Do You Understand Your Trading Edge Odds? | Trading Psychology

Hello and welcome to lesson eight of the Advanced Psychology course for High Performance trading. This video is looking at the practical side of probabilities and probabilistic thinking in trading. It's the second part of the two part topic in this course and as far as I'm concerned, this is the most important video of the course. Regardless of all the other maladaptive issues that we have with trading psychology, we what you see here is the make or break factor. The previous video was theory based, but this one is a practical demonstration of how edges and probabilities are played out in reality and more importantly, how we perceive them playing out in reality. I want to help you understand how System 1 functions with probabilities, which truth be told, is not very well at all. I think this is the main reason traders fail. As I underlined in the last lesson, understanding probabilities in trading is not about improving your maths or creating complex algorithms to compute and execute objective probabilities that might help when developing your trading strategies. But day to day trading is about improving your intuitive sense of probabilities, which is initially maladaptive for trading. The first important thing you must understand is in trading you will never know for sure exactly what your edge is in terms of an exact percentage amount. In certain market conditions your edge may be very high, and in other conditions it's very low. The exact same system traded during one period may give amazing results, but over another period a only mediocre or even very poor results. Neither is a true representation of the system's edge. It's only when you've been trading the same system with consistency over many decades and through all market conditions can you begin to get close to knowing your true edge. But even then you'll never know for certain. But despite that, it doesn't stop us when we are trading to make continuous assessments of what our system might be in line to deliver for us. And it's this continuous assessment that if not monitored and understood, can cause us to either mistrust our system or put way too much trust in it. Because as we've learned over the last seven videos, we are born with a three stage assessment of probability. It will, it won't, or the much more stressful anxiety state of it might, which we try and avoid at all costs. And we try to avoid this by increasing certainty by adding more filters, tools or fiddling with and experimenting with our process on a trade by trade basis. So this video is all about becoming more comfortable with the maybe state by understanding probabilities correctly. But there's a major barrier to that which statisticians and mathematicians would call statistical inference. Let me demonstrate statistical inference for you in the simplest terms using the familiarity of a coin toss, which we know has exactly a 0.5 colloderzi of coming up either heads or tails. And this is real data. That unusual. I've really flipped these coins and these are my first time results. It goes without saying that when you flip a coin once and it comes up heads, as it did here, you don't then think that it is always going to be heads from now on. After another four flips, you can see that the probability is beginning to play out. And then after 10 flips you can see that we've ended up with seven heads and three tails. Now, after 10 flips you don't think, hold on a minute, I thought this coin was supposed to be 50 50. You don't suspect that we're using a weighted coin. You accept that small numbers of outcomes have huge errors or huge variations in the results. System one, however, does make an inference simply meaning that it infers or assumes something. Or at least it would if it wasn't already so familiar with coin flips like this. System 1's inference of probability in this case would be 0.7 in that there seemed to be a 70% chance of the coin going up heads if this wasn't a coin. But perhaps, I don't know, a pebble. That is exactly what system one would infer. But because you do know what the probability is with coins and you are already familiar with this, and this is the key here, in this situation, you accept that in order for that 5050 probability to play out, we need to frit that coin many, many more times, not just 10. Okay, so let's go ahead and do another 10. Okay, now again, this is all actual first time results. I did this manually and here we are with a surprise and string of tails. Now you might accept that in line with your understanding of randomness and probability with coins. But let's continue. And now we've ended up with two heads and eight tails. So system one's inference, when looking at this, run in isolation and is now 0.2. Of course this inference is overridden because you knew at the outset that this is 5050 and despite what the short term results might be telling you, the inference is wrong. And eventually if you kept going and added all of these scores up, it would of course get closer and closer to 50 50. Now let me show you that in action. This is a great online app. From California University to bring statistical inference to life for you. It's basically an online automatic coin flipper, and it speeds up the process of sitting at home for hours on end flipping a coin, which I can tell you from my experience is not much fun. In this section, we can set the probability, which, of course is 5050 for coins, or 0.5, and the number of tosses in a set, which we'll just go ahead and we'll change that to 10, and we'll leave the repetitions of sets on one for now. Okay, so let's go ahead and flip 10 coins.

