable and all, whole issue of this war conflict and all that, now it goes up, now it goes down, it's
[09:34] really extremely volatile. And I say, well look, let's look for a are going to look for a strategy regarding oil. Oil is primarily a trend-driven asset, although it has
[09:47] also happened to gold, for example, which has been but there had been years before it seemed like it wasn't, and there were people saying, "Oh, gold is no longer trending." Well, in the end all
[10:02] correlations or trends go through moments of go through moments of reversal, and now oil had also gone through a fairly sideways period and now it
[10:15] patterns, right?  [laughs] Mm.  And it's a trend-following asset look for counter-trend strategies, but I'm focusing on the trend, okay? I picked up a book that was lying around, I do
[10:30] n't know if... Well, then you put an arrow there on the book.  It's there there because pointing here is very complicated.  Something like that is what comes out that's it.  [laughs] Well, this is Kaufman's non-
[10:44] Yes, it's yes.  People will see it.  Add an image here too.  screen so you have it clear, eh, it's also surely better.  Well, it's a very famous book that we've talked about many times in the course.  We talk about it a
[10:56] lot, people who don't know the Bible of trading have 10-something pages and on top of that, with small print, I mean, it's truly a marvel. So, just like I was saying with Laya, I have that
[11:11] whole book in a custom GPT file that we made ourselves to use for reference. Mm.  And I looked in the trend chapter for a summary and so on, and with that help I extracted the
[11:24] so on, and with that help I extracted the strategies from the book and even programmed them for me.  I've been supervising, at the beginning I made some mistakes, made some small changes and now, well, the
[11:38] strategy has worked out for me.  Also, I told her to give me the commentary so I could, I mean, make a video, you know, give me the commentary so it's easy to explain, you know?  He made it very easy for me too.
[11:50] Then I went to the TR Station and there I worked on the strategy a bit , okay?  But it has been a fantastic starting point, a simple one, not extremely complicated, having the free one, obviously,
[12:05] and that's it.  And from there, I have a strategy as a basis.  That's what we always explain.  Ultimately, they are starting points for working.  Well, good starting points, eh, well, you'll see, a good starting point to then
[12:20] see, a good starting point to then develop a strategy that can become oil. Yes. And something else that I think you've said knowledge to know that oil is a trend-following asset, and therefore you have to
[12:32] these characteristics.  You're going to a section of a book you have that's about trends.  So, there are already parts of a series of knowledge trend is, an anti-tend, and how to exploit them.  And also something that I find
[12:45] interesting that many people don't see in a book, we talked about this on another occasion, I think with you, uh, you have strategies that you can have a very good op sample.  In other strategies that were developed up to 2015 or 2010, and you have that entire period of
[13:00] whether what the author tells you with that strategy worked back then and awesome. This is fantastic.  A good friend of mine , Alex Ríos, also works in this field; he's a professional and a
[13:15] huge fan of it.  We often talk on WhatsApp, I found a book from the 80s know, he loves this because it's just like you said, that you find a strategy that isn't normal, that you don't have to do anything to him, eh,
[13:29] do anything to him, okay?  You pick it up from the book and it already has a winning curve, a decent profit factor, we could say, okay?  Decent. Of course, that's gold, because imagine all the data you have
[13:44] real thing. Absolutely, absolutely.   You Yes, yes. So, what happens is that it's a good starting point, and you put it in place
[13:57] and say, "Hey, well, it's not bad, it's not bad [laughs]. Yes, but from there, well, you can maybe work on the outputs, you can maybe look for a filter,
[14:10] but the core is already that, the core of the system, and they're fantastic starting points . And there are many telesemics enthusiasts who are big fans of this methodology because it's so straightforward . If in the
[14:25] out-of-sample data that hasn't been seen, and that, like I said, is very difficult to debate because in the end, any tool simulates with historical data, and obviously, realism... The other day someone
[14:41] asked me, in a live stream, what is it? I mean, well, you only You know? That's the real one. The other
[14:55] things increase or decrease the probability of things going well, but only the real one truly tells you if something is robust or not. the account, right? [laughs] Absolutely. Okay, so you can share a little of what
[15:08] Yes, look, I have the entire historical data for oil here. I have it all from around for oil here. I have it all from around '87, but oil is an asset that, obviously, this is the adjusted futures chart,
[15:22] and this is a matter of data construction; the program does it, right? It's not much we were saying, you have to have judgment, you have to know how to do it, but the program does it, okay? It's a
[15:35] program setting in Teleson that allows you to create these adjusted continuous charts . Okay? So, well , it's an asset that, in this chart adjusted to 15, has
[15:47] been at 300, 550,  I mean, it's the enormous, right? variability it has, right? That's 2008, remember?
