Transcripts
1. Introduction: So let's say you were looking at two different companies, maybe Apple and Google. And what specifically you're looking at the stocks of these two companies. And you notice that, well, because these are both tech companies and there's obviously a lot in common between them that their stocks actually move up and down together most of the time in the market. But then you notice that these two stocks started to diverged from one another. Maybe Apple is going a lot higher and Google is going a lot lower. And so my question to you is, how would you trade that? And if your answer to that question is I have no idea or can you even trade something like that? The answer is yes, you definitely can. And you should watch this course because that's what pairs trading actually allows you to do. You are essentially literally trading the relationship between two different companies as opposed to just the individual stocks by themselves. And so then you might be asking, well, why would you even do this? And the answer to that question is one, pairs trading actually greatly reduces risking our portfolio and extends trade duration. So you can stay in those trades longer if need be, to wait for those profits to come to you. And then secondly, it pairs trading offers, yet another great engagement tool to help you stay active in the market. And so in this course, I'm going to show you what pairs trading is obviously and exactly how it works. And then I'm going to show you an actual trading simulator that I have created, which is going to use real historical market data and demonstrate that this kind of strategy actually works if done correctly. And then lastly, I will show you the different ways in which you can actually conduct pairs traits, whether you are trading stock or options or futures, really doesn't matter because you can do pair trades with really any financial product. And this is the first course of mine you come across. My name is Scott Reese. I currently work as a software engineer in the financial services industry, and I'm also an options trader. And my strategy is all about selling options when implied volatility or the general fear in the market is elevated. And everything that I do, all the traits that I make are based entirely often probability, there's no subjectivity or emotion involved whatsoever. I literally just play the odds in the stock market. And so in this course, you're obviously going to see how I would do that in regards to pairs trades. But if my style of options trading sounds interesting to you and you can definitely check out my other options trading courses where you're going to learn the main concepts in mechanics that I personally use to turn a profit in the market. So with that being said, let's hop over to the computer and get started.
2. What is Pairs Trading?: All right, welcome to the first video in this course. And in this first video here, we're going to be talking about the concept of pairs trading, how it works and how we can take advantage of it to actually turn a profit in stock markets. So before I can show you some cool stuff, my trading platform here, going to come over to this page and like I said, talk about what this strategy actually is. So pairs trading is actually a very simple concept. Understand, it's simply trading the relationship between two assets, right? And so just trading Apple stock by itself, we're going to be trading shares of stock of two different companies in a certain way that's going to take advantage of their relationship. And this relationship is based on the correlation between the two assets. So let me break this down here. So let's say we're looking at Apple and Google stock, right? And if we take the past ten years of historical data and write up daily price movements for both of those companies. There's actually a way where we can calculate the correlation between those two assets. That correlation is a number that you're going to get from that calculation. That's either going to be between negative one and positive one. And for the purpose of this course, we want to get correlations that are very close to positive one, which would mean that Apple and Google move up and down together in very similar amounts. So on any given trading day, if Apple stock moves up by 2%, then Google stock is most likely also going to move up by around 2%. And then conversely, if Apple stock moves down by maybe 3%, then Google stock is also most likely going to move down by about 3%. And the closer the correlation between Apple and Google is to positive one, the more in-sync they're gonna move together either up and down on any given trading day. And I'll be showing you exactly how to do all this in the next video. Now just as a side note, if you were to calculate the correlation and you got a negative number, something close to negative one. That means the two stocks would have an inverse relationship, meaning apple stock moves higher than Google stock will move lower, and as Google moves higher, Apple moves lower. Now there is a way to do pairs trading with two stocks that have inverse relationships, but it gets a lot more complicated. So just for the scope of this course, we're gonna be focusing on stocks that have a positive relationship. A positive correlation, meaning they move up and down together in very similar amounts. So to help make this a little bit more concrete, I have a couple of examples here that I'm going to walk you through, the very simple. So let's say we have a stock called ABC, that's just some made-up ticker that I came up with. And it's currently trading for a 100 bucks. And then we have another stock, XYZ that is trading for $20. And let's say we ran the numbers on their historical daily returns and we got a correlation of maybe 0.85 or 0.9, something very close to positive one, right? And so now what we can do is take the ratio between those two prices. And the way we do that is we take 100 and divide it by 20, and that would give me the ratio of five, right? Abc stock is trading for five times the price of XYZ. And so the reason why we do this is because for assets or stocks that are very positively correlated, this ratio is going to stay very consistent across time. So for example, if on the next trading day, if ABC stock moves up by 2%, that'll bring the share price from a $100 to a $102. And then if XYZ moves up by the same amount, 2%, the share price is going to move from $20 to $20.40. And if we take the ratio of these two prices, again, 102 divided by 20.4, we again get five. And you'll get the same exact result if the stocks actually move down or price. So let's go to example two and see that exact scenario play out. So once again, ABC's stock is at a $100, XYZ is at 20, ratio is five. Now, ABC moves down by 5%. So the stock price is going to draw from a 100 down to 95. Xyz is also going to follow. It's going to drop also by 5%, which brings the price from 20 down to 19. And then once again, if we take the ratio between those 295 divided by 19, we once again get exactly five. Now of course, in the real world and the real market, you're not going to get price movements that are this exact, right? So even if you have two stocks that have a correlation of 0.99 super, super close to one. Chances are if ABC stock moves down by 5% than XYZ might move down by 4.98% or 5.3%, something very close to what ABC did, but on exactly, which means this ratio is going to be slightly different. But the point being it's going to stay very, very consistent, right? It's going to stay right around five. And so now getting into how we can actually trade this kind of relationship. The way we do so is when the relationship actually breaks down and our breaks down for a temporary amount of time. So let's go to the third example now. So same exact setup. Once again, ABC stock is at a 100, XYZ is at 20, ratio is five. Now however, ABC's stock moves up by 3%, which brings the price to 103. And XYZ actually moves down by 2%, which drops the price from 20 down to $19.60. We take that ratio and now we get 5.25. Now this new ratio isn't too far off from where it usually is, right? But you can imagine if this kind of behavior continued, right? Maybe the next day, the falling trading day, ABC's stock moves up again and XYZ falls down again. And maybe that trend continues for multiple days or maybe a couple of weeks. And eventually this ratio might go from 5.25 to seven or eight, something very far away from where it usually is. And if most of the time, right after doing our analysis and crunching numbers and we got a correlation that was very close to positive one. If most of the time these two stocks move up and down together, than when they do start to move away from each other in opposite directions, which