So we've got eight heads and two tails. Now, down here on this graph, we have the influence drawn from that small run of flips. So it's put a.on 8. Now you know it's not 8 or 8. The coin is 50 50. So you accept that this small run of 10 flips doesn't accurately demonstrate the probability of of the coin. So let's do another 10 flips. And now we've got six heads and four tails. Again, the inference on that set is drawn as a six, which is also inaccurate because of the small amount of flips. But if we keep going, and I'll just keep flipping sets of tame, it looks pretty chaotic. Now we've got two heads and eight tails. So it's drawn a two down here. And I'll keep flipping. And now we've got seven heads and three tails. So it's drawn a seven down here. And now we've got three heads and seven tails. And already you've got a cluster here of six, seven, and eight, and then a two and a three. Nothing actually in the middle where it should be, where we expect it to be. We know it's 50 50, but we haven't even seen one instance of 5050 yet. But if we keep going, we've got a seven and a three. And now we've got a three and a seven. And this is my first take. I'm not fixing this. This is raw data, and it's not staged in any way. We've got two heads and eight tails, and we're not seeing a pattern or we're seeing a very strange pattern that doesn't match what we expect. These seven heads and three tails, and now we've got five. That's the first time we've seen 5050 actually happen. But if I keep going, what will happen inevitably is that we'll start to see a cluster around the center. So far we've done 140 flips now, 15 sets of 10 and still no pattern matching what we expect from these odds. But as we keep going, you'll start to see a bell curve appear. I can speed the process up by, say, the number of repetitions. That is, each time I flip, I do 10 sets of 10 instead of one set. So let's put 10 in there and then draw the samples to another go. That's 100 flips, another hundred flips, another hundred flips, another Hundred. And eventually what you'll start to see is this bell curve pattern appearing. And if I put a graph above it, it shows where the cluster is in the center. So after a huge number of flips, we can see that the probability of the coin is around the center. It's at the 0.5 mark. A small sample size doesn't tell us anything whatsoever about the real odds or probabilities. The actual edge is only visible after many instances, like the graph here. In this example, I've done over a thousand coin flips to see the true 5050 odds. You can imagine what system one infers from small classes of trades. It will make false inferences as the odds in the short term are so skewed and out of balance. If you win eight trades out of 10, system one will be making an inference that your system is producing great results and it's got a really good edge. And conversely, if it loses 8 trades out of 10, it makes false negative inferences about the edge in your system. It would be making a mistake in both cases. So what have we learned so far? Well, firstly, system one makes incredibly fast and effortless statistical inferences, particularly if it's missing critical information or has a small sample size of data. To give you an example, if you went into a restaurant just one time to find the waiter or waitress rude, you might infer that the probability of all the staff being rude is incredibly high and you probably won't go back to that restaurant. And if you only took a couple of trades one year and netted 80% return, you'd probably infer that you had some kind of trading magic and you'd go into next year with a lot of confidence. Now, when we know for certain that the odds are 5050 like in a coin flip, our system one easily accepts that outcomes are random. In the short term, it already knows what the probability is, so any short term inferences must be false. System one is not stupid and it does learn. But the issue comes when we don't know what the probability is. Liking trading when you don't know the exact odds, the inference it makes is very believable. If you knew without question the edge of your system over the past 20 years in all market conditions was 0.7, then you wouldn't care at all about the individual trade outcomes. You would simply keep going, exactly like flipping the coin. But you don't know that. And the smaller the sample size, the the higher the error in making inferences. And this is the key point. Not only are individual trade outcomes completely irrelevant, small sample size of trades and the influences that we effortlessly draw from, these have huge errors in them. And this has massive consequences for traders who just don't get it. Traders will look at a system's results over a very short period, and if that period is profitable or it's had a high win rate, they will infer that, hey, this is a great system. Whereas if the period that they're looking at is in a loss or it's had a low win rate, they'll infer that the system doesn't work. It's not unusual to see traders make adjustments to their systems based off the outcome of one week of trading, even one day, maybe even a single trade. Let me give you an example from my own trading. I've traded basically the Same system since 2004, and I've taken well over 6,000 live trades in that time. So I've got a reasonably large sample size of trades and market conditions to draw conclusions from, and I can be quite confident about the statistics and my edge. However, the win rates from one year to the next vary greatly, as does the net profit. I've had years where my win rate was as high as 62% and others as low as 35%. I've had a year where my return was only 20% and another year where I've made over 130%. If I zoom in on a smaller scale, I've had months where my win rate was only 10%. Other months where it was 90%. On a weekly level, I've had 100% win rates or 100% loss rate. It's the exact same system. But if an amateur trader looked at any