Session 3. Swing Trading Models

[00:00:51.11] - Speaker 1
Good morning everyone and welcome to this product training session. Today we're gonna focus on our swing trading model and our swing trading model indicator. So please let me know if you guys can hear me. Okay. If you have any initial and we'll go over the presentation.

[00:01:10.07] - Speaker 1
So stay tuned on what we're going to show you today. So in this session we'll work through what the swing trading model is and how it works, how can we use it and how can you help? Can it help you as a trader to find an edge in today's complex market? Right, we're going to go over a product demo on how you can find it in the dashboard and we're going to show you also some backtesting results from last week and then we're going to answer any question at the end and also frequently asked question from our users so we can start. And basically what is the swing model indicator?

[00:01:49.17] - Speaker 1
So swing model is probably one of our more advanced model is a machine learning driven tool that basically the goal is to forecast the expected price movement over 5 days and 20 days. It integrates momentum, option flow, market positioning, gamma delta. And the idea is really that we are trying to calculate where the price will most likely to move and where the risk is most likely going to be emerging. So areas where you should be focused on as targets and areas where you could actually expect a lot of volatility.

[00:02:29.06] - Speaker 1
So markets are very noisy, right. So especially in today's environment, headlines sentiment can really move the needle very fast. We've seen it in the past week, in the past couple of days. And also the problem is that we also have lagging indicators that can sometimes provide full signals for our trades. But what if you had a data driven roadmap that can tell you where the price is likely to go, where is likely to stop or reverse and what are the levels that are make or break for momentum trades.

[00:03:05.02] - Speaker 1
And this is exactly what the model is looking to deliver. So think about our swing trading model as your personal roadmap for navigating into short to medium term volatility, leveraging a data driven approach. So instead of really relying on lagging indicators that are looking at past data, the swing model is really like providing you with predictive levels and with quantified probability. And we refresh the data on a daily basis.

[00:03:38.04] - Speaker 1
So finding the edge as retail traders is really about reliability and repeatability. And what the swing model can give you is a few things. One is a directional bias. So the model has a bullish or bearish bias on a daily basis based on position changing and regime changing, you also get tradable levels. So the swing levels can really map out some of the stronger reaction zones and breakout targets.

[00:04:09.24] - Speaker 1
And of course there's a lot of statistical analysis there. So we, we're looking at, uh, we're going to show you also uh, the back testing results and the success rate of the model. So you can actually understand how good the model has been on the asset that you're looking for over the past few months and weeks.

[00:04:30.25] - Speaker 1
So the goal is to help you trade with an edge that is backed by data and statistical analysis. So let's go into what the model does and I think we've done a few sessions here, but I think we want to simplify how the model looks like. So we have three components of the swing model. The first that we're going to go over is our lower band. The lower band is the lowest price that the model expects over the next five or 20 days.

[00:04:58.14] - Speaker 1
So the model has two time frame, five days, 20 days, which is really one week and one month. So the lower band for our five days would be the lowest price that the model expect the price to go over the next five days. Think, think as the lower band as a strong support level. And the lower band can be ideal for entrance bounce setups or long exposure around that level.

[00:05:26.24] - Speaker 1
Then we have the upper band, which is really the highest price level that the model expects. And think about this as a resistance zone. It's great for fading strength or exiting long positions or potential reversal trade to the downside. And then the third element of the model is our risk trigger. The risk trigger is a pivotal level where momentum could flip, but it could also act as support resistance or as an inflection point.

[00:05:58.11] - Speaker 1
So remember, the model is aiming to give you a directional bias. So if we are able to detect the trend and the bias, then the risk trigger could become also a strong inflection point. But it's really good for helping you define your risk, helping you define your time of entries and also your profit target. So the levels are really updated every day. They are available through the dashboard.

[00:06:26.12] - Speaker 1
They are available also via the indicators. And we're going to show you also in a second a very, very good demo of how to use those as well.

