Binance Invited Me To Reveal Algorithmic Trading System

Sam. Hi, everyone. I'm Koster Uzas from Minotaur Trading Systems. I'm the CEO. And today we're going to be talking about algorithmic trading and how systems react to market liquidity. So I want to start off with a couple of multiple choice questions. So who do you think is going to win in this race? This one here or this one here? Ryan thinks the motorbike's going to win. Yes. Hands up. Motorbike. Yeah. All right, let's go. Next one, Eddie hall of the strongest men on the planet Earth. Who do you think is going to win in a strength contest? Him or this one here? The forklift. Forklift. Forklift. Cool. We've got one more. Who do you think's going to win here? This young kid or this robot here? Robot. Cool. In the age of AI, humans cannot outperform machines. That should be pretty clear by now. And this is exactly what's going on in actually all the financial markets. As we can see here, equities and stocks in the last 10 years have gone from 80% to 90%. Algorithmic trading. U.S. treasury bonds from 70 to 80. Commodities from 50 all the way up to 90. Forex is now at more than 95%. And I don't know if you knew, but the digital currency markets are now trading at more than 99%. That means that 99% of all the trading going on in digital currency markets is being done by algorithms. Now, what has caused this change? Well, these are the kind of players behind the shift that have come from the traditional finance markets. We've got Jim Simons. He's the godfather of quantitative trading. His Medallion fund, it achieved 66% annually during its run. He was the most successful investor of all time. He only used algorithms to trade with. So basically he was trading with math and code. Obviously, everyone knows Larry Fink obviously created the Bitcoin ETF that was released this year. He also built Aladdin. Aladdin actually is a code and algorithm that manages around $21.6 trillion in assets. And it's got about 11% of the world's financial assets. The last one here is the largest market maker in the world, Kenneth Griffith. He's the founder of Citadel. I'm sure a lot of you have heard of Citadel before. They operate in over 50 countries. Now, we're here because we're into crypto. And there are also some major players that are doing similar things with a similar playbook in the digital currency markets. Binance, right on this stage, the biggest player, the largest exchange globally, 40% of global spot trading is controlled by Binance. Yeah, Jane street is a little bit more infamous. Sam Bankman Friedman, sbf, he actually worked for them for around three years. They dominate both traditional and crypto markets. They provide massive liquidity and they help to minimize the spreads shaping price efficiency and market stability. This one's a little bit more or less known. Wintermute, they actually one of the largest market makers. They deploy state of the art algorithms across exchanges and decentralized exchanges. A couple of words I want you to notice here. They aggressively capture liquidity and drive rapid price movements. Anyone seen any rapid price movements the last few weeks? October, November, we're going to get into that and what we think causes it. So who do you think is going to win this fight? This guy here or this machine here? Who do you think is going to win? Yeah, I think we all agree that it's going to be the one on the right there. Algorithms themselves are actually fueled by the speculation of retail investors. All the average people, all the, all the people walking around here, everyone buying and holding, these are who the algorithms are fighting against. Right. And let's see how that actually what it actually looks like. But one thing to understand before we actually get into the liquidity is how liquidity actually drives price discovery. So why were we at 125,000 in bitcoin a couple of weeks ago and now we're down at 82? It's because speculation is actually the engine of price discovery. A lot of people think it's the supply and demand, but it's not. It's actually the directional bias that leveraged traders use when they're entering long and short positions. Right. And market makers, it's their job to balance the books, right? They need to fill the orders on both sides. Speculators, when the market's moving in a certain trend, are going to add leverage to their positions. They're trend followers. As the leverage builds up, what happens is we have gigantic liquidity pools form. What I've done here is I brought all the open interest on a Binance futures chart. That's November of last year, this is the beginning of November. Now this chart looks the same on a daily, on a four hour, on a 15 minute, even on a one minute because markets are fractal. But let's see what's going on here. The last time we had a price discovery when the market shot up was in November at the end of last year. Why? What was this huge amount of liquidity here that formed up and it was wiped out they were short sellers that were highly leveraged that built up over time. What do you see here? Short sellers, highly leveraged. The red is extremely high leverage pockets on the bottom. We have long sellers using leveraged also. When a market goes into price discovery, it then consolidates for a certain amount of time because no liquidity exists on the top