period in isolation and they would infer completely falsely that they were different systems simply because they don't understand probabilities or random distribution. And the smaller the sample size of data, the less reliable that data is. As we've just seen, with something as simple as coin flips, probabilities and outcomes are irrelevant and meaningless in the short term. But think about what this means for traders. I'm profitable and I have been every year since 2004 because I keep flipping the coin again and again and I let my edge balance out. I ignore the short term variation, but most traders will see a series of, say, 10 trades and they will conclude it is or isn't working. They change something that would have made them the most money over those past 10 trades and then they have another go. But the next 10 trades give totally different results, so they change things again and then the next 10 trades are different again, so more changes are made. What they are essentially doing is starting from scratch every few trades with essentially a different system. And they are never consistent with anything long enough for the odds and their edge to balance out. This lack of understanding of probabilities and distribution dooms them to failure forever. So let me welcome you to my probability lab. This is an experiment that I set up to demonstrate what happens when we move away from the 5050 and into unknown probabilities, like trading. I've created a coin with an edge. Coin A is a regular 5050 coin and outcomes are completely random. But. But coin B has been bent slightly to give it a slight bias for landing on heads. Although I can't say exactly how likely. The exact edge is unknown, but there is certainly an edge. But in bending the coin and creating that edge, I've now created some expectation for a particular result. I now expect to see more heads if I flip that coin multiple times. Now, this expectation turns out to be very important and it makes our false statistical inferences even worse. Let me show you with a simple experiment. I flipped coinb with its edge in sets of 1010 times. So 100 flips overall. And again, these are actual first time results. There is no staging what happened happened the first time around. So on the first set of 10, the inference was 0.3, which is odd because I'm expecting more heads, but actually more tails have appeared. So if I was betting $100 each way, I'd now be down $400. I've won 300, lost 700 and another 10 flips and I've got 50 50, so still no edge, no advantage. So it already seems unfair. This is the equivalent of taking 20 trades. Surely the edge would be visible by now. But. But I'm still down $400 on the third set of 10. It's 0.3. So we flipped this 30 times so far and it would appear that tails is more likely. And at this point I genuinely wondered if I bent it the right way. I was honestly confused and I double checked. And to make Matters worse, I would be down $800 had I been betting on this. Now imagine if that was trading and, and you purchase this system from a seller, you're 30 trades in and you've lost 19. It's totally understandable. You'd be freaking out by now. Where is the edge that you were promised? But this is the difference between what system one expects and reality. Statistically speaking, 30 is just nowhere near enough events to see the edge. And that's the problem. The, the inference that we make out of these small numbers is false. And it would send us into all kinds of evaluative chaos. And the $800 loss, that would fuel that potential chaos. And remember the time factor. For an intraday trader, 30 trades may only represent one week. For a longer term trader, this could be six months, even a year. Be honest with yourself as to whether you would stick with this and would you keep going without any changes based on these results? Would you really trust that this has an edge if this was trading? But okay, we need to carry on flipping in the same consistent manner with another 10 at last. That's more like we expected. 0.7. I'd made back some of my losses and now I'm only down $400 in total. And another set brings us another 0.7, which nets me another $400. So I'm at break even and now a point eight, which puts me in profit for the first time ever with a $600 profit. Overall. That's 60 flips or 60 trades with a guaranteed edge and trading consistently, so to speak, before I even saw a profit. Again, try and imagine if this was you taking real trades. So those last three sets of 10 have met our expectations. So is the coin biased by 0.7 or 0.8 at this point? Recall in the last few sets of flips, we might even start feeling confident that actually the edge is now here to stay. And it's a big edge. But with another 10, we've made nothing. And then it's back to a losing set, losing US$200 with an overall profit down to only 400. And then another break even. So that now feels like we're part of a losing streak. And in the last term, we got a very slight edge of heads, leaving us up on this set in total by $600. Now, the reason I'm showing you this is to both demonstrate how edges play out, but also to show you what an emotional roller coaster system one's statistical inferences put us through, especially when we expect there to be an Edge. It's that expectation to want to see the edge playing out in the short term that causes the anxiety and the confusion when we trade. The only real way of knowing what the edge of this coin might be is to aggregate those scores. So let's do that. With 100 flips, that coin would seem to have an edge of 0.53, which is slight. It's actually lower than I expected. But is that it? Does this coin have a 0.53 edge? Well, to find that out, we need to keep going. And. And the good news is that I did this for you, and I flipped that coin another 900 times. Yes, it