[00:06:39.08] - Speaker 1
All right, so this I think is very important because we highlight some of the key differentiator of the indicator. So the swing model only gives you one directional bias each day. So each day we are only going to see either a lower band or an upper band. If you see a lower band the model is bullish and if you see an upper band, the model is bearish. The lower band will also be highlighted in green and the upper band will also be highlighted in red.

[00:07:09.12] - Speaker 1
So it will make it easier visually to understand if we are in a bullish or bearish bias. So basically this is really clean and simple. We are either in a bullish or bearish bias based on the model.

[00:07:25.12] - Speaker 1
So now let's look at it and let's break it down, how it works and how it appears. So, so this is how the model appear. We're gonna access it via the dashboard and there are certain parts of the model that you should be looking for. So first we're gonna look at the right side of the chart which is really looking at the current level. So what you see in the red box there, in this case we are seeing, we're looking at Nvidia and this is our five days model.

[00:07:53.14] - Speaker 1
So we are seeing a lower band, we're seeing a level of 162.94 and we are also seeing a risk trigger at 184.5. So those would be the two levels from today that are going to be relevant for the next five days. In this case.

[00:08:16.03] - Speaker 1
Then we have our left side. So the left side and a few of our users get confused because they look at the right side and they look at the left side. The left side is really showing you the historical performance of these levels. So until yesterday we are showing you how these levels perform. And basically also this would go into our back testing results.

[00:08:40.02] - Speaker 1
So if, let, let's identify what success is for us. So if the lower band is present and the close price of the asset in five or 20 days is, is above the lower band, then the model is successful. If an upper band is present and the close price of the asset in five or 20 days is below the upper band, then the model is successful as well. So in this case we are looking at the lower band of 162.94. For it, for the model to be successful in five days from now, the price of Nvidia should be closing above 162.94.

[00:09:17.27] - Speaker 1
And, and if that happens, then you will see a success rate of the model. So yeah, so that's, that's the way it works. So the goal of the model is really to forecast where the price would be and what range the price would be in five days or 20 days from now. At the top we see the back testing results. Right.

[00:09:38.15] - Speaker 1
So what we see in the chart is we See the risk trigger success rate, the upper band success rate, the lower band success rate, and then the swing model success rate. That is really combining both the upper band and the lower band success rate. The model doesn't really take into account the risk trigger success rate. And the reason is very simple because we are trying to provide a directional bias. So if the directional bias is successful, then it could happen that the risk trigger gets broken.

[00:10:10.25] - Speaker 1
That's why we are looking at the success rate just by analyzing the upper band or lower band success.

[00:10:20.16] - Speaker 1
All right, now who can use the model and how can we use it? Right, so this model can be used by swing traders, option traders, in particular option sellers. And we're going to show you some example today, future traders, as well as position traders. The swing model is available on stocks, ETFs, indices and crypto. And for future traders, what we can do is we can convert the swing level to a future contract.

[00:10:48.24] - Speaker 1
We're going to show an example later. For example, if you are trading es, you could convert the SPX swing trading levels. If we are trading nq, you could use QQQ or NDX and so on.

[00:11:06.21] - Speaker 1
All right, now let's look at how to trade the model. So we're going to start with the upper band. So the upper band is considered for us as a resistance zone, is the highest price level that the model expects within the time horizon, whether it's five days or 20 days. So we can use this level to either set our profit targets. If we are in a long trade from the past, we can also identify potential fade zones.

[00:11:36.21] - Speaker 1
So basically this could be a good entry point for a reversal trade. And then of course, we can use it to avoid chasing breakouts or into exhaustion. And this could be very, very important level that you guys can use, especially if you are looking at taking profit and the potential reversal trade. The second is the lower band. So this is the lowest price forecasted for the next five or 20 days.

[00:12:07.24] - Speaker 1
And basically this could be an interesting reversal zone for a long entry. And also it could also become a very important level for a stop loss that can provide again a statistical support.