or below the price. So liquidity is going to start to form. At some point there will be a trigger and the market makers will take advantage of that. What they'll do is they'll remove the orders from the book and the market will chase that liquidity. Why? Because algorithms buy low, sell high, and then they sell high and buy low. And they're getting all the liquidity from all the investors that are leveraging and speculating and getting it wrong. Because markets are fractal. To give you an idea, the charts look the same on the daily, the four hour, the one hour, the 30 minute, the 15 minute and the one minute. They're all like babushka dolls inside each other. So this is what the four hour looks like. And we're getting a bit of a zoom in. And again, this is where your eyes looking. That October liquidation event. So what happened on the four hour? Well, highly leveraged short sellers taken out, market goes into consolidation. Long sellers move in with leverage. They get confident, the market's going up. Super cycle. I'm going to add a 5x10x100x leverage position and then there's a catalyst. Obviously these market makers, these guys here, their short sell is open interest. They cannot close their positions. But the market makers, they want inventory to sell, right? They don't just want to move the price up, they want to move it down. They want to buy cheap and they want to sell high. That's what a liquidation level looks like. I'm going to zoom in on that even further. $19 billion. Does this look strange to anyone? The price is up here. We've got 100x leveraged positions here, and somehow the market went all the way down to there and all the way back up to here. That's an algorithm that does that. The algorithm manipulates the order books. It offers liquidity, and then when it's most needed, it takes it away. And what happens is we have a catastrophe. The leverage traders and the speculators are the ones that get destroyed, and the algorithms are the ones that are making money. This is a story as old as time. We like to call them fried chicken. Our chief strategist is from Texas, so he calls highly leveraged Speculators on the wrong end of an algorithm. Fried chicken. And that's exactly because this is easy money. Very, very easy money for a machine to make. So the question is then, how can manual traders keep up? Well, to be honest, they mostly can't. 81% of retail investors have actually lost money in crypto trading overall, most of them victims of leverage and aggressive position sizing or chasing speculative token hype. Collectively, these losses expose how volatility, poor timing, all these things are emotional, these are human error, right? We're not. Machines are programmed to be unemotional liquidity hunting by large algorithmic players. Another word I highlighted there, hunting. Algorithms are hunting these positions. That's why these, these, these market makers are making billions of dollars. They're actually aggressive, seeking the liquidity, especially at these low prices. These consistently devastate retail participants over and over again in every single market. And let me remind you again, 99% of the digital currency market is driven by algorithmic trading. So how can a manual trader actually keep up? Well, you need to get an algorithm of your own, right? It's the only solution. You don't want to take a knife to a gunfight, you want to take an algorithm to an algorithm fight. So I'm going to show you what algorithmic trading looks like. This is that 15 minute chart. Now the 15 minute is shows us a really good understanding of like what it looks like on a daily kind of movement. So the market is actually chasing these liquidity pockets at all time frames at all times. If I put this on a one second, you're going to see liquidity pools forming above and below the price. And the market makers, they're sweeping that liquidity, remember, at all timeframes, this is what's going on. And you can see it, you can see where it stops and when it comes back down and then it goes up again. You can see here it took out this pool and then wham, back down to collect this pool. And now it's taking this inventory and it's selling it there and then it's buying this inventory and it's going to sell it later on here, taking here, selling there. This is the movement that drives the market. An algorithmic trading system looks something like this. We remove all the emotions and all the human biases and we allow ourselves to engineer and use architecture to create a strategy that can duplicate the movement of the market makers. Right. As you can see here, we've got entries and exits, entries and exits, entries and exits. And I've layered in behind it's. A bit difficult to see with the lighting, the actual heat maps. So an algorithmic system, if you're using one, is able to trade the markets like the smart mechanical money, like these market makers, as you can see there. So what are proven strategies for algorithmic trading? So again, anything that works should follow first principles. And the first principles of algorithmic trading, firstly at dca, you've probably all heard of DCA dollar cost averaging. Well, it works particularly well when you're reducing initial position size exposure by creating safety orders at lower average prices. It's a way to use extensive coverage to basically allow