So thank you all for coming. My name is Ryan Wright. I'm the founder and CEO of VATDOT. VATDOT is the company behind a new open source project called Quine, and that's the topic of today's conversation. So streaming graphs, because we can't afford to query anymore. So very nice to meet you. The plan for the talk today, as I mentioned, is to introduce Quine, the world's first streaming graph, kind of like a graph database but meant for reactive systems, stream processing, and that data pipeline kind of world. So the talk today is going to start by kind of orienting us among some of the modern challenges that if you're building a stream processing system or a data pipeline and you're trying to do it in a reactive sort of way, these are the kinds of challenges that you're going to encounter that were some of the motivation behind Quine. We'll talk about where Quine fits in, how it works under the hood. I plan to give you a demo with some live coding so I can't wait to see what breaks there. And then hopefully we'll wrap up with some links and if we're lucky, have a few minutes for questions. So collect them as we go and please ask away when we get to the end. So that's the plan for the talk today. And let's take a look at the world real quick. We've got streaming data. And if you're just going to count streaming data and count how many times you see something that flows through that stream, that's not so hard. You can watch that stream and count how many things flow through and sort them and filter them and so on. But if you want to put those pieces together into something more informative and do complex event processing on your data stream, this starts to become a big challenge. So the goal is to take what's coming out of that stream, one record at a time, one event at a time, put them together in the right combination because when you have that combined set, it's more meaningful, it's more expressive, it tells you more. And that's the goal of what you're trying to find in the stream. It's built from many different events flowing through. So if you try to build a streaming pipeline to do that, pretty quickly, you're going to have to start building queues for where you store those events that are not ready to be completed as the whole object over on the right. So those queues of unmatched events have to go somewhere. They have to get collected, monitored, updated, expired out. So those queues of events are what hold on to each individual event until you've got the full set. So it's common to hold these in RAM, but this starts spiraling and spiraling because not only do you need queues for just the single events that are unmatched yet, but you also need queues for your partial results. If we're looking to build a three-event pattern, then you've got to stuff your two-item pairs somewhere so that when that third event comes, you can pull them back and combine them together. And then you've got to maintain those queues. The common approach for these things is to do it in RAM. So with as much memory as your machine has available, that turns into the size of time window that you can allow for holding onto these elements, these data records, and putting those pieces together. But when you run out of RAM, you have to expire them out so you can keep up with new things. And I guess we just didn't find matches for those couple pieces we were keeping track of so they get expired out. And if data arrives later on and it wasn't a part of the pieces there, well, that's just some data that we're going to lose. So time windows are sadly kind of the state of the art for stream processing and how you do matching and putting the pieces together for complex event processing. But they lead to lost results. So if you want to do better than time windows, you'll have to go the route of storing the stuff on disk. And so set up a key value store, save records in that key value store, fetch them back, pair them up. Same pattern, but now it's durable. And now you've got that second system to set up and orchestrate. That second system now means what started as this hopefully simple application turns into a complex collection of systems. And worse than that, the semantics of what you're trying to match, the shape of what that goal object is supposed to be, that defines the shape of your architecture. So if the team decides we need to match something a little richer, we need to add a field to this, well, you're going to have to rebuild your pipeline and maybe even redesign your architecture to support higher load, more queries, more read rights back and forth. Because if you try to use a relational store or something bigger for this, it'll never keep up with the volume in the stream. And so just putting these pieces together becomes, it's a simple problem that turns into this complex solution. And if you've ever built these in the real world, this is an architectural diagram for what they often look like in practice. These microservice architectures, they start off with lofty goals, and it's great that we can actually put them together. We can build them. It takes a while. It's a little tricky. But it is technically possible. We can do this. I've been a part of teams who've done this as well. Building these systems is the backbone of modern data infrastructure at a lot of different companies. It takes a small army to do it. But if you've ever run it, then you've probably also been a part of watching this go down in flames for some implicit expectation about how systems are going to deliver data and when it's going to be there and if it's fully consistent or not, because these are hard and they're error prone and they're really slow to build, but possible to scale and expensive in the long run. There's so many implicit expectations between the microservices that get built that if a couple people end up leaving the team, then you're probably better off just throwing it away, starting from scratch, building the next iteration of your data pipeline. But this is kind of the state of the art. So it's fine. That's the world we live in. Well eight years ago, this was the motivation for trying to do something better, something bigger. So we started the project now called Quine. Yeah, really eight years ago, I guess. It's currently run by the team at VatDot. We had major support from DARPA along the way for doing a lot of core research and development, applying it to some really hard cybersecurity problems for the Department of Defense. Quine is a streaming graph interpreter for complex event processing. Feels like a graph database, but it's a graph interpreter for high volume stream processing. And it gives you this ability to put those pieces together, like we showed in that first slide, to join items together to get expressive patterns out of your streaming data and then emit them into a stream in real time. It sits basically between two streams. So you plug it into a stream on one side and it builds the graph. Then we monitor that graph and stream out those results. There's lots of different options for connectors and