[00:12:26.08] - Speaker 1
And then finally we have a risk trigger. So the risk trigger for us is kind of like a breakout point. And it can be very reactive and it can become a warning for an increase in volatility, or it could also become a momentum shift level. So you can use those levels basically to potentially time your entries as well as managing your risk and managing your exit as well.

[00:12:54.22] - Speaker 1
All right, so now that we understand what they are we understand how the model works and then we're going to go into some example. Let's just build a very, very quick framework on how we can apply the swing trading model based on your strategy. So the first thing we're going to look for is directional traders. Directional traders could be traders that are trading the stock, they are trading options. But the idea is really to use the model to potentially formulate a theory on the direction of the price.

[00:13:25.27] - Speaker 1
So the idea behind the swing trading model is to forecast where the price is likely to be in five days or 20 days based on a strong directional bias. So if the model shows a lower band, it's forecasting that the price has room to move higher. So the bias is bullish. If it shows an upper band, then we are kind of looking for a downside move and the bias is bearish. This means that as directional trader, your job can become a little bit simpler where you are basically looking to trade with a bias.

[00:13:59.27] - Speaker 1
It doesn't mean that the price, if we see a lower band today, it doesn't mean that the price will necessarily go up. But you do have a very strong roadmap and a strong bias on, on where the price could be in five or 20 days from now. So very, very good idea there or potential ways to implement the strategy would be to buy pullbacks when the model is bullish or basically fade rallies or short. When the model is bearish, you can use the levels as reference or target price. And basically you can also use a risk trigger as your potential exit or target level.

[00:14:43.26] - Speaker 1
So the idea behind it is that really provides you with a clean roadmap that basically is really looking at data. So it's not looking at simply support and resistance errors in the chart, but it's using our advanced analytics to provide you with the guidance and a roadmap for the move in the next five or 20 days, the next, the next thing or the next strategy that can the people or users can leverage. Our swing trading model is if you are an option trader and in particular an option seller. So the model is really looking at price zones that are unlikely to be breached within the next five or 20 days. Right.

[00:15:29.05] - Speaker 1
So you can use this, the levels as do not touch zones to understand where you can place your strikes for your option trading strategy. So when we see a lower band, the market bias is bullish. So the higher we have a higher probability of success with maybe put credit spreads when an upper band is present, then the market bias is bearish. So cold credit spreads or bearish premium strategies Are probably can provide a better advantage. And basically the model can really be ideal for users who are structuring credit spreads.

[00:16:10.02] - Speaker 1
Iron condors where you can use both wings or other more advanced strategies like butterflies or broken wing butterflies and so on. So basically like the idea behind those levels is that they do not touch zones so that we are trying to understand the range where the price should be in the next five days or 20 days.

[00:16:34.22] - Speaker 1
If you are a futures trader, then you can actually use the model to identify high probability inflection zones across key contracts. For example, we can convert the levels on YES and Q rty, cl, GC and so on. Each day you get a directional bias, whether it's a lower band which stands for a bullish bias or an upper band which stands for a bearish bias. So you could actually look at setups by looking at long setups on pullbacks if you see a lower band present or short setups on rally if you see an upper band. And basically these are very, very interesting areas and we're going to show you some examples.

[00:17:25.18] - Speaker 1
What are the benefits for our traders? You have first you have a way or a tool that is looking at data to potentially make decisions. So you have basically clear entry and exit level that are supported by data. So not emotions. They are, they're looking at data.

[00:17:44.14] - Speaker 1
You can use them for risk management so you can know where your downside can be or your upside can be. And you can also understand where we could see an increase in volatility. And then of course you can actually use them for planning your strategy by looking at outlooks of over next five days or 20 days. And again it can also be used by longer term position traders to understand the sentiment and the bias in the market.

[00:18:14.14] - Speaker 1
All right, now we're going to go into the dashboard and then we're going to go into some backtesting and at the end we're going to answer some questions as well. So if we go to the dashboard, I'm going to open it up here. What we have here is Nvidia. So we are in our end of day section of the dashboard right here we have Nvidia right there. And what we see at the bottom is our string model 5 days and 20 days.