[15:59] Well, do you remember? Uh, I remember this brutal drop in 2008. The prices, I say this in case anyone notices, which is traded at. That doesn't matter to me. What matters to me is that the database is
[16:14] and that it's representative of what happened. Whether the price is the same or not, right now it doesn't matter to me. Okay? For analyzing a system, I mean, right? Uh, that goes on a daily chart. It depends on what you
[16:28] have to do; it might matter to you. Uh, this again, as I was saying, is configure that, but since what I want to do is a good backtest, uh, I've configured it to be representative, and I don't care if the
[16:42] price was 500 or 400.  It happened at the time, shall I explain? Uh, I'll clarify because with oil, in I've avoided that because of this adjustment, okay?
[16:54] Oil, for those who haven't been in the trading world for many years, it'll be shocking. I understand, I understand, but oil traded negative. Yes, yes. This happened. Okay. This is in case anyone hasn't
[17:07] ask, they'll probably explain it to you. It's something that explain it to you. It's something that apparently doesn't make sense, but the containers. If you went there, you picked them up. Yes, yes, yes. There
[17:22] Hello. [laughs] Yes, yes, yes. And they paid you. Thanks for taking it. Yes, yes. And on top of that, they gave you money, you know? They gave you money for taking it. Well, [laughs] that's how it was. That's right. Strange things in
[17:37] the markets. So, I  Here I've created, I'm going to show you the code now. Let's see, wait, I forgot something, but briefly, the code is what we call... it's very similar
[17:51] to what a builder does, okay? We call it... it's an internal name, uh, not a constructor, we call it, okay? In the course, we give one, for example, a very complete one, uh, where a
[18:05] consultant simply lets you input several strategies and with an input, with a small switch, with a system parameter easily—it's worth one, worth two, worth three—you change
[18:19] okay? But here, what you were saying, what I've done is... make it trend-oriented, that is, search only for that type. Okay. I've added only seven entry types. So, this is
[18:37] easy to read here, Victor? Yes, yes, yes, it's perfectly clear. Uh, it's easy to read. okay. Well, a simple moving average, a  A smoothed exponential moving average, a weighted moving average, a regression line, okay? A breakout, it's a Donchan,
[18:52] mentioned several times, typical, a momentum line, and then two moving averages, okay? Two confirmation moving averages, uh, they're all, well, you see, moving averages, regressions, all very simple things, and momentum, okay? That is, it
[19:05] simple things, and momentum, okay? That is, it 's, uh, and the classic Donchan, the in the credentials. So , let's say you've had these seven different inputs and what you do is modify them, playing with them
[19:17] until you see what the configuration is, right? Of course, I have the complete code with some tweaks that I, uh, in the first phase, didn't fine-tune , but it was actually done, it was taken from the
[19:31] n't read all of those comments, I mean, I told her, it was to followers of the trading psychologist, it requires functions from Kauman's book. book. That is, the book has some
[19:46] the code. It's a technical matter, but I already told him to do it this way. He did, and that's it. And it's explained, okay? It's been explained perfectly so that someone without
[20:00] programming or technical knowledge can read it and understand what it is, okay? In fact, from here you can easily come to the concept we've talked about before we could create pseudocode
[20:14] can adapt it, you see? Because in the end, well, if you give it to me in Easy Language and I don't have Easy Language, well, with the pseudocode you can translate it with AI, okay? So be careful, I
[20:27] okay? So be careful, I recommend that you have some basic knowledge, right? You don't need to be a Python expert, but you need to have some basic Python knowledge, okay? So that you can translate this pseudocode into
[20:39] Python without  No problem at all, you know? I mean, if you have even a basic understanding, and probably just do it in one go, right? I mean, because it 's so well-detailed with all the code that I think
[20:52] frankly. And well, that's it. And in the end, All this green stuff you see is comments. This doesn't matter, you know? I mean, it's mostly comments. Yes, yes, yes,
[21:05] because it's very well-commented so that anyone can explain it. The code starts here. I've also added a simple money management system. Well, I 've added a bit of the methodology we
[21:20] use, Víctor, which is to add... and that's it . Well, and beyond the code itself, which in the end is just a tool,
[21:32] I've done a small analysis to see how each one was performing. I've done a slight optimization and I've done my studies here so you can see it.  Okay? It 's a simple optimization where
[21:46] I then do my analysis. Obviously, we explain all of this we do it, and based on that, I've seen some averages. So, the objective of this analysis isn't to
[22:04] create a finished system, but to evaluate which of those seven entry methodologies has the highest probability of being implemented in a real system. That's all it is; it's not a complete system with its exit points. I
[22:19] I did incorporate a little money management because it's an asset that fluctuates so much in price that if you only use one contract—that's what happens when you work with systems on daily or weekly charts, right?