kinds of streams that you can plug into from Kafka and Kinesis and SNS and SQS. You can do other things like server-scent events, web sockets, files, named pipes, and standard in and out. A lot of similar options for where data goes at the end. And in order to get over that bounded by memory problem, there's a stateful layer as well that is also configurable. Using plenty of other open source tools like Cassandra and RocksDB, that stateful layer provides the support, the structure for the graph that can persist over very long time periods, and be why we don't need to rely on time windows in RAM anymore. To use Quine is really this two-step process. First you just say, here's my streaming data, I'll plug it in there, and I'm going to define one database query for how to take that stream and build it into a little part of the graph. Quine then fits that together with other streams or other preexisting parts of the graph. They overlap, they connect, they build this rich expressive graph. And the second part of that is a second database query. In the Cypher language, you say, here's the pattern I want to find as a standing query. That standing query lives live in the system, in the graph. It pushes itself around through the graph. Every time that the incoming stream causes the graph to change in a way that means that query matches again, it streams a result out. So it's like live materialized views on that query built on a graph from an incoming stream and publishing results to an outgoing stream. The overall goal here is to take a high volume of data in and turn it into a smaller amount of high value data coming out. So why a graph? Well, we started with a graph because graphs are really everywhere. They are a very natural, rich way to express data. And at first, it feels like a graph is something different. That you have to have a certain kind of problem to need to use a graph. And graphs are slow, so we can't really use them in production. But in truth, what we found over the last eight years of R&D is that graphs don't have to be slow. They can actually be profoundly fast and be the key to actually scaling the expressivity of data structures that we want to find. So a graph gives us this flexible structure that we can represent anything, including everything else that you'd put in a relational table or a document store like MongoDB. That same kind of data fits very naturally into nodes connected by edges in a graph. The graph data model is as flexible as the human language. Whatever you could express in English, you could also represent directly in a graph. That subject predicate object pattern that shows up in the English language is exactly equivalent to this node edge node pattern in the underlying graph. So anything that you could say in words, you can express as data and compute over it in a graph. What's novel about Quine is under the hood, it is backed by the actor model implemented on top of Acca. Those nodes in the graph get backed by actors. And so the graph data model is paired with a graph computational model. And that's really where Quine veers off the beaten path. To my knowledge, nobody had ever done this before. That independent, scalable, asynchronous, event-driven, message-passing architecture is what's behind the data that we represent in a graph. What that means for each node and how a graph gets built is we take the whole connected graph, whether it's running on one machine or spread across a whole cluster, and we cut the graph up on the edges. So we do what's called edge cut and represent one edge with two half edges that point at each other. So from the perspective of one node, there is an edge connecting it to another node if that node has an outgoing edge of a certain name and type and direction. And the other node has a reciprocal incoming edge of the same name type and direction.  Each node itself holds onto properties that are basically just key value pairs to represent the data. And that gives us the structure of a graph that we can chop up as needed, implement as a collection of actors spread across maybe a large distributed system. And each of those actors can then take action and trigger its own action, do its own computation. That becomes the building blocks for all sorts of crazy ideas. So from there, we said, well, what if we built this graph instead of in the normal way where you start with an empty system and you have to create nodes along the way, but before you can create them, you have to check and make sure node A is there before node B has an edge created to it. Your nodes have to exist first, then you create the edges. Instead of taking that traditional approach, what if we came at it from the perspective of saying, what if we just assume all nodes exist? Every node that you could ever conceive of just exists already in the graph. What if we design the system with that as the foundation instead of saying, well, a database begins empty, so let's start empty. Well, it turns out it gives us some advantages. We can avoid the operations for creating nodes and deleting nodes and instead just focus on individual instructions to an actor that say, add this property or edge, remove this property or edge. If you want to delete a node, remove all the edges. Because if you have a picture like on the right where there's a whole bunch of extra nodes in the conceptual graph that you're trying to work with here, those extra nodes don't matter for queries. They don't contribute to the result. We're still going to find our ABCD pattern in exactly the same way. We just have these extra nodes in there. So why would we do that? That gives us some really powerful primitives for working with streaming data, saving it and loading it and all of this. Because under the hood, each node in the graph saves its data using the reactive technique of event sourcing. So a node in the graph receives an instruction to set a property, to add an edge, to do something to change its state. And it materializes the result of that change in memory. But what gets saved on disk is actually just the change. So that change is added to an append-only log. The next time there's another change, it's added to that log and so on and so on. Whenever we don't need that node in memory anymore, we can expire out the in-memory side, let the changes on disks stay persistent. And if we need that node again to participate in a query, we wake that node up by replaying its history. And all nodes exist. But it doesn't mean we have an interesting history for every node. So any node that exists, but hasn't been referred to before, is just an empty list for its history. So there's nothing to replay, no interesting history to talk about, and the node begins in what is effectively an empty state. But we didn't have to create it. And that gives us a lot of advantages for stream processing and the out-of-order data problems that arise when working with streaming events. And this event sourcing approach also gives us a durable persistence model that is extremely fast for the right heavy load that we have in stream processing.  