certainly can happen. And there's a very high chance going forward that they're eventually going to come back into alignment. Meaning this ratio, if it goes from 5.25 to six to 6.5 to seven, at some point it's going to come back down, go from seven to 66 to 5.5, then back down to five, right? At some point it's going to respect its relationship again and bring the ratio back into alignment. And the reason why we can be very confident about that happening in the future is because the correlation between these two stocks that we pretended to calculate was very close to positive one, which is mathematical proof that most of the time these two stocks move together. So in the few small instances where they don't, they're eventually going to have to move back into alignment. Otherwise, the correlation would not be as high as it is. And also even though this example here shows the ratio getting larger and larger and larger, the opposite can certainly happen as well, right? If ABC's stock where to actually drop by a certain amount and XYZ were to increase by a certain amount. Then when you take the ratio of those two stock prices, you're actually gonna get a ratio that's much smaller than five. So the ratio can get extreme on both sides, either much greater than where it usually is or much smaller. And in either case, those are great opportunities to place trades to take advantage of the fact that most likely going forward, that ratio is going to come back into alignment so that the relationship between those two stocks is once again respected. And so in the next video coming up, I'm gonna be showing you a little analysis that I have prepared for you. I'm going to take historical data from a few different assets, and then I'm going to show you how we can calculate the correlations between those assets. And if we get correlations that are very close to positive one, then those would make great candidates for pairs trading. And I'm also gonna show you how we can actually quantify whether or not the ratio is getting to an extreme point, right? Extreme is obviously kind of subjective. But there's a way to actually mathematically calculate what extreme should mean in regards to Paris trading. So whenever you're ready, I'll see you in the next one. Thanks.
3. Data Analysis: Alright, welcome back. And so now in this video, as I said, I'm gonna be walking you through a bit of an analysis that I prepared for you here in the spreadsheet where I basically pulled ten years worth of daily price movements for a couple of different assets, basically ETFs. And I'm gonna be showing you how we can actually calculate the correlations between these assets and calculate the ratios and how we can actually quantify whether a ratio is quote unquote extreme or not. So like I said, what you're seeing here are ten years of daily price returns, four. And this case QQQ, which is an ETF that just tracks the nasdaq Index, mostly tech stocks. And then same exact thing here for IUWM, which is an ETF that tracks the Russell 2 thousand, which is an index that is comprised of small cap stocks. And in case you're wondering, I got all this data from Yahoo Finance, it's very easy to go into their website. Type in the ticker symbols of stocks or assets that you're looking for. And just to download a CSV file like this that has all the historical data within a certain timeframe. Although just take note that the daily price returns, these percentages here, these are not included in the actual Yahoo Finance data. You have to calculate these yourself. It's very easy to do so. So for example, the way I've done this here is looking at this, this row right here, negative 0.27%. This just comes from taking the corresponding day's closing price and subtracting from it the previous day's closing price. So $44 minus $44.12 gives you negative $0.12. And then we take negative $0.12 and we divide that by the previous day's closing price. And that's what gives you the result of negative 0.27%. And I just apply that logic all the way down this column to get all the daily price returns for this 10-year dataset. And so now coming over here, I have another colon here that has all the price ratios. So looking at this first row right here, 0.76, this number is just calculated by taking I double-click here, the boxes will highlight by just taking the closing price, QQQ and dividing it by the closing price of OWN, these two numbers right here. And that's, that's it. And I'll press enter here and you can see 0.76 is the ratio. And same thing as what the price returns. I've just apply that logic all the way down this column here. And so then from this data right here, from these price ratios, we can then calculate what the average ratio is for the ten years of data that we have. And you can see that the answer is 0.98. So just rounding up, let's call it one. So most of the time over the past ten years, the ratio between QQQ and IUWM in regards to their prices, is basically just one-to-one. They're typically about the same price. And so what this would mean is going forward into the future, if the ratio between QQQ and IUWM was around one, then you would know that their relationship is currently being respected and they're generally moving up and down together. Now, of course, there'll be times where that relationship actually breaks down temporarily and their prices might diverge, right? Qqq might start to really go higher and higher and higher. And I WM, my structure really sell off. And so now this is where we can use the price ratio of standard deviation to help us figure out how extreme a ratio between these two assets really is, right? If we have a ratio between QQQ and IUWM, that's maybe 1.15. Is that extreme? I've no idea is a ratio of 0.82. Is that extreme? I don't really know, but we can look at the standard deviation to help us figure that out. And so I'm not going to dive too in depth and to stand deviation and what all really means in great detail. And if you want to learn much more about standard deviation and statistical modeling and things like that. You can watch my course called options trading, understanding stock market behavior. But basically the way this works is we take this number, which is calculated by doing some sort of analysis on all of these price ratio numbers here. And Excel will do those calculations for us. And so what we do here is we take 0.24, we subtract it from the average, and then we also add it to the average. So let me go ahead and do that and bring out the calculator here. So if we take 0.98 and we subtract 0.24, we get 0.74. And remember that. And now if I take 0.98 and I add 0.24, we get 1.22. So 1.22.7 for those the two numbers that you wanna keep in mind here. And what these numbers mean is if going forward into the future, if on any given trading day, if we take the ratio between the price of QQQ and I wn, and we get a ratio that is 1.22 or greater. Or if we get a ratio that is 0.74 or less, those kinds of situations are only going to present themselves around 30% of the time. Or in other words, there's about a 30% chance of 30% probability that you're going to get a situation like that, right? A ratio of 1.22 or greater or 0.74 or less, and something that only happens about 30% of the time, I would view as pretty rare. Obviously not super rare, but definitely if you get a ratio somewhere in this vicinity, I would argue that that ratio is at a somewhat extreme point. And like I've mentioned before, once the ratio gets to an extreme point, we now can actually quantify. That makes for a great opportunity to deploy a pairs trade. In this case, we would be trading shares of QQQ and I WM in a certain way. And I'll talk more about that in the next video. But bottom line, I would say once you get a ratio that is at least one standard deviation away from the average, either above it or below it, I would start to view that ratio as an extreme point. Now if you are extra patient, you might want to wait until a two standard deviation move occurs, which we can calculate by just taking this number right here, 0.2 for multiplying it by two, that gives you the two standard deviation move away from the average. And then same thing. We subtract it from 0.98 and we add it to 0.98. So let me go ahead and do that. Take 0.98 and we subtract 0.48 now gives you 0.5. And then I take 0.98 again, and I now add 0.48 and we get 1.46. So now what this means, a two standard deviation move away from the average if going forward into the future, taking the ratio between QQQ and IUWM. If you get a ratio of 1.46 or greater or 0.5 or less. Those kinds of situations only present themselves about 5% of the time. So that would be a very rare situation. And when Definitely make for a great opportunity to use a pairs trade. And