[22:33] Because, of course, a contract is completely different when the price is 10 than when the price is 130. The value of one is very different. Here it's worth very little, and here it's worth a lot . Do you understand? So, I've
[22:46] simply applied gentle money management so that the contracts  They need to okay? I mean, so that buying 11 here, you understand? Because otherwise, a negative streak, of course, a
[23:00] higher can mess up the statistics of a good streak when the price is high. do that, what happens? The gain, the loss from the period when the price is matters, what gets eaten up
[23:13] what gets eaten up because the value of the point is the same, but the percentage, markets ultimately move in percentages. A 2% course. In points,
[23:25] right? So, in the end, that makes it impossible to analyze a curve if you don't normalize it a bit, and that way, I can The curve would be quite strange.
[23:39] These are, let's say, the result, right? It's the result of the side  On the long side, with a profit factor of 1.65, a system that barely has, of 1.65, a system that barely has, I think, two parameters,
[23:53] a moving average. Very simple, okay? I mean , this is extremely simple. It simply uses the exponential moving average
[24:06] the exponential moving average and enters and exits based on it. That is, that's an obvious improvement that needs to be made, okay? Besides adding a filter,
[24:19] evaluate the entry, okay? That is, well, does the entry have any kind of advantage, does it make any sense, uh, could there be something sense, uh, could there be something tradable there, and uh, the answer is yes, okay
[24:34] answer is that in that case, the exit—you haven't set any kind of exit—uh, it exits via the opposite exit, okay? That is, if you enter based on the moving average, then when it falls below the moving average, it exits,
[24:47] okay? That is, the same. In that case, yes. In that case, yes. No, it doesn't have  Why can it also be used? Uh, I mean, we, well , it's not exact, but Nemesis Gold, which we trade, as you know, in
[25:02] SO, well, we trade a trend-following trade, this, called Nemesis, and it has a small very small. It's quite similar to the entry exit, okay?
[25:17] I mean, no, no, no. In trend-following trades, it 's quite common, but it doesn't mean it's mandatory. Uh, I mean, it wouldn't be...
[25:32] nothing is free. I mean, normally a trend-following trade, since it's more trend-following and manages to take better advantage of, in this case, the upward movements, is like that, okay? It's
[25:44] by exiting on the opposite signal, but it returns a lot, okay? I mean, when there's a really big reversal, which oil has has some, it takes a long time to exit. Okay.
[25:57] goes faster than its average. So, in the end  Normally, when it catches a good moment, it's capable of making incredible trades, okay? Incredible, but it depends on the speed of the moving average, obviously,
[26:11] So, well, hm, is it good or bad? Well, it's a matter of things. This one, for example, lets it run longer. It's a different setup.