We've got a small little change that gets computed in memory. That change gets appended to disk. We can do that very quickly. We can do that very quickly in parallel. And since all these changes go through the same node, that order of that log for that node is perfectly ordered. And it gives us the ordered history through time of the changes to that node. So we can even go back and query how that data used to be back at some historical point and say, give me the answer to my Cypher query right now, and then here's a timestamp. Tell me what the answer was 10 minutes ago, 20 minutes ago. So I mentioned before standing queries are how we get streaming events out of the graph. A standing query is just an ordinary Cypher graph query, just written in the Cypher language. But when you issue that query as a standing query, it gets dropped into the graph and stays alive, stays resident in the graph, pushes itself around through the nodes in the graph. As the graph changes, the events that cause the graph to change also cause the standing query to test and say, do I match my sub portion of this query? If so, relay the next portion to the next node. Each node is an actor. It can do arbitrary computation whenever it receives an event. So it receives a query AST saying, continue this query. So in that way, standing queries remain live in the graph, push themselves through and find patterns somewhat automatically, or behind the scenes autonomously. So whenever we've got the full structure, enough data has streamed in to create a new match, that match gets detected and can trigger any action, including publishing results out to the next system, the next service, or downstream service, or it can even call back into the graph and perform other operations to update nodes or to query for extra data. I'll show you an example of this. So if I drop out of slide presentation and flip over here, hopefully this is legible enough from where you are. This is the Quine open-source website, so you can go to coin.io and check it out if you're interested. There's download links and everything there. If you download the jar file from this download page right here, then you could even follow along and do exactly what I'm going to do here. I'll show a link in just a moment for all the resources and everything that I'm going to show. So using Quine, I have real quick set up a Kafka server just locally on my laptop because conference Wi-Fi, you never know. So Kafka is running here on my local laptop. It's preloaded with a little data to help show this demonstration here. So using Quine is really just a matter of calling Java-jar, passing in my Quine fatjar here. And then I'm going to say dash R for something called recipes, and I'm going to feed it my reactive 22 YAML file as a recipe. So on the Quine website, there's a collection of recipes that have been built by the community around Quine, just demonstrating the configuration and everything needed for different kinds of use cases. So if you want to go try one of these out, it's really just a simple matter of picking a recipe and running the command with the appropriate name after dash R. In this case, I'm going to run a local YAML file as my recipe, and so it's called reactive 22. Let's just run it and see what happens. This is what my recipe looks like. It's pretty empty. There's not much here. This is the minimum template for a recipe. It does have some stuff in these last couple fields. It's just cosmetics, trust me on that. The real meat of this example is going to be in lines four and six as we fill those in, because that's the two parts that I mentioned. Streaming data coming in to build the graph, that's in just streams, and then standing queries monitor the graph to find graph structure, and then trigger action to send it out. So I started this empty recipe, and it started at the command line, and it did nothing interesting. So that's exactly what I'd expect. Let's kill it and do something interesting. So I'm going to edit this recipe and make the simplest possible ingest stream here. So this is a Kafka ingest from localhost 9092. I'm going to run this a couple of times, so we're going to start from the beginning of the topic each time, and the name of my topic is Endpoint, because this example is a cybersecurity example. It consumes data from two different kinds of sources. Endpoint data, and I'll show you one for network data as well. But when we pull those two sources together, we can find some really powerful patterns that indicate a bad guy doing something under the hood in the data. That's our goal to see here. But this is technically all it takes to build an ingest stream, so let's just run that and see what happens. So I'm just going to run the same recipe again now that I've saved it. All right, it started up. It's ingesting. As you see down there, there's a counter going up, and I'm going to go to localhost. This is what the Quine UI looks like. There we go. We've got some data. Technically, this is a graph. It's not a very interesting graph because there's no edges, nothing's connected. This would be a waste of time if you actually tried to build a graph just to hold some JSON objects like this. But you can see there's key-value pairs in there. There's an event type, object. This apparently represents a process. There's a process ID on it, a timestamp, some information like that. Cool, we've got some JSON data that was just come in each JSON object saved as a node in the graph. Technically works, not very interesting. So shut that down and let's do something more interesting. I'm going to add a specific ingest query. So this simple definition just used the default ingest query of taking every object and making it into a node. So if we add a little more to it, I'm going to say this is a Cypher JSON query and here's the Cypher query that actually takes that record and builds some graph structure. I'm going to take one JSON object and build three nodes out of it. It's a process, an event, and an object. And what's unique about Quine is Quine is very fast for streaming use cases if you know the ID of a node. If you have to go look it up and scan every node that ever exists, it's going to be incredibly slow. So Quine has some built-in tools like this ID from function. ID from is basically just a consistent hashing kind of a technique that takes in any number of arguments and hashes them into the ID of a node. And so if I take my incoming data, here it's represented as $ that. So this is one record we're reading out of Kafka and I can read a field off of that. I'm going to use the process ID in this case and I'm going to generate a node ID using ID from just by passing in the process ID. And so that's the constraint on my ingest query. So match these three nodes, pull them out of the soup of all nodes that exist, but constrain this incoming reference to the process to the specific ID created by hashing that process ID. That gives us a specific node ID. Down here we can set a few properties on that node. And the last line is just creating