[00:18:42.26] - Speaker 1
So if we start from our 5 days model here again on the right side to to repeat this, we now have our levels for the next five days. We have a risk trigger, a 190.84. We have a lower band of 169.16. On the left side we have our history. So we can see basically how the price behaved around these levels.

[00:19:07.01] - Speaker 1
So for example, right here, the five days level that you would have got five days before this candle was at this level. So you can see clearly see that the candle closed above that level that you would have got five days before then. You can look at the backtesting results right here. So what the model is telling us is that our risk trigger has a success rate of 75% over 119 days. Our upper band has a 57 success rate of only on 19 days.

[00:19:35.29] - Speaker 1
So we were bearish on Nvidia only on 19 days going back here. And we can see the lower band as a success rate on of 87% over the past 100 days. So we saw over the period in this chart, which is 119 days, we saw a lower band on 100 of those days. And out of 100 of those days the lower band had the success rate of 87%. On the other hand, the, the upper band was only present on 19 days and we had a success of 57.89%.

[00:20:09.17] - Speaker 1
We can do the exact same thing if we look at our 20 days. So the swing model success rate in this case over the past 104 days is 85% 85.58. The lower band was successful on 89% of the cases and the upper band was successful on 68.42 and was only present on 19 of those days. And as you can see, the risk trigger level only had the success rate of 41.35. But again, the goal of the model is to provide you with a directional bias.

[00:20:42.23] - Speaker 1
And of course, if we are able to identify the trend, then it could happen like in areas like this where the price breaks, the risk trigger and the risk trigger can really become a strong inflection point as well.

[00:21:00.27] - Speaker 1
You can access the levels on any stocks, ETFs and indices. So once you save it in the dashboard, you can also come here and look at the different, the different levels. So it's always there, it's calculated at the end of the day. And you can then combine it with our other model, our Q score. And today we're going to show you some example.

[00:21:24.11] - Speaker 1
So please send us any questions. We're going to go back into the slides and we're going to show you now some back testing results. Right. So the first thing that I want to show is we showed this slide in last week's training when we were talking about gamma levels. I think it's very important because what we're Going to show you today is how you can actually think about trading like an institutions.

[00:21:52.23] - Speaker 1
So what you see in this slide is how institutional traders trade. They would use a large amount of data to create a strategy and to improve their alpha. Right. So what we, what we're going to show you today is a similar approach. So they would use maybe Bloomberg Terminal, they would use alternative data, they would use other data.

[00:22:14.28] - Speaker 1
And the goal is really to add more factors that can provide a better risk and reward and better return to your strategy. So let's go into some backtesting results from last week. So we looked at last week. The reason why we did that because it was a very, very interesting week. We had a lot of earnings, we had the big tech companies reporting.

[00:22:39.06] - Speaker 1
We also had a very, very volatile week. So what we're going to show you today is how the model perform and how you can use it in conjunction with some other of our tool. So we're going to talk about our Q score. But before we do that we're going to start with the first step which is really beginning with the foundational tool which is the swing trading model indicator. So again what the model gives you is directional bias bullish or bearish.

[00:23:06.18] - Speaker 1
We have our levels, we have our lower band, our upper band and our wrist trigger. And basically just alone, just using this alone it can give you a high probability roadmap for where the price is likely to move. Right. But again we're going to look at it on how we can add some other models and how we can actually tilt our strategies based on the models and mentor Q provide. So here first we are looking at some assumptions.

[00:23:38.11] - Speaker 1
So we took the data that you will see today and this is also available on our blog. I'm going to share the link is looking at the levels as of the end of day Friday July 25th. So the levels that we take are looking at July, Friday close. So we took the levels and then we use the levels to then trade at the open of Monday, so 28 July and simply close at the, at the close of Friday 1st August. There's no risk management involved, there's no, there's no take profit, there's no stop loss.

