Transcription
foreign [Music] hello and welcome back to another video. I'm Andrew, the CEO of Quant Theta, and in today's video, we're going to be going over netflow. So let's get right into it.
So we're going to talk about what netflow is, why you should use netflow, where you can access the netflow tool on the Quant Theta platform. We're going to show you how you can use netflow, and we're also going to go over three case studies of different real-world scenarios and how netflow can be applied in those scenarios. So let's get right into what is netflow.
So on the Quant Theta platform, the netflow tool is actually an area chart. An area chart is a graph that combines a line chart and a bar chart to depict quantities that are changing over time. The netflow tool tracks the put premium, the call premium, and the underlying ticker's last price over time. Right, an important thing to note about the netflow tool is that it actually dynamically updates in real time, allowing you to see these put and call spikes as they occur.
Below, we have a picture of the netflow tool on the Quant Theta platform. In this picture, you can see that the red activity represents the put premium, and the green activity represents the call premium. And in this particular situation, we're looking at SPY. So the blue line is going to represent up the last price for SPY. Additionally, the x-axis shows the market day across 15-minute intervals, and we actually have two y-axes. On the left-hand side, we have the premium, so we can see, you know, the call and put spikes for, in this situation, SPY. And then on the right-hand side, we have the reference price, which shows us simply the last price for, in this situation, SPY.
Let's go right into why you should use the netflow tool. So countless research studies have affirmed the price-predicting capability of options activity on the stock market. The information content of options activity is the outcome of the high leverage opportunities and minimized downside risk present in the options market. So basically, knowing that options information is valuable, we must create different tools that extract actionable insights from these information-rich options data feeds. And that's the exact reason why we created the netflow tool. We created it so that we can track all optionable tickers' real-time put and call activity. Now, by tracking every transaction in the US options market, we can see where the entire market, including smart money, is positioning live. We even account for your transactions in the netflow tool. So when you place a trade and it executes, that activity, our algorithm actually picks up that activity and includes it in the netflow chart.
This elevated put and call activity that we see allows investors to read the level of informed trading present in the options market. In the research paper, "The Information Content of Options Ratios," Blau and others investigate this price-predicting capability that the ratio between put and call activity shows us on the stock market in the short term. So the results of the study were astounding. It showed that the relational put and call activity contained price-predicting information in the short term.
So now that we've affirmed why the information present within the netflow tool should pique your interests, let's actually show you where on the Quant Theta platform you can access this tool. And then after that, we'll delve right into how you can actually use this tool and how you can, you know, understand the impact of the information that this tool shows you. So let's show you where you can access the netflow. You can access the netflow tool on the Quant Theta platform, which is accessible at quanttheta.us. Once you're logged into the platform and you've started your free seven-day trial, you can find the netflow tool on the chain and OI analysis page. So we're going to actually switch over to the Quant Theta platform real quick and show you where on the platform the tool is. And then after that, we're going to step right into how you can actually use the netflow tool.
So once you're logged into the Quant Theta platform, this is what you'll see. This is the main dashboard of the Quant Theta platform. You'll want to go ahead and navigate over to the left-hand side and click the second page titled "Chain and OI Analysis." Once you click this page, give it a second for all the data to load, and you'll see that we have our netflow tool here in the bottom right portion of the website. On the netflow tool, you can see we have the different user inputs here. We have the ticker that you're looking for, the expiration date if you want to filter by an expiration date, the money type, and then the session date. So you can look at historical data if you'd like. So this is how you access the netflow tool on the Quant Theta platform. We're going to switch back over to the slides, and we're going to talk about how you can use the netflow tool, and we're actually going to talk about three different case studies of the netflow tool in real-world scenarios. So let's go ahead and switch back over to the slides and let's get right into it.
So now that we understand why this tool is important and how we can access the tool, let's actually get into how we can use the tool, right? So one thing to note is that when your put-to-call ratio increases for a particular ticker, it indicates fear in the underlying. Whereas when that ratio decreases, it indicates confidence in the underlying. Basically, what this means is that when call activity rises in relation to the put activity, we can expect increased confidence in the underlying ticker. Right, and when put activity rises in relation to call activity, we can expect increased fear. So with this in mind, we can actually utilize the abnormal put and call spikes on the netflow chart to identify when the market activity may have increased in fear or confidence.
So we're going to go over a few observations that I made while researching and analyzing the netflow data. So the first one is that spikes indicating reversal points are the most effective. For example, if we have a large call spike after a drop in price of the underlying, that's likely going to cause a reversal in the price of the underlying. In this sort of other side of this is if there's a large call spike as the underlying pushes, it's actually less informative than the contrarian scenario that I had just described. Basically, what this means is that if we get a spike that contradicts the underlying price action, that spike is likely going to show that there's possibly a group or an individual who may know something and is placing a large bet on that on that information that they may have. So when observing netflow, I realized that when you're looking at netflow, it's going to be more beneficial to look at these put and call spikes at reversal points.
And then the second observation is that filtering by moneyness type, specifically out-of-the-money, yields more significant results. And I'm not going to go into much detail about the reasoning behind this. The reasoning behind it has to do with the different transaction costs and the market structure and basically why traders might choose out-of-the-money options over in-the-money options and, you know, in the context of different volatility scenarios and whatnot. But basically, for us, the most important thing to realize here is that, at least through my observation, that analyzing the out-of-the-money activity is more beneficial than just looking at the overall activity.