some graph structure, some edges. If I save that I can run it again. There we go. We're ingesting. Let's reload and take a look. I'm going to use the cipher command to call recent nodes. And we start seeing some more interesting things here. Oops. It's more here than I actually want to look at. But take for example this thing node pattern. That's what we're creating right in the middle. This is an incoming process. It has an event that is reading a file. This is sample data meant to simulate real endpoint information, but it's based on a true story. So in this case, that is one record, one incoming JSON that we just pulled apart some fields and created some graph structure to present that. The reason we would want to do that is because there's other connections that occur. So as we refer to the same node using the same values in our ID from case, we build some other interesting graph structure and we can see this process in the center here did a lot of things. In this case it read and wrote to this one particular file. And that file was also read and written from some other processes so you can start to see the graph structure materializing from the data that is streaming into the system. All right, so we built our ingest stream to construct a graph just to make it a little more interesting. I'm going to do a second ingest stream. It's going to work a whole lot like the first one, but this time we have network data coming in. That network data is also going to be built into a three node pattern and it's going to work essentially the same way. But the fun part is then we get into standing queries. I want to watch the graph that's being built for a certain kind of pattern and every time that pattern exists I'm going to define outputs. These outputs take a match and trigger some action based on that. I'm going to show you pictures of what this looks like because it's a little easier to glance at when we actually see the diagrams. But I'll show you the pattern that this is defining here to find. Every time it finds a pattern it's going to go make another Cypher query to fetch some extra data take that data and package it up in a new event that we're going to write out to Kafka. So we're going to watch for a complex pattern every time we find it we're going to fetch some additional data formatted into a Kafka event and publish it out to Kafka. So let's save that. Let's close that and run it again. Now down here in the corner I've got a Kafka consumer running just command line consumer watching for the place we're publishing which is this results topic. So you can see data is ingesting, it's streaming in and this is the UI is really meant for visualization purposes and inspecting small graphs but behind the scenes Quine can scale to run in a clustered environment and handle huge volumes of data streaming through behind the scenes it's building a graph it's monitoring that graph and if it finds a record there we go I saw something happen in the background our event got published to Kafka the consumer picked it up this is what that event looks like it has metadata in here about the result and it has the actual payload of the data result I was publishing out a URL let's take that URL if I open a new tab pasted in the URL it formatted a query as part of that payload that pointed me to exactly the point in this data that was the pattern I was trying to watch for so the pattern that we set as a standing query is looking for this pretty complex graph structure so this is a case where a process had a write event pointing it at some file and that file was actually a covert communications channel behind the scenes for another process called NT Clean to read that file and then delete it later but first it's going to send some data out to a specific IP address so we were watching in the stream the stream was building each of these nodes one at a time incrementally building the graph monitoring for this complex pattern here once we found it it collected the data, published it out as a URL that we could just click on to a browser and see the details of what we're looking at now if I were a cybersecurity analyst I could go further, I could say well here's Excel what files was it reading let me right click and choose the right thing what files were read well it read a spreadsheet that spreadsheet probably had a malicious macro in it and it turns out it also then read this private plans document so we can start to see what's happening here well where's this NT process NT Clean process come from well this was started by whoops there we go so it had a spawn event connected to an SSH process that SSH process itself received data on a local IP import that IP import had some external communication from the same IP address where it ended up sending data out to and so in the Quine UI we can bake in some of these right click exploration kinds of functionality to go explore this particular use case different use cases can support different functionality but in this case the event triggered found the critical result that communicated what we wanted and a human could come back in and explore more later on so that's an example of using Quine connected into Kafka to consume data, build a graph monitor the graph for complex patterns every time one of those patterns is found send a downstream event so that you don't have to build oodles of infrastructure and microservices just to do that complex event processing so with that I want to wrap up with a pointer to this URL Quine.io is the open source website you can go check out the code there's links to GitHub on there if you'd love to try it out there's a community to help answer questions and get started as I mentioned there's recipes to demonstrate different use cases and show how to get started this is supported by the team at that dot if this is your thing we are hiring right now so if you want to come work on this kind of stuff we'd love to talk to you but also Quine.io.demo is another demo that you can see of a different application but if you'd like to try and run everything I showed here check out Quine.io slash reactive22 you'll find the slides the files I was using the sample files all of that so that you could run this and try it out yourself thank you very much if you have questions we are out of time but I would love to hang around and take your questions if we did so catch me afterwards thank you very much for your time and attention


Ten, nine, eight, seven, faster. Six, five, four, three, slow it down. Two, one. Ladies and gentlemen, boys and girls, you will see right here, I'm filming this. The ball that wins the board eight. This is a $200,000 approximate prize. Now let's go. The winner is B12, which is Yapster 99. Where's Yapster? Yapster. Yapster, where do you, what country are you in? I'm in the USA, I'm in Arizona. Arizona! Now Yapster, we're not done because we're going to transfer it to you on the blockchain right now. You're about to see a board eight just pop in here. How cool is that? Oh, dude! Oh! Dude! If I could, I would say thank you.