[00:24:17.28] - Speaker 1
So the goal really of this exercise, very, very simple is to show you how good the levels were and then how can we add more factors to potentially add alpha to our strategy. The strategies that we're going to look for are two types of strategies. One is a directional trading strategy. So if a bias is bearish, we then go short at the open on Monday. So we take the levels from the previous Friday, we go short at the open of Monday and we exit at the close of Friday.

[00:24:46.27] - Speaker 1
Very, very simple. If the, if the swing model bias is bullish, then we go long at the open of Monday and we exit at the close of Friday. The second strategy is using credit spreads. So if the bias is bearish, then we use a call credit spread. If the bias is bullish, we then use a put credit spreads using the levels as our short strikes.

[00:25:11.05] - Speaker 1
So using the upper and lower band as our short strike. And again, we are not looking at trade management. We're just looking to see if the price at the close of Friday of the asset closed above the lower band or below the upper band. Right. So the first really exercise is starting with just the string trading model alone.

[00:25:38.12] - Speaker 1
This is our baseline framework. So what you see here, and then I'm gonna go over into the file as well and show you the data and show you where you can find this exercise. So we looked at about 904 assets between stocks, ETFs and indices. And we looked at a portfolio size of $1,000 per trade. So the total portfolio size was 904 k. And the reason why we do that is because we want to have an equally weighty portfolio to understand the accuracy of the model.

[00:26:09.17] - Speaker 1
In this case, the win rate was 33.85% with a return of -1.37%. Just to note, last week was a very, very volatile week, was probably one of the most volatile week of the year. We had a lot of news, we had a lot of events with a lot of earnings. So what we want to show you is how you can then use our other models to then potentially add values to that, to that exercise. If we look at a simple option selling strategy over 904 assets, our win rate was 75.44%.

[00:26:47.02] - Speaker 1
That means that the price at the end of Friday closed above the lower band or below the upper band on 75.44% of the cases. So what does that mean? That means that if you were to sell credit spreads, you would have been right on 75.44% of the cases. And of course, there's risk management involved and we're not going to go into that. This is really simply to show you the accuracy of the data.

[00:27:15.11] - Speaker 1
The next step is really to segment this. So how can we add one step forward similar to what do. How can we then add additional factors that can help me first narrow down my strategy and potentially have a Better return and better results. So the second step is really using the Mentor Queue score. So the Mentor Queue score, and let me go into where you can find it, is we're going to go into details of the score this week.

[00:27:47.03] - Speaker 1
We're going to have a separate product training, but you can find the Mentor Q score right here on the dashboard. And we have four different factors that we use. We're going to talk about option volatility, momentum and seasonality. So basically what this tells me is if we are bullish or bearish on an asset by looking at different factors, we're going to talk about option, momentum and seasonality in this exercise. So let's go back here.

[00:28:18.07] - Speaker 1
So the first, the first exercise, and we call this tilting our strategy. So we started from our baseline, which was simply using our swing trading model. So we had about 904 assets. How can we narrow it down? By adding some factors.

[00:28:36.09] - Speaker 1
So the first factor that we are going to add is our Q score, options and momentum. So what we do here is we filter out those 904 assets by our Q score. And we only take a bullish trade if the option and the momentum scores are equal to five. And we only take bearish trade if the option and momentum score are below 1. That means that both options and momentum, if they are five, they're very bullish, and if they're one, they're very bearish.

[00:29:09.19] - Speaker 1
So what happens here is that we now only have a universe of 120 trades. The portfolio size stays the same, and as you can see, our win rate improved from 33.85 to 41.67. And also our return improved from minus 1.37% to minus 0.09. If we look at our option selling strategy, then we are kind of like in a similar environment. We have a 75.83 success rate.

[00:29:42.29] - Speaker 1
Okay, if you have any questions, please send them over.

[00:29:48.09] - Speaker 1
Then we add another tilt to the strategy. So in this case, we want to test out the momentum Q score and the seasonality Q score would perform together. So in this case, what we do is we only take bullish trades if the momentum Q score is 5, which is really bullish, and our seasonality score is greater than 2. And we only take bearish trades if our momentum score is lower than one. So very bearish.