again, the reason why a one standard deviation move away from the average or as two standard deviation move. The reason why those are great opportunities is because going for beyond that, it's very likely that this ratio is eventually going to come back down and settle somewhere near the average again. And the reason why we can be confident of that is because of the correlation between QQQ and I WM. Alright, this number here, this correlation is calculated by taking or doing some calculations that I won't get into super in-depth here, but there is an Excel function you can use that will basically take the daily price returns of QQQ. And also I WAN. And it will figure out the correlation between those two assets. And in this case, the correlation is 0.82, which is pretty darn high. I would say a general rule of thumb here when you're considering pairs trading is you wanna have a correlation of at least 0.7 or above. Although ideally if you can get a correlation of 0.8 or above, that would be very ideal. And obviously, the higher you go, the closer you get to positive one, the better the situation is going to be. Although finding correlations of 0.95 or 0.99 are almost impossible to find, especially over a longer time period, like five or ten years. Like I was saying, because these two acids have a very high positive correlation to each other, that means most of the time they're going to move up and down together and in very similar amounts in terms of percentage changes. And when these two assets start to diverge and they start moving in opposite directions, right? If QQQ shoots up to the upside and IUWM sells off, that's going to really increase the ratio between their two stock prices. And then on the flip side, if QQQ sells off and IUWM has a huge rally, that's going to decrease the ratio between the two prices. In either case, once the ratio between those two assets exceeds a one standard deviation move above or below the average. That's when you can start looking at that ratio as a pretty extreme point. And so I believe that covers everything I wanted to talk about for the pair between QQQ and I, WM and I have one more Parrish. Oh, you're just gonna get through really quickly here because it's basically the same thing for pair two. I have GLD and SLB. Gld is an ETF that just tracks the gold market. And SOV is an ETF that tracks the silver market. So two very different assets from QQQ and IUWM. And once again, I had the same kind of data here, ten years worth of daily price movements have the daily returns calculated here for you on both these assets. And then once again, I have the price ratios column just calculating the ratio between GLD and SLP on each of their trading days over the past ten years. And then the same kind of statistics here again, the average price ratio is right around seven. The standard deviation is 1.5, and the correlation between these two is 0.79. So again, that's pretty high and as a result, the relationship between GLD and SLP would make four great pairs trading candidate, right? Most of the time these two assets move up and down together and similar amounts. But once the ratio exceeds seven, basically running up to seven here. Once the ratio exceeds seven plus 1.5, which is 8.5, or it drops down below seven minus 1.5, which is 5.5. In either case, that's a one standard deviation move away from the average, which only happens about 30% of the time. And in those situations, I would definitely be interested in potentially making a pairs trade. So now what you're going to be seeing in the next video coming up is I have written up a Go application that's going to take in all of this data here for both, for both of these pairs, GLD, an SLB, and also QQQ and IUWM. And it's going to walk itself through each of these daily returns here and calculating the ratios along the way. And once it finds a ratio that is beyond a one or two standard deviation, move away from the average is going to actually make a trade. And it's going to make this trade by buying and selling a certain quantity of shares of, you know, in this case GLD and SOV. And then using the historical data going for from that point, it's going to figure out how profitable that trade is going to be. And it's going to exit that trade at a certain profit point or at a certain loss point. And then in either case, once it exits that trade, it's going to do the same thing again. It's gonna keep walking itself through all this data here going forward in time until it finds another ratio that is beyond a one or two standard deviation move. And then it's going to make another trade. And it's going to keep doing that, so on and so forth until it gets through all ten years of this data here. And then you're gonna see the final profit or loss at the end of this 10-year period to see how profitable is kinda strategy actually is. So I think it's going to be a very cool thing for you to c. So whenever you're ready, I'll see you in the next video. Thanks.
4. The Trade Simulator: Alright, thanks for joining me here again. And so now I'm going to be showing you here the trade simulator that I have written up. This is basically a little Go application here that's going to, as I said last video, walk itself through the historical data of QQQ and I WM and then also a GLD and SLP. And it's going to actually simulate trades based on the price ratios that it's calculating along the way. And once it finds a ratio that is quote unquote extreme. And again, we measure that extremity by using standard deviations and things like that. Once it finds an extreme ratio, it's going to actually simulate the trade and then exit that trade at a certain profit point or at a certain loss point, and then repeat the process for the full ten years of data. Now, before I can show you exactly how this is going to work, there are two simple concepts that I need to go over. First, the first of which is called short selling. And this is basically going to be the exact opposite of just buying stock and holding it and hoping the stock prices go up with time, right? Short-selling is how you make money when stock prices go down. And so the, the general process for how this works is you first literally borrow shares from your broker. You borrow shares of stock. You then immediately sell those shares in the market at the current market price. And then as time goes for maybe a couple of days or a week or two goes by. If you are correct and the share price actually goes down, then you'll be able to buy those shares back at the lower price. And again, this is if possible, of course, you could be wrong and the share prices could just keep going higher and higher. But ideally you buy the stock back at a lower price than where you sold it. And then you just return the shares to your broker. And the difference between the price at which you sold those shares and the price at which you bought them back, that difference is going to be your profit on the trade. So I have a few examples just to make this a little bit more concrete. Example one here, let's say we have a stock, the ticker symbol is just XYZ, just some made up ticker symbol. And let's say it's killing, trading for $100 per share. And since we want to short sell the stock, our assumption is that the share price is going to be dropping in the near future. So let's say we want to short sell ten shares in total. So we're going to borrow those ten shares from a broker and then immediately sell them at a 100 bucks per share. Say week goes by and we are correct and XYZ actually drops to 90 bucks per share. At that point, we're going to buy those ten shares back at the new market price of 90 and then give those shares back to your broker. And so then our profit on that trade is simply calculated by taking the price at which we initially sold those shares for. And we subtract from that the price at which we bought the shares back. And then we multiply that result by the number of shares that we're involved, right? So a 100 bucks is what we sold them form. Bottom Beck at 90, the difference here is ten. And we did this tray with ten total shares. So ten times ten is $100, that's our total profit on the trade. And then an example, two, same exact setup. Xyz is initially trading for a 100 bucks a share, and we are bearish on the stock. So we're going to borrow and immediately sell those ten shares again from our broker. Now in this case, we are wrong with our bearish assumption. And going forward in time, XYZ actually rallies and goes from a 100 to a 110 bucks per share. So this point, we might want to just get out of the trade, cut our losses, and move on. So we're just going to buy ten shares back at the new price of 110 shares back to the broker. And in this case we have a loss on our hands is