96, obviously, that goal with Gaza they probably voted. I don't know if it's right. We're great interview, thank you. How was it with the two years after that? No bro, I've rather polled scored that goal than any other Englishman. Polled is the only man that could score that goal. I'm just glad I'm in history at Wembyd because I voted the best goal ever. Rightly so, but we missed 45 seconds before that.  I was six inches out of position, fact. And I'm looking back thinking I'm just six inches out of position in its costars. I was raging. They've won the game, blah blah, and as I'm coming off when that I've seen Gazz walking over I'm thinking, I'm worse than anybody in training.   I've seen Paul coming over it, and I've looked at him. He's obviously coming at a big dab smile, he's got his new teeth, and all that, I'm looking at him.  I just looked at him, he's clocked it, turned away and walked off. After the game, we're in the bar, and we spoke for about half an hour, we had a good couple of drinks. He never mentioned it. I'm like, I've got a way with this one, right? Normally I'd be getting, I'll eat it. Never mentioned it, so my first day in training, the scene after Ibrox adresions, massive adresions. I'm walking in, I can hear a commotion in the adresions. What's going on in here? I've opened the door. Gazz has got two big police cones at the end of the training, at the end of the adresions, there's goals. There's a beach ball in the middle of the goal, which was me. There's a wee cone with a mop head sticking out of it lying on its side, which was Colin Henry. And then I walked in, Gazz has flicked over the mop head, smashed it past the beach ball. I went, is that where it was? But then he went and laid down, and the coach was squatting water in his mouth. They'd set it all up for me, so I've got for it when I get back. I said, I'd rather him score that goal than anybody else, but there's only him capable. That's a clash, man. That's a clash, but later I see it. It's really annoying, but it's even in your scores, and they planned all that. He's actually thinking about what's going on here, he says. The confidence in him, and the level he's at, I'm going to score here and see what I do.  They planned it, the celebration, which means for me, he's thinking, I'm just going against this lot. Especially when he's playing in Scotland. I just showed you the confidence he had.


in three, two, one. All right, guys, okay, we are live, okay? But just wanna make sure if you guys can hear us, okay? Can you type V in the chat, okay? V stands for victory because today it's a really a victory night for me. I think I finally managed to able to have, you know, most of the time it's me doing it by myself or sometimes I managed to invite Pete up but today on top of being able to invite Pete I also managed interview another professional fund manager all the way from the U.S. So today will be a lot of insights exchange by Pete himself as well as by one of the very, very great fund managers that I managed to meet in Omaha when we actually went to Berkshire AGM this year. So I can see people are tuning in. I can see IC is here. Hi, good to see you, IC, all right? So without further ado, without further ado, I'm going to officially invite the key owner speaker tonight and he is none other than Matthew Peterson. Hi, Matthew, good to see you. Hi, Matthew. Nice to see you, Chloe and Pete. It's very nice to be here. Yeah, it's been so, it's been like about one month, right? Since we last met. Wow, it's been one month already. Yeah, one month ago, I guess we were in Omaha, right? Yes, fantastic. And that was the first time I met you actually. That's right. It was very nice. I want to see some context to our audience, like how we met is because when Pete and I went to Omaha, we were just thinking about what events to go to. There's so many like additional party, of additional networking events that you can go. And we went to the barbecue, which actually organized by Matthew himself and he has been doing that for past four years. Every single year he's there, he organizes parties so that people who are like-minded, they can gather to talk about investing to network. I think this is one of the best party I've ever been. So thank you so much, Peter, for organizing this. You're very welcome, Chloe. Thank you for coming. And because of that, I get to understand that Matthew himself, he is a professional fund manager. And that's why tonight, I also want to really delve deeper into your investment philosophy because your fund has been performing so well for the past 10, 11 years, right? The analyzed return is like 14% year on year. So like if the investor invested $1 million back then, now their portfolio will have become, I think close to a form $4.5 million or more in terms of the fund size. So I think that is really tremendous work being done there. So we want to tap into your insights as well. Yeah, Peter. All right, so I can see some of our followers are here as well. Hi, Jeffrey. Good to see you and Sebastian. Now, before we get started, maybe I get Matthew to introduce a little bit more about your work. What made you started, like how did you get into this, becoming a fund manager right now? Yeah, I can provide a bit of background. So I run Peterson Capital Management in the United States. We actually have a Turkish fund as well, called Palace Capital. And I spent, well, I studied economics and math and I always had this intention of running a fund. So I needed to put the building blocks in place. And after my undergraduate degree, I went out to Wall Street and I managed to secure job consulting for investment banks. And I spent many years with Goldman Sachs working in the risk management department, doing all sorts of things from credit risk management to market risk management, working with a number of different entities. And I spent time both on Wall Street and also in