[00:30:18.07] - Speaker 1
And our seasonality score is lower than minus one. So just remember the seasonality score goes from minus five to plus five. Okay, so what happens here is that now we have only 24 trades. The portfolio size stays the Same. And our win rate went again from 35.33.85% to 41.

[00:30:41.00] - Speaker 1
And now we are at 58.33% with the return of plus 1.31%. If we look at our option credit selling strategy, our win rate also went up from about 75% to, to about 87.5%. Okay, so very, very important, we see a great improvement by combining momentum and seasonality score. But then we want to take it a step further. So let's now put everything together.

[00:31:13.08] - Speaker 1
And now we are adding our option score, our momentum score, and our season ID score. So we only take bullish trade if our option key score is greater than 4, our momentum score is equal to 5, and our seasonality score is greater than 2. And we only take bearish trades if our option score is lower than one, our momentum score is lower than one, and our seasonality score is lower than minus one. So we are now combining the three scores together. So as a result, what we see is that now the universe is also smaller.

[00:31:48.00] - Speaker 1
We only have 14 assets that match this criteria. Our win rate is now 57.14 and our return percentage is 3.18, which is great compared to also the previous exercise where we have a similar win rate but a better performance. And. But the most important part is that we now have a 100% win rate on our option selling strategy. So I'm going to show you where you can find this data.

[00:32:22.07] - Speaker 1
One second.

[00:32:27.01] - Speaker 1
So, first of all, this is the Excel file. This will be available for you guys on our blog and I'm going to show you where it's going to be. So we have our first tab, which is really just our full coverage. Here is what you see the assets. Here is all the calculation.

[00:32:44.22] - Speaker 1
Here is all the prices, the SKU score data, the swing trading levels. And then we have the different exercise where it's adding our option and momentum score, momentum and seasonality, and then option, momentum and seasonality. Right? So all this is available within our blog. So if you come to our financial wiki page, just click on Quant Strategies swing levels.

[00:33:10.22] - Speaker 1
And then here is the exercise that we did. This is available for all of you. I'm just gonna also copy the link. I'm gonna paste it in the comment here so you guys can can access. And basically within this document, you will also be able to download the file right here.

[00:33:30.00] - Speaker 1
And then it's going to show you the same exact data that I showed you before. Right.

[00:33:39.05] - Speaker 1
This is really. And I'm going to start answering questions in A second. This is really looking at how we can then integrate not only our Swing Trading model, which is already very powerful, but then how can we add value by adding other models like our Q Score and so on. We're going to spend more time on Q Score in a separate training session. But for today, let me know if you guys have any questions.

[00:34:04.14] - Speaker 1
The next step before we go into our Q A is really to understand how you can then use the Swing Trading levels within your chart and within your integration to potentially plan your roadmap. So here what you see is the data. So you see the levels here, but how can you then plot them into a chart? So what we did is we developed our Swing Trading model indicator. This is available for all our trading application for TradingView, Ninja Trader CR charts.

[00:34:34.09] - Speaker 1
So every application has access to this data. And what you can do is you can find the string level here. Once you become a subscriber, you can access the indicator there. And what the indicator does is really plotting the levels on the asset that you're looking for. So I can very quickly change from one stock to the other one.

[00:34:55.26] - Speaker 1
So I can go on Nvidia.

[00:35:00.15] - Speaker 1
And what the indicator is plotting is the five days swing levels. And then let's go into the settings a second. And what we plot is also the levels for the past five days. So what you see at the bottom is the, the five days level. So T minus 1 means the latest levels from yesterday, T minus 2 means the level from two days ago, T minus 3, the levels from three days ago, four days ago, five days ago, and so on.

[00:35:29.26] - Speaker 1
And the reason why is very important is because if we go back to our back testing, the level that we see today are going to be reliable for the next five days. So the goal is really to make sure that we can forecast how the price reacts. So the level for, for today will be available for the next five days. And that's why you see the different levels here on the chart within the settings of the indicator you can remove some of this. So if you don't want to see the levels from five days ago and from four days ago, you just want to see the recent levels, you can do that and this will disappear from the chart.