calculated the same exact way as the prophet. Just take the price at which we initially sold those shares for. Subtract from it the price that we bought them back four. So 100 minus 110 is negative ten. And then we multiply that by the number of shares that were involved. So negative ten times ten is a loss of $100. And just to know all the borrowing of shares and the returning of shares, this is actually all handled for you behind the scenes. So if you were to do this in your trading platform, like maybe Think or Swim, for example. It's literally just as simple as clicking the sell button instead of the buy button. Meaning instead of clicking by to just buy shares of stock, there's just gonna be a cell been too just short sell shares of stock. And when you do that, that's automatically going to take care of borrowing the shares and all that. And then once you buy the shares back whenever you want, either to bank profits or to cut losses. That was shares are going to automatically get returned to the broker. So all you have to do as the trader is just click buy and sell, and that's it. And so that covers it for short selling. I hope that made sense. Again, it's a pretty simple concept, just the inverse of buying stock. And the second concept I need to cover really quickly. It's very simple. It's just the concept of notional value. And this simply means the total cash value of your position. And you calculate this by just taking the number of shares that you have in your portfolio, either long or short. And you just multiply that by the current share price. So for example, clean back to, let's look at example two again. If XYZ was initially training for a 100 bucks per share and we short sold ten shares, then the notional value of that position is just ten shares times a 100 bucks per share, which is $1000, that's the notional value. And then went XYZ rise to a 110. The notional value is just 110 times ten shares. That gives you one hundred, one hundred dollars. And that's it. That's all notion of value really means. And so the reason why I'm telling you this stuff is because the trading simulator here is actually going to take advantage of those two concepts to actually make the traits. Because in pairs trading when you're dealing with two assets that are positively correlated, when that relationship breaks down, the way you're going to make a trade on that is you're going to buy shares of one of those assets. And then you're going to short sell a certain quantity of shares of the other asset. And the quantity of shares that you are going to be buying and selling. Those quantities are going to come from ensuring that the notional value between those two assets is going to be about the same. So let me break this down and show you what I mean by all this. So let me come back to our spreadsheet here that you saw in the last video. And so we're going to focus here on just QQQ in IUWM, this relationship right here and here, all the price ratios again and the statistics that you saw previously. And so now tying all this together and how the trade simulator is going to work is it's going to, like I said, Walk itself through all of this data here. And it's going to calculate the price ratios along the way. And keeping in mind what the average ratio is and what the standard deviation is also. And once it finds a ratio that is one standard deviation away from the average, either above or below it. It's going to make a trade. And the way it's going to make that trade, it's going to short sell the stock that has exploited to the upside. And it's going to buy or go along the asset that has really sold off. So for example, let's say QQ and I WM, which normally move up and down together, right? Let's say QQQ At some point really has a strong rally and explodes to the upside. And I, WM does the inverse and it really sells off, right? In this case, the two stocks have diverged. And since we're taking the ratio of QQQ to IUWM, if the price of QQQ increases and the price of IUWM decreases, taking the ratio that is going to increase the ratio between those two prices. And once that ratio increases to the point where it's one standard deviation above the average than the trading simulator is going to short sell QQQ and it's going to by I WM. And that's because for the ratio to come back down into alignment, to come back down to around where the average usually is. Qqq is going to have to sell off. And I'd WM is going to have to rally. Because as the price of qg, qt then decreases and as the price of IUWM increases, as going to decrease the ratio between those two prices, which is obviously what we want. And so in essence, what the similarly is going to do is once the ratio has gotten to an extreme 0.1 standard deviation above or below the average, is going to buy the asset that it has gone a lot lower. And it's going to short sell the asset that has gone a lot higher. And I'll walk you through one more scenario here just to make this little more clear. So let's say going forward, I wm is the one that has a strong rally, and q, q is the one that sells off. So as the price of QQQ goes down, and as the price of IUWM goes up, that's going to decrease the ratio between QQQ and I WM. And the way that ratio is going to come back into alignment with where the average usually is. That means IUWM is gonna have to change directions and start to sell off. And QQ is going to have to rebound and start to rally again. So regardless of how these stocks actually diverge, doesn't matter in which directions QQQ goes and where I WM goes as long as they diverged, period, we're going to buy the asset that it has gone lower and we're going to short sell the asset that has gone higher. And the last thing we have to do is answer the question, OK, well, how many shares of IUWM and QQQ Are we going to either buy or sell? And the answer to that question depends on the notional value between our QQ and our IUWM positions. So the goal here is to get the notional value of our OWN position to be exactly the same or very close to the notional value of our QQQ position. And as a very simple example here, let me pull up the calculator again. Let's say QQQ is trading for $100 and IUWM is trading for $50. And let's say QQQ is the asset that has really exploded to the upside. So we're going to short sell that one. And IUWM has really sold off. So that's the one we're going to buy. And so what we can do here is we can short sell one share of QQQ. Because shorting one share of an acid that is priced at $100 gives you a notional value, obviously of $100. And so now we want to buy a certain quantity of IUWM that will also give us a notional value of $100. And if I Wm Is Killing training for 50 bucks, then what we can do is by two shares of IUWM. So 50 times two. Is also $100 and it's a simple as that. We're just going to buy and sell shares of our two assets here such that the notional values between them are basically equal or very, very close. And so now that I have all that laid out, finally, we can return once again to our trade simulator here. And I'm gonna go back over here actually to my terminal. This is where I'm going to run the application. And this line up here, this is how I'm going to execute it. And these little arguments right here. This just allows me to configure how this application is going to run. So this first argument here, this hissed a, just stands for history a. And so this specifies that we're going to take in the full ten years of data for QQQ and then for history be same kind of concept here. We're going to also take in the full history for IW him. And like I said, that's the data that this application is going to walk itself through. The next argument is this Z thresh argument. And this just means that as it's walking itself through the data and calculating the price ratios between QQ and OWN. Once it finds a ratio that is one standard deviation away from the average, either above it or below it, then it's going to make a trade. Assuming it's not already in a trade. And he's lost two arguments. This first one here is Prof. P. This is our profit point, or the profit percentage, I should say. What this means is we're going to exit the train. And once we have a 2% profit based on the total notional value of the entire position. So for example, if we have $500 of total notional value for a QQ and 500 bugs have notional value of IUWM. Add those two together, that's 1 thousand in total between both of these, right? Then 2% of that would be 20 bucks. So once we make 20 bucks on the trade, we're going to exit it. Which obviously does not sound like a lot. But when you are doing pairs trading with just stock by itself, you're typically not going to be able to take profits a huge percentages. And though I am showing you all this analysis and this example here with the trading simulator, with just stock trading. I'm actually going to show you in the next video how you can also do pairs trading with options and futures that will lead to make greater percentages of profit and also put up way less capital. So all this is really just for example purposes. So you can just get the general gist of how this kind of trading strategy or this trading style actually works. And the last argument here is the stop percentage. This is when we're going to cut our losses and just get out. And you'll notice here is currently set to one which is basically 100%. Which means that if we have $100 of total notional value between qg, q, and pwm. We're basically saying here that we're willing to risk all of it to make some sort of profit on the trade, right? 