was painful. Thank you for asking. What I saw was that the edge settled down more and more, and I ended up feeling pretty confident that the edge of this coin is actually 0.65. And on that basis, I would be happy that if I could bet $100 each time and play it again, infinite number of times, I would be very profitable. And if you want to do this kind of experiment for yourself, which I highly recommend you do because it will help teach your system one, you can use this online app for that as well. Last time here we have the probability set to 50, 50 in single sets of 10. And when we do that, you can see that it represents the outcome with coins. But if we change the probability to, say, 0.65, which would be the coin that we just used with that edge, or a trading system with an edge, then we can simulate how we might react to that expectation of that edge. Okay, so let's now go and change that and simulate 10 flips or trades with that edge. You can see now that the visual representation is different. It uses a clock hand to create the randomness and color code those portions to represent the edge. So the 0.65 edge is represented in blue. And. And it's more likely to land in blue, which it calls successes, or we would call a wing as we would know it. So now we have expectation, and we know that there is an edge, and we want to see evidence of it. But the first set of 10 there didn't show it. And you can see the influence point on the graph below. It says 0.4. So more or less the exact opposite of what we expect. Oh, dear. If that was a trading system, a new trader would very likely give up Vera Men and probably voices frustration on a review site or a forum. But anyway, let's try another 10. Okay, so now we've got eight wings and two losses. So even with a definite edge of 0.65. Each of those two sets of 10 or 20 trades doesn't represent that edge. Which is why reacting to a set of outcomes is pointless, let alone reacting to an individual outcome. As I keep saying. But hopefully I am now demonstrating individual trade outcomes are meaningless. Even small sets of trade outcomes are meaningless. But let's go ahead and ramp it up and we will continue doing more of these trades. Again, just like the 5050 demonstration, you can see the inference points appearing on the graph. But slowly, after many transactions, you can start to see a pattern appearing and going to accelerate this even more again by putting this up to 10 and then flipping 100 at a time. So here we go, another 100, another 100. What's the inference? Can we start seeing what the probability is? Well, there we go. We can start seeing that shape appearing. And if I put the graph over the top, you can see the data is saying that the probability is actually playing out about a 0.65 level. And that's after 670 flips. That's a lot of trades before you begin to see your edge. And 65% is a big edge. Hopefully you can see what I'm trying to demonstrate here. Single outcomes, small sets of outcomes are meaningless. In order to see what the edge really is in reality and see it in your equity curve, there has to be a large set of information. But now let's go back to our two coins. With a regular coin flip, you know the chances are 50, 50. You accept that the outcome is random on a flip by flip basis. And you accept that expecting a particular outcome on any flip is totally ridiculous. Your intuitive sense of probability gets this because this is familiar with CoinB. We have created an edge. And remember, an edge creates expectation, which stops us from accepting. But the outcomes are still in fact random. There is now a system one expectation that we should be able to see it with our own eyes very quickly as traders. That means seeing this this week or in this month's equity turf. Now, yes, intellectually we all claim to accept losses and periods of drawdown, but there's always something miggling away in the back of our mind. Inexperienced traders expecting to see an edge are expecting it over a very small sample size. And when that doesn't happen in the short term, that's when doubt sets in. And it sets in pretty quickly. To summarize, so far, if the exact odds or the edge are unknown, like in a banked coin or any trading system, the but we know that there is an edge in our favor. We Create expectation that individual or small sets of outcomes will demonstrate those favorable odds. But they don't, which means despite having an edge, we are confused when the outcomes are negative. And this causes us pain, distrust and total chaos in the way that we evaluate our trades as we try to work out what's going on. Well, now, let me introduce you to a new coin we've already discussed. Coin A, which is 5050 and it comes with no expectation, and coin B, which has a slight edge and it triggers some unhelpful expectations of the next few outcomes, even though the outcomes are still random. So now meet coin C. As you can see, this is totally bent over giving it an overwhelming edge. We still don't know what the edge is precisely, but we know it's a big one. This is the type of edge or trading system you wish you had, or certainly the one that System one wishes you had in terms of trading. This is what most system sellers are trying to promote. But the funny thing with this kind of edge is it may give you a high wing rate, but overall these are usually losing systems. It's not so much a high edge, more a high wing rate to disguise the total lack of a real edge. You can achieve this sort of thing by having a very wide stop loss and small take profit target that will instantly give you a high wing rate. But there's a very good reason that people chase these kinds of systems. Because there's no pain associated with the false statistical inferences and System 1's expectations not being met. These systems give System 1 