[00:36:08.29] - Speaker 1
And then, and then we can also look at other customizations. So you can, you can see here that we have a risk trigger from yesterday, two days ago and three days ago we have a lower band from yesterday. We have a lower band from three days ago and two days ago. And then you can combine those with our gamma levels. Right.

[00:36:30.07] - Speaker 1
And we can also use those to potentially create our trading roadmap. So the trading roadmap is also available on our string levels indicator. So very, very easy. You can change the ratio, you can hide the levels if you wanted to. So now we have our roadmap coming from our string levels together with our gamma level.

[00:36:54.16] - Speaker 1
So you immediately know that here we have not only our one day minimum, but we also have a very important level coming from our five days model. And you can always plug there. So understanding how these can become your levels for your roadmap is very, very important. For example, if the price in this case was to go up here, not only you have our Jackson level, but you also have our level coming from our swing trading model. In this case we have a risk trigger from two days ago.

[00:37:26.15] - Speaker 1
And then going back to the chart, you can actually come here and look at the success rate of the risk trigger. So you know that on 75 of the days, if we have a lower band, the price would close below the risk trigger on 75% of the days in the five days in the future. So here you have the swing volume. So whenever you see a price kind of reacting right here, you can use this level to create kind of like your, your roadmap. So very, very nice and easy.

[00:38:00.20] - Speaker 1
The next question that we get is, okay, so I'm trading futures, how can I plot the swing trading levels on my futures? And the answer is we don't have direct swing trading levels on futures, but you actually can convert the swing trading levels from an ETF or an index directly into the future. So what you see here, very, very simple within the indicator I can actually click here, I'm gonna convert SPX swing trading levels onto yes and I'm going to convert NDX swinterling levels onto nq. So let's go and see how that works. So I'm going to go here now, I'm going to go on es.

[00:38:47.14] - Speaker 1
And now what I see here again based on the settings is my SPX swing trading levels. We have our lower band, we have our upper band, our risk trigger. And again I can also build my roadmap like I did before, just sticking on the box there. I can also hide the levels and then I can also combine those with my gamma levels. So for example, very, very interesting.

[00:39:13.25] - Speaker 1
We have our core resistance here. We have our one day max, but we also have our stream trading level right there. So if you wanted to have an additional confirmation, you could actually use those levels as basically your confirmation there. We can do the same thing on nq.

[00:39:39.26] - Speaker 1
And what we have here is our NDX swing trading levels and then of course, plotted on nq. But you could also do something more advanced, which is really using swing trading levels from other assets to potentially plot them on your future trading level. So let's say that you wanted to, for example, plot Nvidia levels on nq. You want to see basically how Nvidia could potentially have a reaction on nq. So we can actually go back on nq and basically we can see where our swing trading levels for Nvidia are converted to our NQ price.

[00:40:23.13] - Speaker 1
The indicator is very flexible. You can do that on any other assets. You know, today we had, you know, Palantir reporting. We could convert that to nq, we could convert that to another. Another index and so on.

[00:40:41.20] - Speaker 1
All right, so I'm gonna pause here and I'm gonna open it up for any Q and A. So please let me know if you have any questions.

[00:40:56.17] - Speaker 1
So we have a question from Daniel. When you say it gives you a directional bias each day is. So I think we answered this. So the goal really is to forecast the price over the next five and 20 days. So if you go to the dashboard, we have two time window time horizons.

[00:41:15.13] - Speaker 1
We have five days and we have 20 days.

[00:41:25.11] - Speaker 1
Another good question. So you say for Iron Condors, so you can use both bands as wings. So I. Basically, the exercise that we did is just looking at credit spreads, not looking at Iron Condor. And the reason why we look only at put credit spreads or call credit spreads is because, again, the model is looking to forecast a directional bias.