London. I was in London for two years during that stretch of time. And I earned my CFA designation and was, as I said, putting these building blocks in place. And in 2010, I left that role and we launched Peterson Capital Management. And so we opened that up to outside investors in 2011. And here we are in 2023. So we are about 11 and a half years into the fund. And we've done very well. We're very pleased with the progress and the firm is growing, the fund is growing. It's been quite a journey and it's been a great journey. Yeah, and maybe I just show our audience the slides, the information that you actually shared with me, which I think it was really, really amazing. Hold on, where is the PowerPoint? Okay, this is the... In fact, you guys can also get this PowerPoint from the Metropolitan Capital Management website as well. So you can see that in terms of the fund performance has been really consistent. And in fact, this will be one of the question I'm gonna ask you tonight, which is what is the secret sauce behind how you manage this fund that has been able to generate such a consistent return? Well, Chloe, it's a good question. I'm gonna almost... I don't know if it's a positive thing here, but I will argue with you that it's not very consistent. In fact, we're quite volatile. And that's part of the secret sauce. I mean, we have a very concentrated portfolio. We hold the very best companies in the world we're looking for the greatest business models. It's a value-based fund. So we're looking to pay an extremely low price for the companies that we're buying. We're very patient in that manner. And we also run a very concentrated portfolio. So with sort of seven core holdings, we are making this progress and we hold them through volatility. So one of the things we notice, look, we're all over the world. I'm over here in Istanbul right now. And it's quite interesting to see the dynamic in different cultures and how people invest. So to put it in perspective, in addition to Peterson, which you just showed, we have Talus Capital. Talus is solely invested in Turkish equities. And by the way, these securities trade for currently like PEs of two and three. I mean, just like an amazing opportunities. And basically when we are looking at these types of firms, we're doing, we're meeting with the exchanges and things and we're learning like the foreign investors here in Istanbul, for example, are investing maybe for 180 to 270 days on average. That's an average holding period. And they're making some positive returns. We are much longer holders than that, but that is the average for the foreign portfolios. Sorry, for foreign investors, but for local investors, their average holding period is like three days and they're on average money. So it's about how the mentality is behind these markets. So we are really long-term owners of these businesses. So with the, I see you've put these down there. There's information on petersandfunds.com. If anybody wants to look at those charts you were showing. We talk about the positions we hold and we do a lot of deep research, but then we hold them for many years. In fact, we would love an opportunity to own them forever. So some of the things we've talked about in the past is like our daily journal position and others. This is like, maybe we've been holding it for five years. We'll probably hold it for many decades, many, many decades. And this is the secret sauce. The business itself is growing and we ignore the stock price. The price will follow and as the business grows, eventually the market reflects the value of the business. And so we simply hold and watch the business grow and we're business analysts and business owners. And as the price fluctuates, it doesn't bother us, it doesn't concern us, it doesn't concern our partners because we've educated them on this. And so you say, how do you achieve this consistent growth? But key, there are stretches where it's flat and volatile and there's other stretches where we jump forward. So we don't have control over the price. Nobody has control over the price in the short term. So we're looking for excellent businesses that we can buy at a really great discount with extraordinary managers. And this is the secret sauce. This is the approach that we take to building out an extraordinary portfolio. I see. Maybe Pete, do you have anything that you want to add? Yeah, so Matthew, actually I was very curious about your fund in Turkey, because of all the places, right? And right now, Turkey seems to have a bad name in terms of the economic stability and the inflation that's running quite rampant over there. So what in Turkish market that caught your eye? Okay, well, I have several ties to the Turkish market, but so my wife is from Turkey and I've been coming to Turkey for many years. I think the first time I came here was about 17 or 18 years ago now. And I've spent a lot of my adult life here. I mean, I spend about probably an aggregate a month or five or six weeks, probably of each year. And so what originally caught my eye is I was out in, it was really opportunistic. I was in Switzerland. I'd been running my fund for a number of years and I was in Switzerland visiting Guy Spear at the ValueX conference. And I've been a long-term attendee of that conference. And through Guy, I was introduced to Mesut Eliotolu, who's like the best equity analyst, Turkish equity analyst globally. He was Chief Investment Officer of ABN Amro for many years. He's an extraordinary individual with just such deep understanding of these firms. And it's a small market, all right? It's a little bit, it's not like being in the US. It's maybe more like being in Singapore. There are truly only a few hundred companies that are publicly traded and the prices are not as efficient. So the market's not as efficient, meaning there's inefficiencies in the market and the prices are wrong. And the prices can be wrong