what it wants in the short term. Let me show you with the results of me flipping this manually in sets of 10. Well, the first set meets our expectations. There it is, the edge we expected straight out of the box. And I'm $400 up on that first set. Second set slightly lower, and another, but still an edge. We'd be up $800 by now. Great. Next we've got a bumper 0.9, and it continues 0.7, 0.9 break even at 0.5. And another three profitable sets. So over 100 flips, the coin seems to have an edge of 0.72, giving us a profit of $4,400. And most importantly, no inference pain along the way because our expectations have been met. Yeah, we accept some losses, but system one was very happy all of the way through that because the edge was played out in much smaller sets. This is the coin that represents the edge all traders wish they had, or in other words, what System one would really accept. Comfortably now, if we nip over to the app again and just put in coin C, I Change this to 0.72 and take 10 trades or flips and you can see again, the edge is visible on the first set. Here we've got 10 wins and no losses. Let's try again. And yes, it falls in line with expectations. Seven wins, three losses. And again, nine wins, one loss, eight wins, two losses. So far, no pain. System one accepts this entirely. There's seemingly not a big difference between 0.65 and 0.72 on paper, but every set of ten here feels painless. We feeling like we're on top of it. You can see what I'm trying to demonstrate here is that the lower the edge, the closer to 50, 50, the bigger the pain in inferring outcomes and therefore the bigger chaos when trying to analyze short term and individual or small sets of results. Okay, so where are we? Well, of course traders do, on the face of it, accept that a trading edge is probabilistic and that you must accept losses. But system one's expectation is that a trading edge should behave more like coin C, which is almost painless on a trade to trade basis, and certainly when we recall sets or groups of trades, because it sees the edge very quickly. But the reality is, what we experience, and should ideally be able to cope with is a lower, more realistic edge that plays out only over a much longer period. And that is what your trading system is. It's a small edge that requires consistency of execution over a very long term. Despite the uncomfortableness of the statistical inference that system one seems to make on a day to day or even a month to month basis, and the emotional rollercoaster that comes with that, that I've described earlier to drive the point home. If I gave you a guaranteed secret system to switch the odds very slightly in your favor on a gambling machine, would you expect a particular outcome on any particular pull? No, of course you would just keep playing, knowing that in the long run you would be up. You'd know not to expect anything specific on an individual go, but you'd be confident in the edge playing out over the long term. This is exactly how casinos work. They don't get hung up on the individual outcomes and they never panic when they lose to a player. They only care about spinning the wheel or rolling the dice or digging the cards over and over and over for as long as they can. That's how the house advantage plays out. If you trusted your trading edge like a casino trusts theirs, then trade outcomes individually would Become inconsequential. Assuming of course you have a system with a real edge in the first place, and you have the mental capacity to trade that system consistently. Hopefully this course is helping with that. So the reality is that indicators, tools, systems, rules, all inevitably cause expectation. They are often seen as outcome predictors or rather than probabilistic advisors. And if you fall into that trap thinking that any part of your trading system is an outcome predictor, then you will have some expectations as to what the outcome of a single trade might be. And as we've shown with the COIN experiments, expectation is only going to get you into trouble. Because if the expectation is not met, the trade does the opposite of what your system supposedly predicted it would do, then all you have is paying disappointment, frustration and beginnings of system distrust. And even if your expectation was met, the trades did do what your system supposedly predicted it would, then you have got something even worse, which is false correlation and bad learning. Meaning you start to think that if you did the same thing again, you would get the same result. It's false hope. You might even start to think that the outcome was down to your trading skill. Your system is not a trade outcome predictor. If you see it as a predictor of individual trade outcomes, you set it expectations about the outcome of the next trade and that will cause you nothing but pain, frustration and disappointment. Thinking of casinos again, we say the house never loses, but actually they do. In the short term they lose close to 50% of every game they play. They only have a very small edge, but they don't care because they've got no expectation or prediction for single spins of the wheel. They know it would be stupid in the extreme to try and predict the outcome of the next spin. They simply know they have an edge. And they know it will work if they give it enough time and a long enough opportunity. So they stay open 24 hours a day, 365 days a year so that their edge can balance out. And in the long term they will make millions. That's the approach that all successful traders need to have. Okay, so to summarize the last couple of slides, Trading with individual or short term expectations will lead to trouble. If you have any expectation on trade outcomes and they are met, then you get false correlation, confidence and worthless analysis. This is not