[00:41:50.23] - Speaker 1
So you can come here. You can also see the success rate of the risk trigger. If we are in a strong directional bias, then it could happen that the risk trigger gets broken. So if you use the levels for Iron Condors, then you need to account a potential risk of the price to move up that direction. I hope it makes sense.

[00:42:21.29] - Speaker 1
Good question from Frank. Yes, Frank. So this is a great question. And we're going to go over Q scores also in two days, a couple of days. So is there a way to scan for Q scores for options plus momentum and seasonality in order to find bullish or bearish setups?

[00:42:43.04] - Speaker 1
So what you can do now is you can come to our screeners and you can actually look at our Q score screeners right there.

[00:43:05.05] - Speaker 1
Sorry, guys, just one second.

[00:43:09.14] - Speaker 1
All right, so here what we have is different screeners. So first we have the highest option score, the highest volatility score, momentum score, and seasonality. Or we have the lowest score. So let's say we want to start with our options score. What we can do is we can first filter the asset with the IS score.

[00:43:30.24] - Speaker 1
And then what you can also do, you can actually compare the different scores right here. So we don't have a way to combine the three together like I did. I did it separately using data, but you can actually start from one of the scores and then you can kind of see immediately if that score is also relevant at the momentum or seasonality score. So in this case, very interesting. So meta as a 5 option score, 5 momentum score and really positive seasonality.

[00:44:00.17] - Speaker 1
So you can use that data to kind of like analyze there or another very interesting one is the increase of score. So let's say that I want to see the highest option score increase compared to the previous day. You can also come here and screen for companies that saw an increase in option scores. In this case, for example, we have Gardner, we saw an increase compared to the previous day of 4. Now the option score is 5.

[00:44:29.08] - Speaker 1
Two days ago it was a 1. So something really happened yesterday. So you can also use this data to take a look at what's going on with Gardner, Roku, Moody's and so on.

[00:44:51.13] - Speaker 1
How can we do backtest like you did, playing with filters? So what I did is I did it in Excel. So I downloaded the data and I basically use the Excel filtering to filter out the different assets that match that criteria. Yeah, so very simple in Excel.

[00:45:28.05] - Speaker 1
All right, so just another piece of information. So now you can access our events directly from the dashboard and we are going to have another session on Thursday around Q Score and then of course stay tuned for our live at the end of the month with the with Champ, Carson and Ryan. This is going to be a very, very good one. So please set a reminder. Join us on YouTube.

[00:45:54.15] - Speaker 1
This will be live on the 22nd of August. Very, very interesting session that we're going to have about positioning. So stay tuned there and. And yeah, let me know guys if you have questions and we can go through them. But if you have anything and want to reach out to us, just send an email to info enter q.com and we'll be able to answer any question that you have.

[00:46:23.04] - Speaker 1
And the. And then we got another interesting question. Is the entire Excel available? Yes. So if you go.

[00:46:31.16] - Speaker 1
So if you have an account with us, you can create a free account and you can look at our. So if you go here, just go under Financial Wiki, click on Quant Strategies and then simply go under Swing levels right here. The first one that you see here is the document that I just showed you guys. And then at the bottom here you'll be able to download the data so you can access the file here. And then here is just looking at the assumption.

[00:47:08.02] - Speaker 1
But we also have a lot of different other backtesting that we did in the past. So just take a look at all these different backtesting on stream model. We also have different strategies. This is really looking at Q score and basically you can also access all the backtesting results there. Yeah.

[00:47:24.03] - Speaker 1
So just come to our guide section and everything is available and the file is also shared in the document.

[00:47:41.25] - Speaker 1
Right team? So yeah, thank you so much for joining us today. And then stay tuned for our next session on Thursday where we're going to talk about our Q Score. And if you have any questions or want more information, just send us an email, infoentorq.com and then of course you can find all this information on our website, mentorq. Com.

[00:48:02.19] - Speaker 1
So thank you very much for being with us today and see you guys again on Thursday.