in the short-term, but in the long-term, eventually the prices match the value. And so with Mesut's deep understanding, we just became friends for a few years. I would come to Turkey, we would visit each other and we ended up, he proposed and we ended up launching TALIS Capital. And so that was about five years ago. We have very similar mindsets. We are truly business owners. In fact, so what's attractive is it's very difficult to resist things that are trading for two and three times earnings. For me, I just, I can't believe the opportunities. We can buy the Coca-Cola bottling company in Turkey for five times earnings and everywhere else in the world is selling for 20 times earnings. And here there's much less consumption and a growing consumption of these sugary beverages and things that they're selling. So there's actually a lot more growth in this region and the price is much cheaper in this region. So there are so many issues that you mentioned, as you mentioned, Pete, we've just had an election here in Turkey, Erdogan won the election again. And in the past, there's been some very controversial, controversial is maybe, so there's been some really unconventional economic policy where there's massive inflation but also lowering interest rates, which in economics 101, you understand that. Doesn't go hand in hand here. It doesn't work well. But now that this election has passed, our anticipation is that this, the administration will now try to stabilize the currency. In fact, there's some new folks in the treasury, they've put together a three-year plan. As inflation does stabilize, I think people will realize these firms are truly just gushing with cash. They're, you need the right firms. You can't just buy the Istanbul index or the Turkish index. Yeah, it's very hard to buy. The old banks. Yeah, it's not the right time necessarily to be buying all the financial institutions. What you wanna be looking for and what we have looked for are firms that are earning revenue in hard currency. Things like, we have this company, we own Archelik. Okay, Archelik is a manufacturer of all sorts of different household goods from air conditioning units to dishwashers and they have manufacturing facilities, but they export all over Europe in many other countries in fact. And so their revenue is coming from exports. So it's actually increasing as there's inflation in like a Lyra perspective, but their costs are declining. Any debt on these companies books based in Lyra is declining. So inflation isn't always a terrible thing if you know how to use it. If you have your costs in an inflating currency and revenue in a stable currency, in a stable currency, you find these really unique scenarios. And I think it's so much well known that Turkey right now is among or maybe the cheapest market in the world. It is filled with these companies trading for two and three times earnings that are really great firms, many of them operating internationally on a global level. And Zorlu Energy is another where, oil prices have a global price. The Lyra can depreciate, but their production price keeps a value. It's coming in dollar based barrels of oil. So actually the inflation does not impact the revenue. It only impacts the cost. So the firms are absolutely, it's quite remarkable when we look at the data and Masut and I've been discussing this for like 70 hours straight. It's just remarkable what's happened, how much revenue is coming in, how large the margins are and the costs are shrinking very quickly. And for some of your viewers, they may not realize the significance of the inflation, but 17 years ago, actually, sorry, 12 years ago, 12 years ago, it was about 1.3 Lyra per dollar. And there was a big event about 15 years ago. It was a million Lyra per dollar. It didn't start that way, but there was a million Lyra per dollar. And then what they did is they printed new currency and they erased all the zeros. And then they made it one to one or 1.3 to one. Today it is 23 to one. So in 12 years, the Lyra has fallen by 95%. And that means companies with costs in Lyra have fallen, their costs have fallen 95%. So if you can keep your revenue growing and stable in foreign income and your costs depreciate, you have a very, very unique and special opportunity. And so the prices can rise considerably. It will take a little bit of, I think foreign investors need to recognize the opportunities first because the local investors speculate a little too frequently. We're well aware of the gambling mentality that's taking place. Other than that, when that occurs and it can occur quickly because there are, the election is now over. As foreign investors come back in, I think the markets are like maybe 80% undervalued. It's so inexpensive here, it's remarkable. It's a great opportunity. Wow, I think that's really amazing insights that we will not be able to get from Singapore. Thanks so much for sharing. And you can see that for Matthew, even though when they are investing in a country like Turkey, they are still finding great businesses that have very consistent, in fact, growing revenue at the same time controlling the cost. And in fact, it's still predictable business which is what Buffett has been practicing all his investment journey. And that's how he built his riches as well. And that's what in fact, Matthew Peterson has been doing for his fund to grow for his clients. But I'm also very curious about if we go back to the talking about concentration, right? Because a lot of time, we know that a concentrated portfolio also carries some form of risk, right? In terms of there will be a lot more volatility as compared to a diversified portfolio. So in your opinion, how do you manage this risk? Like what gives you the confidence of concentrating on your portfolio so much? Yeah, I will share with you a few insights that I think are very useful for many investors. Most investors, unfortunately, most