yourself to cover a big deviation in price like what we're seeing right now. And it's very old fashioned and simple to use. You may have heard of the WYC off cycle. This is basically where we have accumulation, markup, distribution and markdown. The wyck off cycle also occurs at all time frames. So some people might be looking at the daily chart and seeing these kind of move, but it happens fractally. So it's happening every second and every minute. This is how the market is moving. So like I said, the wick off cycle can happen in a one minute time frame with 1440 candles. So this is happening constantly, all the time. The last one is mean reversion. So Jim Simons as a medallion fund took advantage of mean reversion and he generated those 66% returns that we talked about earlier. For Bitcoin we actually have the power law which was discovered by a physicist called Giovanni Santostasi. If you've got time, you should look him up. Mean reversion is a strategy that can be used particularly in bitcoin. I don't think as much in altcoins. That's why I tend to focus on studying Bitcoin only if someone was able to integrate Wyckoff market structure, mean reversion dynamics and DCA safety orders, then they would have the foundation of building an algorithmic model that would replicate institutional trading logic. And this is what that looks like. An algorithm that works makes money no matter what the market is doing. So a lot of people that I've been speaking to are in the red. They're waiting for the market to go up. But how much better if you made money when the market went down and when the market went up. That's what the smart money does, right? They don't have a directional bias. They make money no matter what. So as you can see here, using a long only strategy, trading bitcoin futures, an algorithm is able to make money by the price actually dropping due to a combination of its architecture and following the foundational principles that we spoke about before. So this entry here, which was at 126, it bought the top. It was actually able to sell at 112, take profit, reset and start trading again. Enter here, sell there, enter here, sell there again. We see another example of it moving against it and it's able to take profit or lower. That's because algorithms don't try to predict price. Most traders, especially most human traders, they think they know everything about the market. They think they know about the direction. They go on YouTube and they find someone who they think knows everything, and they basically try and copy their trades. Now, you can copy someone's trades, but you can't copy their risk management. And that's something they're never going to show you. Right. A lot of retail people believe the influencers know everything about the markets. Usually what they're doing is they're only showing 10% of their hand, but you think you're seeing the whole picture. So an algorithmic system like this, it ignores all the noise, it ignores all the influence, and it just works off the structure and architecture that the smart money is using. So where does that leave us humans? Well, still a few things. So macro and geopolitical analysis, firstly. So humans still matter because human judgment can interpret complex, ambiguous geopolitical shifts, like what's going on today in politics. This is a really important thing to understand. Computers aren't really going to understand that the way we do. Humans also still matter because regulations and politics are constantly evolving as well. Another important thing is compliance. Humans still matter because these rules are constantly changing. But the most important thing is system design and oversight. A lot of people think they can just get on ChatGPT and write an algorithm because they asked ChatGPT to write them an algorithm. Write me a good algorithm. ChatGPT. It's not how it works. You need to have huge amounts of experience. You have to understand fundamentally markets, finance, psychology, all these things. And you've got to then be able to program and build a system for yourself, because really, that's what you need to do if you want to win. The best system designers today, they're not going to be just traders, they're actually going to be innovators, philosophers, and also global macro thinkers. People that can bring in knowledge from everything they've done lots of disciplines and come with their own personal strategies in order to compete with these gigantic market makers that have been running their systems for a very, very long time. How do you win? If you're a regular person and you want to win in this game, I suggest you use an algorithm to harvest volatility and liquidity. If you want to get institutional great performance, what that means is you're going to make money when the market goes up and down, just like the institutions do. Secondly, you need to use algorithmic precision. Why? Because the market's going to move while you're asleep, while you're picking up your kids from school, while you're doing your music lessons, while you're watching tv, while you're having a bath. If you don't have algorithmic precision to adapt dynamically to evolving market conditions, you're going to miss. You're a human. You're not going to watch the market 24 7. Lastly, if you want to win, you have to let algorithmic architecture and engineering