100%. Which might sound totally crazy. Because pairs trading is actually a great way to reduce risk because you are trading to assets that are highly correlated in an inverse fashion, you're typically going to see very little volatility and these kinds of traits. That's not to say you are not everyone to see losses that are temporary, right? Because of course, once you've promised pairs trade, it could still move further and further against you before things eventually come back around and come back into alignment. But if you wait for a one or even two standard deviation, move, the chance that it's going to continue working against you is much less than the chance that the trade is actually going to work for you at some point in the future and eventually come back into where it should be, meaning the divergence between these two assets will come back into alignment. And the ratio will come back to the average. We're just going to allow those losses to expand it they need to, and we're going to hold that trade for longest possible until these two assets here eventually come back into alignment and we can actually make some sort of profit on the trade. So let me go ahead and press Enter here and boom. So over the course of this dataset, if found three possible trades and looking at trade number one here, we can see that the entry date was 2010, December sixth. And on this day, QQQ was trading for a price of $48.66 and we bought 11 shares of QQQ. So this was the acid that had really sold off. Iuwm was trading for a price of $66.12. And in this case we short sold eight shares of IUWM. That's what the negative eight means. So this was the asset that had really exploded higher. And you can see we were in this trade for quite some time, right? We got out about eight months later on August fourth of 2011. And these were the exit prices of these two assets. And the total profit was about 26 bucks, which again, might not seem like a lot of money because this is only a 2% profit target. And secondly, we're only dealing with, in this case, 11 shares of an asset that's about 50 bucks a pop, and eight shares of an asset that's only 66 bucks a pop. So the total notional value here is really quite small, only a few $100. And so I'm making a 2% profit on that is obviously not going to be a huge amount. And like I said earlier, this is all just for demonstration purposes. It's just to give you examples and real data to see how trades like this actually work out. But of course, in the next video I'll be showing you how you can do this kinda stuff with options and futures to make larger profits, put up less capital, and also give yourself higher probabilities of actually making a profit on these kinds of trades. And also I want to direct your attention to the actual share quantities here. If I pull up the calculator, actually me, bring it over to this desktop right here. So pulling out the calculator, if I take 11 shares, a QQQ that we bought, and I multiply that by the share price that gives us 48.66. So the total notional value of our QQQ position was $535. Which means H shares of IUWM should give us a very similar amounts. So we take eight shares of IUWM that we short sold and multiply that by the share price of 66.12. And that gives you $529, right? Very, very close. Obviously because we're dealing with whole shares here and not fractional shares, you're not gonna get notional values that are exactly equivalent. But as you can see, we got very, very close. And so then moving on to trade to same kinda thing. Looks like we are in this trade for exactly one month and we made 296 bucks on that trade. And then in trade three, looks like we were in this trade for about five or six weeks and we came out with a 1000, $166 profits. So the total profit between all three trades is down here, was 1400, or basically 1500 bucks. It's like I said earlier, by basically saying we're going to letter or losses if they do occur, we're gonna let them do their thing and we're obviously going to be taken losses at some point in the trade. But as long as we trade small enough, we can hold onto these trades for as long as we need to. So that by the end, once the relationship between QQQ, an IUWM eventually does become respective once again, and these two assets move back into alignment. Actually still make money on the trade. And when I say staying smaller, trading smaller, that would mean that since the, you know, for example here at the total notional value, like we saw in this first trade here between QQQ and IUWM, the total notional value between this two was about $1000, I think. But if your account value in total was maybe $50 thousand, then this is still a very small trades. So even philosophize do get pretty big at some point. Those losses are only going to be a very small fraction of your total account. Which means you can just continue to hold this position obviously for eight months in this case, until eventually came back around and it was profitable. And you can see if I run this application again. And maybe I set our stop percentage at 10%, right? So now once our losses hit 10%, we're just going to cut them and get out. You can see now, in this case there are actually more trades because once that stop-loss got hit, we were out and were able to make a new trade. But still in the end, we actually came out losing about $3,500. So again, this is just why I generally like to, when doing pairs trading, that is, just let my losses run a little bit longer than I might normally let them so that I can just keep holding them. And eventually the trade will likely become a winner in the end. And then finally, a run this application one more time. And with our other pair that we have, which is GLD and SLB cell. Just change these arguments to GLD and SLB. I'll hit enter. And there you go. So over the ten years of data that we have here, there were seven total trades between these two assets, and the total profit in the end was 830 bucks. And similarly, you know, if I were to once again try and cut my losses sooner than just letting them grow to as large as they need to be before things come, came back around. If I set my stop percentage at 10% again. Okay, or so are still profitable in this case. But obviously, the total profits in the end are half. We have more trades that we did, right? 20 trades in this case, but our total profits at the end of the day are obviously much smaller. And if I were to cut my losses maybe at 5%, then in this case, I'm actually going to be losing money in the long term, even with more trades, more potential opportunity. If I'm just to skittish and I'm getting out of my trade is the moment I start seeing losses. Well, that's actually going to really hurt me in the long term. And this is why when you're doing pairs trading, it's always important to stay small so that you can continue to hold these trades even when they do move against you and even sometimes quite substantially in the hopes that at some point down the road, maybe a few weeks or even a few months, the trade will eventually come back around into your favor. Now of course, this does not always happen. At some point. You may just want to cut losses and move on it. There are other opportunities you see and you want to use the capital for that. Generally speaking, because these trades are meant to reduce risk, which will therefore mean you're going to have to stay in these trades for a longer period of time to see potential profits, it's best to just stay small and hold the position until it most likely comes back around into your favor and you're able to profit from the trade. And so I believe that covers it for this video. I'm I know it was long one and there's a lot of information and stuff thrown at you in this video. So if you have to watch it two or three times, I would definitely recommend that. But in summary, once again, once the price ratio between two assets that are normally very correlated to each other, pits in extreme point, maybe one or two standard deviations away from the average. We're going to buy the asset that has really sold off. We're going to short sell the asset that has really exploited to the upside. And in the case of trading stock here, we're going to hold that position until we can take out a few percentage points of profit. At that takes a long time to come to fruition while then we're gonna stay small on trade entries that we can continue to hold that trade for as long as possible until we hopefully can take out some sort of profit from that position. And so in the final video coming up next, as I said, I'm gonna be showing you how we can do the same kind of pairs trading strategy with options or futures. And I'm also going to show you how the thicker skin platform can make a lot of this very simple and easy in terms of showing you visually when ratios are getting two extreme points, are showing you how correlated assets are to each other and things like that. So whenever you're ready, I'll see in the next one. Thanks.