[26:26] 's the same. It must be this one. It must be this one . That's a different setup. I different setup. Yes, in that one, that one is a bit exactly what I was saying, it lets it run a bit longer,
[26:42] you see what happens there. Yes, yes, yes. It takes a pretty considerable hit, and it has worse ones, it has many worse ones, okay? But this can be mitigated with an exit,
[26:57] okay? With an exit that takes it out very trending assets  It's good to have, if you have several strategies or
[27:10] several sets, which might be in a portfolio, it's very useful to have one like this crazy, you know, it does? Well, you can really pick up some really, really powerful runaps, you know? You can pick up some really, really
[27:24] example, or this one, for example, no, this one, for example, well, it hasn't been bad, has it? It hasn't been bad. So, so, you see? This is the curve of this version, which is similar to the other one,
[27:39] Okay. And how long has this been going on? Since what year? I've included all the historical data, and it starts as it is on a daily chart. It 's a system that uses daily bars,
[27:51] 's a system that uses daily bars, on a regular hourly basis, and it goes back to '87. It's all the historical data I have on the platform. I simply included everything because it was on a daily chart, and I wanted to analyze what
[28:06] I emphasize in the objective.  Right? To validate or see if this type of entry can work or not. Okay? And this is up to the present day, I mean. Yes, yes, this is up to... Well, when I
[28:22] data, but now I've put it all in and it's up to last Friday. Yes, I mean, it's up to date. If we look at the end, in . Yes, yes, the last one has been fantastic.
[28:35] Yes, yes, yes. Well, a trend-following stock, the good thing about a trend-following stock, Victor, one of the things a trend-following stock has to have is that if there's a be in it, okay? Otherwise, it's not a
[28:49] that can also be good. For example, Apollo, which also operates in the segregated stock, missed the NASAQ rise, so it In the end  I mean, if
[29:05] Nemesis had been there, he would have definitely caught it. Okay. So, of course, when this happens, they catch it, unless it's just a single bar that they don't have time to process. Well, there generally speaking, if there's a more or less sustained movement,
[29:18] they catch it because in the end, whether it's a moving average, a breakout, a Donchan, whatever it is , it indicates price direction, and when that absolutely. So, in the end, that's why it made
[29:33] Spectacular. Here, yes. And here, look, you can see it adjusting. Here it has six lots. Here, even though it's winning, it adds four because when Okay, here it adds five. That's
[29:47] I would trade, but it's what we use to assess the simply decides the number of contracts based on the contract's nominal value, right? All those kinds of things that some people will
[30:01] follow and some won't. I understand that, but that's what we're talking about, okay? When we talk about which things and all that, well, all those things you have to know, you have to learn them. They're not
[30:13] explain them to someone, that's it. They're not that difficult. Like how to adjust the charts, what the point value is, why we use money management, where we look for ideas, how we
[30:27] validate them, why we do it this way, why we do it that way— all those explanations that don't depend, and this is very important, and I insist on this a lot, Vitoral, on any platform. I mean, I use
[30:39] Station, but I could use MQL or I could use NinjaTrader, it doesn't matter to me. I mean, the Yes, yes, let me explain. It's not the methodology itself. That's what I totally disagree with. It's not
[30:53] based on a platform, it's on a specific, closed thing, where you depend on what it gives you, period.  Do you understand? I think the key language. You're learning to speak a language here, and that
[31:05] language doesn't depend on who speaks it, it depends on how you understand it. You'll have your own accents and quirks, your own ways of speaking, your own dialects, but in the end, the language of an algorithmic trader, no matter how many tools you have, how many
[31:18] platforms you use, how much AI you have, you'll never be an algorithmic trader, because being an algorithmic trader goes far beyond StrategyQuam, EasyLanguage, or being a programmer. It's about how to think, how to search, how to see the world, you
[31:31] know, how to see the charts. And people don't understand that. It's a job, I mean, it's a job that can be part-time, full-time, that's another issue. Well, but it's a profession. I mean, you know, anything is like
[31:45] , but just like an architect, well, imagine...  So, an architect only knew how to use the graphical program called AutoCAD to graphical program called AutoCAD to design buildings? Well, damn, you'd say, "I'll just
[31:57] hire someone else to design the house," right? No, no. I do architecture with AI. Well, yes, maybe I'll call you, right? maybe it'll fall through, right? Yes, yes, yes, yes. Absolutely.
[32:11] So, I mean, uh, it's sure to help him a lot in his work. It's sure to help him a lot. It helps us, but that's it. It's different for it to help you, I mean, for it to be your whole job,
[32:26] the builders themselves? Yes, sorry. No, I meant that it's seeing this, what you're seeing right now . And you could, uh, we saw a bit of the second code earlier, could you explain, uh, in plain English
[32:39] , as they say colloquially, what it's about?  Would this strategy be based on that? Yes, look, if it's explained, it's explained. Here you can read it by size, you can see the text. If not, I'll make it bigger for you.