feeding your intuition. Good information. And if your expectations are not met, then inevitably you get pain, frustration, growing distrust, paranoia and all kinds of other things. The long and short of all this is there are six things that you must accept if you want to continue to trade with real risk capital. Firstly, your trading edge may be completely indistinguishable from 5050 on a trade by trade basis. It will likely not be obvious at all. Secondly, you must accept that no part of your trading system, no tool or indicator, predicts direction or outcome of the next trade. And to see the search creates expectation, which as I said, will lead to trouble. Thirdly, the direction and outcome of individual trades are completely random in the same way that the outcome of even the weighted Coin B flips were random. Now, of course there will be positive expectancy over many trades, but nevertheless, individual outcomes are random and therefore influences made on individual and small sets of outcomes are false. You will make inferences because it's an automatic, effortless system, one process you can't switch off, but you need the awareness to recognize that the inference is false and there is no direct cause and effect between your system and the outcome of the individual trade. And lastly, you need to remember that your system one, and indeed the majority of the unprofitable trading community for that matter, will initially tell you that everything I've just said is wrong. Which is why so many traders never accept the true nature of randomness, low edges and and probability. Okay, now with all that said, there's one last thing that we need to talk about. As I mentioned earlier, there are systems out there that have very high edges or more accurately, very high win rates, but which ultimately are losing systems that wipe out your account in the long run. System one craves certainty. So welcome to Coin D. This coin might represent a couple of things. Either a system with a crazy high win rate because it uses average your name, no stop loss Martingale Betting strategies or grid strategies. So a system that wins nearly every single trade, but which, when the unlikely loss happens, it's so big as to wipe out the account. Or it could represent a black swan event, something so rare as to be assumed to be impossible. When we get used to success, we start to assume that something with a very high or low probability, depending on how you look at it, is is actually certainty. We get complacent or overconfident. In fact, when I made this coin, I was convinced myself that this was actually a 100% certainty coin. But I tested it nevertheless to see how long it would take to land on tails, if at all. And importantly, to see how I would react to so many flips with this kind of coin. And this is what happened. So we joined this video at flip622. Now, after 500 flips, I remember Losing all expectation that it would ever land on tails. Every single toss landed on heads. But I decided I would keep going to a thousand and then I was going to give up. I would make a slightly less bias coin. But Anyway, incredibly, after 632 flips, it did land on tails. If I were actually betting on this coin after a few hundred tosses, I would have been completely confident to put more and more money on it. After 500 flips, I would have bet almost anything. I was so certain that tails would never happen. The intuitive inference made by System 1 on these kinds of odds is one of complete certainty, which breeds recklessness. Or it leads us to think that we don't have to plan for the improbable. It's like playing a giant game of Russian roulette with a thousand barrels A and this is exactly what causes catastrophic failure and losses not just for amateurs, but also for supposedly the smartest people on the planet. I've told you in plenty of videos before about Long Term Capital Management. They had two Nobel Prize winning economists and the former Vice Chair of the Federal Reserve on their team and they created an algorithm that in their testing had a 99% win rate, which they inferred was the same as 100%. And 55 major banks and hedge funds agreed with them and they ended up with over $100 billion invested. And they were so certain, they leveraged themselves up to the point where they actually were managing over a trillion dollars worth of investment in the market. They were certain with a 99% win rate they couldn't lose, that nothing could go wrong. But guess what? That unlikely event that they thought couldn't happen happened. They lost literally everything and merely took out the entire global economy with them. They are the perfect demonstration to prove everything that I've said in this video. To start with, when they were designing their system and coding the algorithm, they only backtested four years worth of historical data, which is way too small of a sample size. It's incredible to me that they thought that was a good idea. And even with that and the hypothetical result of 99% accuracy, they misinterpreted 99% for 100% for certainty. They didn't understand probabilities despite having Nobel Prizes in economics. They had statisticians and mathematicians on board. Didn't matter in it all blew up in their faces. Even the famous George Soros, one of the greatest traders ever invested with them. He lost $2 billion in that fiasco. So don't be too disheartened when you make similar probabilistic mistakes. We're all vulnerable to this because of how system one has evolved and how it works. Interestingly, Myron Scholes, the Nobel winning economist responsible for that catastrophe, went on to set up a second hedge fund after he built up Long Term Capital Management and, and then he lost another 600 million in the 2008 crash. So he still hasn't learned his lesson. We humans are a stubborn