5. ThinkOrSwim Demonstration: All right, welcome back to the last instructional video of this course where I'm gonna be showing you the various charting tools and features that you think are some platform offers which allow you to identify when two assets which are normally very positively correlated actually start to diverge from one another. Which then obviously brings about great opportunities for pairs trading. And then I'm also going to show you the various ways you can do pairs trades with different financial products, whether you're trading stock or futures or options. All three of these different kinds of products offer you great ways to make pairs traits. And so what you're seeing here is the price action chart over the past three years. And this is a weekly data here. So each one of these bars represents one week. And this data will show you the price difference between QQQ in OWN. This is one of the cool features that thing or some offers. Instead of just looking at a normal price action chart for one individual stock by itself. You can type in QQ, dash OWN. And that will bring up a chart like this which just shows you the price differences of these two assets over the past three years. Now this is obviously different than calculating the ratio between qg q and i WM. And that's shown down here below, which I'll get to in a minute. But this graph is just showing you the actual price difference, right? Taking the price at QQ and subtracting from that, the price of IUWM still a valuable thing to look at because we can see for the first half of this, of this three-year period, the price difference between q dq and IUWM was pretty constant, right? These two assets obviously fluctuated up and down together, which kept the price differences between them relatively the same. And we can see that being reflected in the correlation graph right here. And so the way you interpret this graph is on any given point on this graph, the software here will take the previous 200 weeks of q dq and IUWM price action. And it will calculate with that data that passed 200 weeks the correlation between them. So for example, on October or in October of the year 2017, roughly point on the chart. We'll take the previous 200 weeks of data of QE2 and PWM and then calculate that correlation, which you can see is very high. It's right around 0.95. so at this time, these two assets were very, very highly correlated. And then now getting to the price ratio chart down here, the way this works is for each one of these bars, for each one of these weeks, the software just takes the price of QQQ and divides it by the price of IUWM. And the opposite gives you the price ratio between them. And so obviously, as you can see here, during the time where the price differences were very stable, the correlation was very high and very stable. Obviously, the ratio between these two assets was also very stable, right? The ratio is right around one. But as time moves forward, we can see the price difference is starting to increase, right? So this would mean that the price of QQQ is going higher than the price of IUWM. So they stock prices are starting to diverge, although not bias by a huge amount, but even the small divergence we can see being reflected in the subtle breaking down of the correlation between these two assets. And then same thing with a ratio, we can see it's starting to increase. And then finally, when the coronavirus pandemic happened and the markets crashed together. Once the recovery happened, which is kinda right around in here, we saw the nasdaq, which is reflected by the QQQ IETF, right? We sell the nasdaq heaven absolutely explosive recovery, basically hitting all-time highs every other day. And I OWN was also recovering as well. And the IBM is tracking the Russell 2 thousand small cap stocks that was recovering too, but at a much slower pace. And now in recent times it's basically going nowhere. It's actually kinda coming down a bit. And so you can see with this price difference chart, the differences between the prices of these two assets has really exploded. And he sues stocks have really diverge from one another. And that has also been reflected by the absolute breakdown of the correlation between them. The correlation used to be right around at 0.9 has dropped all the way down to about 0.25. So these two assets are almost not even cold anymore, at least in the short-term. And then moreover, we saw the price ratio between them absolutely explode too. And it's been hanging out around 1.8 for the past few months. And so this should also demonstrate that pairs trades can definitely takes some time to complete the full cycle in terms of the two stocks diverging and then staying diverged for quite some time. And then who knows how long it will be going forward, maybe a few weeks, few months, or even a year or two before these two assets eventually come back into alignment to where they normally are in most of their history. But obviously, since there's no way to predict the future, I would say just looking at these charts here we are in a great opportunistic situation to make a pairs trade on QQ and IUWM. And specifically, since q, q is the asset that has really skyrocketed, and IUWM is the one that hasn't really gone anywhere. That would mean QQQ is the acid we will want to short. And I, Wm Is the asset we want to buy and go long. And also briefly, I do want to show you the same kind of chart here between GLD and SLB, since that's the second pair we were looking at in this course. And so here we go and we can see for the same three-year period weekly data here for the first half of this of this three years, the price difference between GLD and SOV was remaining relatively constant and the correlation during that time was pretty stable as well, right around 0.73 or so for the majority of this time. Then by halfway through 2018, these two acids started to relate, diverged, right? The price difference between GOD, SLB got greater and greater and greater, meaning GLD was going much higher and SLP was either going nowhere or going lower. And once again, we can see the same kind of phenomenon being displayed in the pair correlation chart, right? The correlation between these two assets started to really breakdown as this was happening here. And now in recent months is starting to recover a bit. And then also looking at the price ratio chart or the pair ratio chart, especially when the carnivores pandemic hit the ratio totally exploded. So this would have been a great opportunity to make a pairs trade on, on gold and silver. And then after that a totally collapsed. So this would also been a great opportunity to make a pairs trade. And now finally, recovered to the point where it normally is based on the past three years of data here. So definitely ought to say you can't do this kind of a spreadsheet analysis, downloading historical data, calculating the PE ratios in the statistics here, and doing all this manual stuff yourself. You can certainly do this to either teach yourself, make you, make yourself more confident and all this kind of information. But I would say this is probably a bit overkill. I obviously wanted to do all this just to help you really learn this material in this course. But if you're trading platform has these kinds of metrics here, these kinds of graphs. I would say you can definitely rely on this stuff alone. It's obviously going to be a bit more subjective in terms of identifying, you know, at what point is the pair ratio extreme enough for you to make a trade? But you can obviously see visually over the past three years, you know, it's obviously been pretty stable. So just looking at this chart here is pretty obvious that