[32:56] Uh, it's here because I specifically asked her to explain it to me like this for a novice, okay? And she documented it perfectly, really. Uh, I mean, you see, it's a code that's
[33:10] daily chart, although it can also be applied to other futures or we were saying before, you can also apply it, okay? The idea is simple. We choose a to 7. In this case, I've shown you, in this
[33:26] with seven and another with two. But anyway, now I'll explain the two, okay? Uh, this method decides if the market is bullish, bearish, or neutral. Based on that, it operates.
[33:40] If the  The signal is bullish; now we'll see what the signal is. The system is looking for will look for short positions or exit, depending on whether the system is operating on its own or only long or short positions.  Now we'll watch the short film, okay?  Oh, and the number of
[33:57] contracts, as I said before, is adjusted based on simple money management based on the nominal value of the futures contract. OK? What is each entry? Now we're going here.  I've said it
[34:09] before, three mode two is an exponential average, that's what it shows, okay?  An specific case, right?, the one I have loaded is seven, which are two moving averages, okay?
[34:23] And so simple.  And then, in addition, in the case of the two moving averages, there is a parameter that allows you to use, and that is a trick that I will leave for everyone quite interesting because many people always work with moving averages when they work with moving
[34:37] averages.   It's not bad, it's not bad, but I also recommend the very valuable advice from the video, okay?   Let's also explore the slope of the averages, okay?  In other words, it doesn't
[34:52] necessarily mean the price closed above, but rather that the average is rising or falling, right?  In other words, okay?  And when you use two, you can do the same thing.  You can use the crossover of
[35:04] the two averages or simply have both have a positive slope. rising. Yes, yes.  positive and when it is a In other words, today's average bar is higher
[35:18] than yesterday's average bar.  That's a positive slope.  That's it. So, it 's a small change, but it sometimes marks a different behavior of the system, and we also control that
[35:32] with an input, that's it, okay?  It's called cross option.  If it is zero, use the direction or slope of the line.  If it's one, use the price against above the line. OK?  So, basically,
[35:47] basically all this, as I say, are small parameters that you control when programming, which I insist, she did because the book did it that way and she did it that way, it's in the
[35:59] but it's something we usually do, it's a good practice.  OK. And specifically, to go directly to the signs, okay?  Look, notice, A even gave you examples and everything.
[36:13] Fantastic.  Fantastic.  To go to the specific signs. Ah, Morim simplified.  Everything is explained perfectly here. Truly wonderful. Here's the logic of the signal.  We're going
[36:29] three mode one.  Okay, it's the same.  We're only going to explain what we 've seen so we don't explain everything and make the video too long.  Train eh mode two exponential mod and this mode uses an exponential line.  The idea is the same
[36:44] with the simple average, okay?  But the exponential line gives more weight to recent prices.   In case you did n't know, this is exponential average and a mean, okay?  It simply gives it more
[36:57] importance.  You have an average of 100, a simple average of 100 is the sum of okay?  In other words, it doesn't give more importance to any of the 100.
[37:09] more importance, through a mathematical formula (which isn't worth spending time on right now), to prices closer to the present, away, it becomes less important to the price, so that the exponential measure
[37:25] price, so that the exponential measure recent changes, isn't it? Yeah, and that's it.  So, the code simply does that depending on whether it goes with the closure.  If it involves the
[37:41] closes above the average, well, buy.  And if it goes with the slope, well, if the slope is positive, buy.   That's it .  Hey, when does it close?  When it ceases to be so, when the slope ceases to be positive,
[37:55] or when it closes below the average. This is the basic setup to, as I say, test the idea. From there, we'll explore right? But it basically does this.  In the case
[38:09] of seven it is a crucem. It's a crossroads. A crossroads or slope of the two, what I was telling you before, but that's it, okay?  Use two pairs of socks, one faster and one slower.