bunch. As a retail trader, you don't have the luxury of playing fast and loose with other rich people's money with no consequence if you lose it all for you. You have to learn this stuff if you want to succeed with your own account, because it is your money win rate. And high probabilities can give you the illusion of certainty. It can make you complacent, it can make you ignore risks and the downsides. Always remember, if something can happen, it will happen. So anyway, there we have it. Here are all the coins lined up. We have coin a, which is 50 50. It doesn't create any outcome expectation. So with coin A, System 1's assessment of comparability accepts the randomness. And then we have coin B, which is most likely to represent a typical trading edge within a good system, which because we know it has an edge, does create some kind of outcome expectation. And of course, when we have outcome expectation, we get all the false statistical inferences and we find ourselves on an emotional roller coaster. And actually at an individual outcome level or small clusters of outcome level, these two coins feel very similar. The edge is just not visible. Not to system one anyway. Now coin C, this is what system one really wants. But it's unrealistic. Our intuitive sense of probability behavior is perfectly comfortable with this coin because we can see the edge in real time. We accept some losses, but the wins are clearly more evident. So we don't freak out. But as I said, in most cases this is a fantasy edge. It's not realistic in the market. This is what the trading to mean to refer to as the Holy Grail. And of course then coin D, which creates false certainty and it causes us not to plan for the worst by maybe not protecting our tent or piling on more and more risk. When we step back and we look at this, we can see why traders have such difficulties. We mistake probabilistic systems for being predictive systems. We think that having the odds in our favor somehow predicts the individual outcome. And when that doesn't happen, we think something's wrong. We mistake coin B for coin A because in the short Term, they are indistinguishable and therefore we attempt to create Coin C, but we overshoot and we end up creating Coin D because of our deep desire for for certainty. COIND in terms of trading systems are systems that use averaging down Martindale grid strategies, wide or no stop loss and quick profit targets. They have exceptionally high win rates, but they mistake high probability for certainty. And in fact these systems are always negative expectancy systems in the long term. They always lose in the long term and when they do, the loss is catastrophic and the account is blown up and the trader loses everything. The frustrating thing is CoinB or trading systems with that kind of edge are super easy to find and it will make you rich. But it doesn't look that much different from coin A and as such most traders tend to throw them away as junk. You've probably already had several systems like CoinB, but you've given up on them now. Just to be clear, the point of all this is not so that you can work out what your edge is exactly. That is unknowable and of course it will fluctuate with market conditions. But if you have a reputable system with a positive expectancy over time, that age will play out as long as you stick to it and you keep playing the game. And as your trading intuition grows, that age would actually be extended. What I've tried to do is demonstrate why reacting to statistical inferences in the short term will lead to over or underconfidence in your system. You can't turn these inferences off, but you can learn to not react to them. You can learn to see them as a maladaptive advice from system one. So like always, it's all about self awareness. Look for and become aware of where system one might be struggling with probability. To what extent are you or are you not accepting that trade outcomes and small sets of trade outcomes are irrelevant? Start noticing whether your emotion is driven by whether the trade won or lost, whether you made money or lost money. In other words, are you focused on short term outcomes? What you want is oversight to be able to discount false inferences and begin to place your focus on the process you are following. Trading is all about measuring your process, not outcomes. You can't control the outcomes, but you can control what you do. So as usual, here's a quick summary site if you want to pause the video and take some notes. But where are we going with all this? Based on everything we've talked about today and in the last lesson, the obvious question arises about how you can assess a trading system's edge. How do you know if you've got a Toyn B and you should stick with it or if it's just Coin A and it should actually be abandoned? Well, that's what I'm going to try and cover in the next video. The next video is about trading systems. The next three videos actually they're all tied in closely to this topic of probabilities in context, how we can apply it practically to our trading. I'll look at assessing profitable strategies with genuine edges and positive expectancy and the processes of executing those systems effectively and improving your performance. The final phase of this course really looks at your trading performance process evaluation and developing feedback loops that will lead to incremental improvements in everything that you do in the market. Make sure you click through to watch that next video as soon as you can and if you've got questions please use the comment section and I will try to reply directly, but I will definitely use your questions to create follow up videos after this course to help you make sense of all the new information that you've got so far. So thank you and I'll see you in the next lesson.