The third observation that I made is that a significant spike in both calls and puts indicates increased volume, but it actually reduces our ability to observe and, you know, form a directional bias. Additionally, that particular scenario does not really significantly change our put-to-call ratio, making it not as important. If we get a put spike and then a corresponding call spike, and they're relatively the same size, the put-to-call ratio has not changed much, and therefore the fear or confidence indicated by by that particular ratio has also not changed.
So I actually have a case study that we're going to go over that explains sort of each of these observations in more detail and, you know, how they can be beneficial. But on the actual netflow tool, we have some filtering capability, right? We allow you to filter by any expiration date for the ticker you're looking at. So, you know, SPY, if you want to filter by next Friday's expiration date, you could select it here in the expiration date input box. Additionally, we allow you to filter by money type. We allow you to filter by out-of-the-money, in-the-money, or at-the-money. And then we also allow you to look at historical data as well. You can look at previous days where netflow may have been interesting to you, right? If you want to look at last Monday, you could look at the netflow activity for last Monday. And when you don't select the expiration date, money type, or session date, it defaults to show you all expiration dates, all money types, and it shows you the current or latest market session.
Now that we sort of, you know, understand how we can use netflow and some different things to keep in mind when observing netflow, let's actually go into three different real-world scenarios and let's, you know, let's break them down and sort of understand how netflow could have contributed to forming a directional bias. So the first case study that we have here is actually on Meta. And if you look here, we're displaying the out-of-the-money netflow for Meta on November 1st at 12:20. We can actually see the large call activity spike, and this call activity spike was over 8 million in premium. Subsequently, after this spike, the price of the underlying, which in this case is Meta, spiked and it spiked over three dollars before it leveled off and then came back down. Basically, throughout the entire day, we pretty much, you know, prior to the spike, we had dominant call-side activity, which, you know, if we think back to earlier, how I mentioned when the, you know, put-to-call ratio, when the call activity increases in relation to put ratio, it shows increased confidence. So in this particular situation, we had increased confidence, and we had this massive spike over 8 million premium, and then subsequently the price rise. Another thing to note in this situation is that this occurred after a period of consolidation in the morning, and then, you know, right around noon time, we had that spike in call activity and the subsequent increase in price. In this particular situation, there was no corresponding put spike, which contributed to our directional bias because it showed us that the call activity in this situation was dominant. That's the first case study right there. There's a few interesting pointers to look at here. Let's get, let's go ahead and step into the next case study.
So the second case study is on JP Morgan, which is ticker symbol JPM. We can see here that we are filtering for out-of-the-money activity, and that this data is for November 4th. We're looking at all expiration dates because we don't have an expiration date selected when we're looking at this data. We can see that at 11:26 a.m., we have this massive put spike here, and we can see that subsequently after this, we have this massive put spike. The price of JP Morgan decreases about two dollars before it rises again. So we have this nice downside push here. For 11:26 a.m., we can see that the call activity, in the call plot activity, we can see that the put activity was dominant throughout the morning, and then you can also see that the stock price of JP Morgan was actually increasing throughout this morning, right? And we can see the put spike pretty much came right at, right next to the peak of that push. So this goes back to the first observation that we talked about, which was that the spikes at reversal points are going to be more significant. So we had a push, and then we had a corresponding put spike, and we dropped. So that's just one thing to keep in mind. You want to look at those spikes at reversal points, at least that's what I observed, and that's what I have found to be beneficial. You know, this case study, it shows us a few things. It shows us that we have that spike at a reversal point that was indicative of the price potentially decreasing, and that's what ended up happening. Let's go ahead and move on to the next case study.
The next case study is actually on Apple, which is ticker symbol AAPL. You can see that we're filtering for out-of-the-money activity again because, as I mentioned in my observations, I found out-of-the-money activity to be more beneficial. And we're looking at the data for the session date of November 1st. So you can see on November 1st, we actually had a lot of call and put activity. You know, what this indicates to me is that we have a lot of indecision because we have a massive put spike here, followed by an even larger call spike here, followed by another call spike, two put spikes, a massive put spike, right? We just have all these different spikes. And basically, what this shows to me is there's no clear dominant put-to-call activity, as both the call and put spikes occur within minutes of each other. Especially this is especially prominent around 10:45, and we have this big put spike followed by the big call spike. This activity to me shows indecision. This particular situation is an example of how the ratio of puts to calls is not drastically changing, and therefore isn't really indicating an increase in confidence or fear. I wanted to include this example so that you had a full picture of netflow. Netflow, when we have these indecisive spikes like this, is likely indicating to us that we're going to potentially move sideways, and that's what occurred here. We moved sideways for pretty much the rest of the day. So it's just another thing to keep in mind. Remember, when you're analyzing netflow, to maybe take into consideration the observations that I discussed.
That's all for the case studies. Don't forget to look at the netflow article as well. There's some great information there. Also, all of the case studies are there with the description, so make sure you check that out. It'll be linked in the description. Thank you for watching the video. Don't forget to subscribe and like. Also, in the description, there will be a link to our community. Don't forget to join our community. It's completely free. If you ever have any questions, feel free to reach out. And obviously, don't forget to sign up for a free seven-day trial. That link will also be in the description. [Music] Thank you.