at this point in time the PE ratio was at a pretty extreme point. And then same thing given where it fell to down here. But if you wanted to come up with exact numbers in terms of standard deviations and things like that to kind of figure out or quantify how extreme a ratio actually has become. And you can definitely do this kind of analysis. It's not that difficult. It's pretty easy to run through this quickly. Obviously, Excel has built in functions that will calculate these numbers for you. The one caveat I would say is probably not a good idea to use a full ten years of data. Because as you can see on these charts, the correlations and ratios are very dynamic in the short term. The reason why I use ten years of data in my data set, there's because I wanted to have enough data for my trading simulator to use to actually output enough trades to look at. But I would say if you're doing this kind of analysis on your own, probably use two to three years of data to give yourself obviously enough price action to make your calculations accurate. And the results of these calculations will be a bit more accurate given the short-term future that you're probably looking at. And I believe that covers it for the various charting tools I wanted to cover that thinkorswim offers. So now I'm just gonna show you briefly on a high level here of just the different ways or different options you have when making pairs traits. So I go to the trade tab now, and let's go back to our IUWM and QQQ pair. So I'm just gonna type in QQ for now just to pull up the treading tab for just this asset by itself. And what you're seeing here is the option chain if you wanted to trade options on QQ. And here's where you can see the actual stock trading price for the actual Keith Q ETF. So just to give you a brief example of how you would do this with stock in a real trading platform. On the way we would do this is since Q, Q, again, is the one that has really explore into the upside, this is the asset we would want to short. So I can just click on the bid here. And that will automatically bring up a, an order here to short sell 100 shares of QQ. And I can set the price at which I want to sell the shares for. Now, obviously based on what you saw in the previous video, I want to make sure the quantity of shares that I'm short-selling here would create a notional value of my QQQ position that would be very close to your equal, the notional value of my IUWM position. So if I run the numbers and I came to the conclusion that I needed to short, maybe I don't know, 87 shares of QQQ and I can just hit that number in right there. And then just hit Confirm and send and send over time. And that would place the order and it would take care of borrowing the shares and all that for me behind the scenes. And the cool thing is if you have a margin account like I do here, you will not need to put up the entire notional value of this position to actually hold that position, right? 87 shares of an asset as trading for $271, that's going to be tens of thousands of dollars. I don't need to have that much money tied up and locked away to hold this position. You can see my account is only require me that I put aside about $7 thousand. And this is one of the benefits you get with having a margin account because the rest of the money that you would typically quote unquote need to hold this position. You're actually just borrowing from the broker. So this is the only amount of money I would actually have to fork over myself, my own trading account to hold this position. And so that would take care of Q Q And then I come over to IUWM now, and since this is the stock we went to buy or go along, I can just go over here and click on the ask now. And that brings up a default order of buying 100 shares of IUWM. And again, I'd have to run the numbers and figured out maybe, okay, I need it by 92 shares are needed by 92 shares of IUWM. And I can set my price right here, taken from insane. And we can see that brokers only require me to have about $4 thousand locked up for this position as opposed to the total notional value of this entire position, which we weigh more than this. And then once I hit send, I'm basically completely into my appears trade between qg q and i WM that was obviously with stocks. So if I go back to QQQ and how do I do this with options? So for example, I'm going to come to the December contracts here because, you know, like I've like I've been saying, pairs trades can take a while to play out. So I want to give myself a decent on time for things to play out and work in my favor. So these December contracts have 82 days to go. That's pretty far. So I can scroll down here and come to the contracts that are right around at the money. And so once again, since QQQ is the asset, we want to short make money when that, when the price goes down with options. Here we have two ways we can do this. If you went to buy options on a Paris tray, which is what I actually don't recommend, but you certainly can't do this. So if you were buying options the way you would short keys EQ is you would buy a put option and obviously you have many, many choices here, but I'd probably go to put option that's right around at the money, if the strike here is 272, and q to q was trading for 271.5. So it's basically right at the money and I could set up an order to buy 11 contract of this put option. It's going to cost me about 1800 bucks and I would just hit Confirm and sand. And there you go. I am now in a short position on QQQ. Now one thing I will say is if 1800 bucks is too expensive given the size of your trading account, the way you can cut this down is by, instead of just buying a put option by itself, you can buy still the same put option, but then also sell another put option that's further out of the money. So for example, I can instead by a vertical spread here, still buying the 272 strike put. But then I can also sell maybe the 262 strike put. And that's all going to cost me 400 bucks to put up. Now that's also going to really limit my profit potential, right? Just buying an option by itself gives you theoretically unlimited profit potential. Doing a spread like this means I only have about 600 bucks a potential profit to make. But obviously I'm only putting up $400 to do so. So depending on the size of your account, you may wanna do something like this to bring the cost of the trade a lot lower. And so then going to IUWM now tied that in. Go to the IBM option chain. I go to the December contracts, of course keep everything the same. And since we are now bullish on IUWM, and if we are buying options in this case, I would want to buy a call option. So same kinda deal. I'm gonna go right to around at the money. I WMS trading for 146 bucks. So I'm gonna go to the $146 strike call option and I'm going to set up a buy order to purchase one contract. So here we go, buying one contract, 146 strike called antenna constantly button $943. And then same thing here again at this price is a little bit too much given the size of your trading account. You can also just once again by a call vertical spreads. So it's still going to buy the 146 strike call, but then also sell maybe the 156 strike call. And that'll bring the cost of the trade way, way down. Again, it will limit your profit potential, but there's always going to be those given takes when you are making trades in the stock market. Now for me personally though, I am, as I said, an options trader in my intro video of this course, but I never buy options unless I'm doing vertical spreads and specifically doing credit spreads. And I'll mention that briefly in a second here. But basically almost 100% of what I do is simply selling options. And you can watch my other options trading courses that will tell you exactly why I do that as opposed to buying options. Now if I wanted to put on a pairs trade between q dq and OWN by selling options. Let's go back to the QQQ chart here, or the option challenge and say, let's go back to at-the-money strikes. So now instead of buying a put option to get bearish on QQQ, we're just going to sell a naked call option on QQ. And it's also going to give me a bearish bias on this asset, but I'll be able to sell a call option way, way far out of the money, maybe right around here, the 296 strike call. So definitely very far away from where QQQ is currently trading. So it gives me a lot of room for this asset to continue moving against me and still make a profit on the trade. And you can see if I were to sell this contract, I would be able to sell this contract for $700. We'll need to put up a decent amount of capital to do so by hit Confirm and send, a broker is going to require that I put up $3 thousand of buying power to do this. And so once again, if you wanted to