gride your strategy. If your strategy is based on influencers and Instagram and you're flip flopping this way and that, I'm telling you now, you will lose everything. I'm talking about Hodlers if you hodl, that's okay. I'm talking about traders, right? Or anyone thinking getting into trading trade smarter, not harder. So we've actually got a booth down there. We're a quant team that develops algorithmic trading systems. We also offer education and trading solutions. But the one thing that we offer that's most importantly is a is a completely built, fully deployed algorithm built on everything that we've already discussed. It also really focuses on capital preservation by only trading Bitcoin. We only focus on Bitcoin because for us it is the most liquid market and one that we believe can be traded probably forever. A fully automated trading setup. The good thing about algorithms is that once you've got the keys, it's plug and play. The work's already be done for you. So it can take less than a few days to actually deploy an algorithm. I wanted to add this. I put this in last night because everyone's probably thinking, what's going to happen next? This is where we are right now after this talk. It's been like 25 minutes. Where do you think we're going? Well, if everything I've spoken about today is correct and logical and reasonable, the market makers that just bought this gigantic liquidity pool that's been sitting there since July, where are they going to move their inventory next? Do you think they care about their halving? Do you think they care about the cycle? Do you think they care about 10, 50 days since the bottom of last cycle. No, they care about making money and they just took the maximum amount of money that they could off the table. Where did the wick stop? Right at the bottom of the liquidity pool. Perfect ending to that story. See below here. There's no liquidity, there's no bridge, there's nothing for them to buy there. All that's left is the sellers that have been stuck since November last year. Highly leveraged speculators that are praying for the market to drop further. So what happens and what does Bitcoin always do? Well, it does the thing you least expect, unless you're an algorithm, and it does exactly what it's built to do. It's about to eat some fried chicken, in my opinion. So, again, I've only got three minutes left if you want to come talk to us. We actually do 45 minute demos for free, no strings attached. You can get my team to talk you through exactly how our system works, how we create our risk management profile, how the algorithm trades in live. We've also got Alexei here, who's going to have his little swipe thing. We're going to be sending emails and also calling people and seeing if they want to do a demo as well. So, yeah, there's about three minutes left. Any questions anyone might want to ask? I don't know if I can hear you. Go to the mic there. If AI keeps improving over time, models keep improving, becomes more efficient.

What'S required? I mean, doesn't that make an efficient market and all of a sudden there's no market that exists in the future? Or is it something that privacy and dark pools will be required so that this doesn't become this inefficient where there's no, you know. Yeah, the AI, it's a war of algorithms against algorithms. Right. And everyone's going to get more efficient and everyone's going to get better. Everyone's going to use the tools better, use the tools smarter. But again, the people that are building the machines, the smartest people are the ones that are going to build the best algorithms and they're going to take out the ones with the worst algorithms. We're always going to have retail investors that come into the market. I don't think, I don't think everyone's going to have some magic algorithm and everyone is going to make money. What's going to happen is very few people are going to make money and the rest are going to lose most of their money. That's what's always happened and that's what's going to continue happening, I think. Thank you. Fees are quite a big thing with automated trading, so I guess that's something to. I mean, the trading fees, platforms. You mean the trading fees? Yeah. Like certain exchanges are better to use than others. Yeah, of course. I believe actually Binance is one of the better ones. Bybit any of the futures exchanges have a 0.05 take and make a fee. Another thing is the strategy itself, or the one that we use particularly, it's not high frequency. It's actually kind of one trade a day, maybe two trades a day, maybe a trade every three days. So we don't really get chewed up by fees. It is important to be cognizant of the fees. But if the strategy doesn't allow itself to be a victim of trading fees, then in our case as well, take profit levels are quite high. They're around 2, 3%. So again, if you're hunting tiny inefficiencies that are what a lot of people do, but we've almost. We've built a trading system that actually works with retail. So we built it in a way that we don't have to fall victim to those kind of things. That's all. If you want to leave your details, all you got to do is swipe your card over here and we'll send you some more information. Otherwise, come talk to us at booth 100 outside the keynote speaker.

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