[38:21] Crossed stockings, huh, typical.  When the fast one crosses the slow one, then I buy.  Or when the slope of both is positive, I buy.  When the slope of both is negative, or one of the two, that can be configured, okay?  One of
[38:36] is leaving.   That's it .  That's all. .  That's all. long, it's long.  They vote that they have in the case of the positive slope.  If both
[38:50] averages vote short, short; if they don't agree, neutral.   I minds the most, that something so simple, so basic, can .  And that's the difference, I don't know if you think the same, when someone
[39:05] wins using algorithmic methods, it's not because they use very complex ideas, but because they use simple, existing, and well-developed ideas, applied monetary management the way it needs to be done.  That's where the magic
[39:19] of algorithmic trading lies, not so much in whether the entry is from, I don't know, that many people today try to identify the professionals, I don't know what.  Those are simple ideas, very well exploited. Yes. And validated with a methodology,
[39:32] Yes. And validated with a methodology, Victor.  In other words, in the end, it's the key for me and the part that our training dedicates more and more time to, right?  Validation will be done through videos and then through mentoring,
[39:45] okay?  Mentoring sessions when students bring their cases, like the one I was telling you about from RB, right?  For example, Arturo, poor Arturo, I greet you, I 'm hunting for your name, because he brought it to the mentorship.  Well, I
[39:57] reviewed it, gave him my opinions, and that's it. In other words, in the end the idea comes out the same analogous.   That is , absolutely analogous.  In other words, it comes from a... in fact, I presented the idea here too.  Yes, yes, yes.   He
[40:12] here too.  Yes, yes, yes.   He system.  On top of that, he didn't even do it, and if you know what I mean, he uses it like a ninja. Well, that's fine, I mean, no problem at all.   It doesn't matter
[40:25] .  In other words, I put it in Easy Language for him, I gave him the pseudocode there he worked on it and has presented a system that I, well, uh, I have
[40:37] n't spoken to him for days, but he told me he was going to put it into practice.  I feel like he will have put it into practice in the next mentoring session. Uh, I'll probably tell him, I'll mention it. how that first month of operation has gone .
[40:52] Excellent.  That's great, isn't it? Excellent.  And finally, we were talking about all of this people in the introduction. A lot of people were thinking about how basic idea. We're planning to do a live stream where you can show a bit
[41:08] more how all of this is progressing, how to find more options or filters.  Can you Yes, because as the devil is in the lot and it's in this methodology, well, here we have
[41:21] obviously done a quick zoom, right? A YouTube video, otherwise right?  Yes. So, at the end, we can do a live stream where we explain in more detail and
[41:34] try to teach the strategy. We can even give it away because I had already designed it with this idea in mind, with the exit that I got to work best. I'll explain why I chose that exit, whether I
[41:48] apply a filter or not, and why.  Well, it's a bit like the methodology that Arturo has used to implement his real system, applied and explained in the video, and in exchange for subscribing to the newsletter, of course, when
[42:04] we do the live stream, I'll give you a really nice PDF with all this code and pseudocode so that if you don't want to use it in that language because can perfectly translate it with that pseudocode.  In other words, and if
[42:21] you have even a basic understanding, it will easily translate it into days. And this, Sergi, about the live stream, what day do you plan to do it? Well, if this works for you, we
[42:34] can do it on the 27th, okay?  May 27th, okay?  From this same May 27.  Yes, yes, yes.  May 7th. Okay.  Hey, Exacto, for whoever else that I've already scheduled the live stream with Sergi for May 27th,
[42:50] which we'll discuss now, so you can come and Sergi will explain everything related to this strategy at the level of code, pseudocode, filters, and how to improve it.  Well, beyond that, it's a
[43:02] making a very summarized video here, trying to condense all the information those live streams is that we spend a long time there chatting.  Imagine you have Sergi, a professional trader whose
[43:16] portfolio is replicated and manages $17 million, and that can an algorithmic trader's mind works and how it's done. Okay, traders, okay?  So, we'll leave it at that for the live stream on the 27th.  Hey, thanks for being here another day to
[43:29] people, I really hope a lot of people appreciate what it means to have someone wants to share these kinds of things because it makes a appreciate it from the bottom of my heart that you always stop by here and we're in touch.
[43:44] Well, it was a pleasure, Victor, and I'll see you all on the 27th.  See you soon.   See you soon all on the 27th.  See you soon.   See you soon .  Have a good one.