make a trade like this and the buying power is too much. Instead of selling just a naked call option like this, you can sell a vertical spread, which is just the inverse of buying the spread that I showed you just a few minutes ago. So we're still going to sell the two 96 call option, but we're also going to then buy a further out of the money call, a call option to cut down the buying power requirements. So you can see here again cell the two 96 call. But now I'm also going to buy maybe the 306 strike call. And in this case I'm only going to collect about 270 bucks, but the buying power has been reduced to only $730. And of course you can narrow the strikes even more to get the buying power even less. So you do have a lot of choices with options and how you can construct your trades to get your buying power reduction in the right sizing and also do collected enough premium to make the trade even worth it, of course. And then most importantly, when you are selling options and especially selling far out of the money options like I've just done here, you give yourself very high probabilities of making profit on the trade. And so doing something like this would give me that bearish bias on QQ. And then lastly, I can go over to IUWM. And now instead of buying a call option, the other way you can get bullish on IUWM with options is you could sell a naked put option. So same kind of concept. I might come to around the 135 strike, which is still very far away from where I WMS curly trading gives me a lot of room for the stock to work against me and for me to still make money. And I can sell this contract for $548 and the buying power would be about 1800 bucks. And then same thing as before. This is too large, Give me your trading account size. You can just buy another put option even further away. And that will bring down the buying power by however much you want. Just depends on how wide those strikes are. Then once I'm in this position, then I have fully entered my Paris trade between q dq and IUWM with my kind of bread and butter options selling approach. And so before I continue here, I do want to touch on briefly the concept of notional value, right? Obviously when we are trading stock, as you saw earlier, we want to get the notional values of r, In this case QQQ position to be about the same as the notion of value of R i to the UN position. Now the concept of notion of valued does break down a bit. It's really hard to translate over to the world of options. So in this case, when you are trading options to do pairs trades, I would mostly focus on the buying power effect and treat that as the quote, unquote notional value of your trade. And more specifically, I will try to get the buying power effect here between QQ and IUWM to be as close together as possible. So as you saw earlier, selling a naked call option on QQ and was going to acquire about $3 thousand of buying power. And for PWM sling and they get put is about half of that. So what I might want to consider here is still selling that one naked call on QQQ. But then now maybe son to naked puts on IUWM, right? Because if I do it that way, the buying power effect for my IUWM position is going to be about 3600 bucks, which is much closer to the 3 thousand for QQQ, that's going to be required for that call option than if I were to just sell this single a naked put option for PWM. So just keep that in mind when you're dealing with options, it's best to look at the buying power effect and try to get those as equal as possible. And the final thing we want to show you here before up this video up is how you would do all this with futures. And if you're not familiar with futures, they're basically just another form of derivative, just like option contracts, there are a lot more simplistic in nature. Actually. Just allow you to kinda the same thing, buy and sell certain quantity of an asset at some predetermined price at a point in the future, hence the name futures. So if I go over to here and I type in forward slash and Q, this is going to bring up the futures contracts for the nasdaq index. All right, so here we go. These are all the contracts we can be trading here. And once again, since the nasdaq or the key dequeues are the asset we want to short make money when the price goes down. I can just go to the active month contract which expire in December, and I could just sell one of these contracts. Now these Nasdaq futures are quite large in terms of their notional value. There are other forms of features like h0 minis and microbes that have smaller notional value amounts that you can be trading with much smaller account values. You know, like you can see right here, the price that could be sun as contract for is about $11 thousand. So these are very large products. Like I said, if you trade these smaller notional value versions, you'll be able to do so with much smaller trading accounts. So I could just sell one of these contracts and that would enter me into a bear's position on the nasdaq. And then just like you've been seeing previously, I could go over to the Russell 2 thousand futures, which is what I WM tracks, right? So just type in forward slash RT y. And that will bring up the Russell 2 thousand futures contracts. And here we are once again, these are the contracts that can be trading. So I'm gonna go to the active month which expires in December. And since this is the asset we are bullish on, I'm not going to buy one of these contracts. And again, these contracts are quite large again, so there are other variants that I would recommend trading. And then once I hit Confirm and send, I am now officially in my Paris trade, which when the nasdaq and the Russell 2 thousand using futures contracts. And again, just in regards to notional value, the concept of notion of value actually does translate over to the teacher's role a lot easier than it does with options. So calculating the notion of value for a futures contract is actually pretty straight forward. And if you want to learn more about that and about futures in general, you can watch my future's introduction course, but the same general rule of thumb applies as I've been saying in this entire course, that you want to get the notional value of your Nasdaq futures position in this case to be roughly equal to the notion of value of your Russell 2 thousand futures position as well. The closer you can get those notion of values to be equal, the less volatile and the less overall risks you're going to have in that position. And so I believe that covers it for this video. I know I threw a lot at you again in this video with all the different kinds of financial products with futures in stock and options and things like that. So, so if you're unfamiliar with some of these products or some of the strategies that I use, like the vertical spreads or naked poets and understanding the differences between buying options and selling options and things like that. I recommend you watch my other courses on skill share on options trading in futures and things like that. And those will get you up to speed on those kinds of concepts and those products so that you can be really diverse and had a lot of choices when you are making pears treats. So thank you so much for watching and I'll see you in the final video coming up next just to wrap things up.
6. Wrapping Up: Alright, congrats to finishing this course. I hope the information you learned here is going to be valuable to you in your trading activities and to help you get started with Paris trading, you can take a look at the course project down below. And I do also want to say that whenever you are attempting a brand new strategy or your training with a new product, I would recommend you do so first in a paper trading account, which is going to allow you to trade with fake money. The reason being is mistakes are certainly quite easy to make when you're trying something new. And they can also be very costly when making those mistakes in the real market. And once you have that confidence and you have a firm grasp on what you are doing is then very easy to switch over and start using a real money account. And so with that being said, thank you so much Washington's course. I do appreciate any and all feedback that you have. My MD scout Reese again, I do try and publish one new course every two weeks and please do also check out the other courses I have unskilled. Sure. I have a lot of content already published on options trading concepts and stock market investing concepts, as well as if you courses on computer science related concepts. So please do check out those as well, and don't forget to also follow me in skill share as well so that you'll get notified every time I publish a new course. So thank you for watching and happy trading.