investors are educated incorrectly about the value of diversification. Diversification is a really good way to underperform the market. You sort of avoid maybe some price fluctuations to some degree, but if you buy a number, basically, let me take a step back and share this. There's a, if you look at the Kelly criterion, and you look into the Kelly criterion, I actually re-derived the Kelly criterion about seven or eight years ago for presentation I was doing, actually for myself, and then I presented it. What happened was John Kelly originally was trying to figure out some aspects and technological reasons, doing this for technological reasons with AT&T, and he recognized in the Kelly criterion that it worked very well in places like Vegas. And what it basically says is, if you have a fixed pool of capital and you are allocating capital to an opportunity and you know the probability of success and you know the outcome if you're right, and then if you know the probability of failure and you know the outcome if you're wrong, then there's no longer a subjective allocation. There's a very objective maximization that you can put. And so if you come from that perspective and you look at it, the challenge is that you still don't know the probability of being right and you don't know the probability of being wrong and you don't know the outcome always when you're right or the outcome when you're wrong. But when John Kelly was creating the Kelly criterion in I think the 1940s, he was using punch card systems and really old technology. So I just opened Excel because I knew the concept, the idea, but I just wanted to see for myself. So I opened Excel and I just used the formula and I solved for every outcome. What happens if you're never right or always right and what happens if you make 100 times your money when you're right or what happens if you lose your money when you're right? Because you know, you can be right as any Duke, any Duke's professional poker player. The outcome isn't always indicative of the quality of the decision. You know, you can make a very good decision and still have a poor outcome. You can even make a bad decision and have a good outcome. Yeah, pure luck. That's right. You have luck does play some role in this. So you need to evaluate kind of the process, the decision making process rather than the outcome. So when I did this with the Kelly criterion, you can just solve for everything. And when you kind of narrow it down to something that's realistic, maybe you're right half the time. And Warren Buffett, you might know, has said that one out of three of his investments is his mistake. So maybe you're not right more than Buffett. Maybe you're not right more than 65% of the time. So now you should be right like at least half if you're an investor, a professional investor. But maybe you can't count on being correct or having always a good outcome. When you solve for this, you see very quickly that the profit maximizing outcome, the greatest compounded return is somewhere between two and 10 positions in your holding. When you find a holding that says, if you find that you maybe have a 55% possibly being correct and if you're right, you'll make 50% on your money. The Kelly criterion will tell you to allocate something like 25% of your whole net worth to that opportunity. And what happens in risk management that I think many people fail to grasp is that as you introduce new businesses beyond the 10th or 12th or 15th, you are no longer eliminating the non-systematic risk from your portfolio. What you're doing is you're introducing lower returns to your averages. So you've done a lot of the possible diversification with five, six, seven holdings. And when you get into 15, now you should be able to say, my 15th best idea is worse than my first idea my best idea. So skip the 15th and put more money in the first because you don't get diversification benefits. You do lower your return. So optimizing your concentration to me, it feels like we're very diversified. It feels like, so Tallis, we have 12 positions. Peterson, we have seven or eight positions. That feels very comfortable for me. And I think that's optimal. So we are like managing risk very optimally. And then we get higher returns. You can get higher returns if you go bottom up, find individual securities with great returns on capital, the ability to reinvest. Ultimately, what we sort of, we look for the greatest business models in the world, the greatest management teams in the world, and then really, really great prices. And if you have those three, it's so hard to find, you can't find 25 companies like this that are cheap, great managers with great business models. So you have to concentrate. And that's what allows you to outperform. Yeah, Pete, you wanna say anything? Actually, that was a great transition to my next question actually, Matthew, because other than learning from Matthew about what he holds in the portfolio, very importantly, I always find interesting and also important to understand why people sell their position. So Matthew, I noticed that recently in your latest annual report is that you're actually sold Bank of America, right? Which is actually also a position that Buffett holds, Berkshire Hathaway holds to a huge proportion as well, right? So maybe can you share a bit more about and on that decision and also maybe your outlook on the financial sector as well? Because in Singapore, financial is a huge thing. We have four main banks and pretty much I think everybody has some money in those banks. Yes. So it's, our portfolio is quite unique and you're asked, so ideally we don't sell, Pete. Ideally we hold, by holding in the US, we postpone any tax liability in a way you get what Buffett would call float, you get to reinvest the money that would have been paid for taxes. So we are typically not sellers of these business, but as, look, we've been running Peterson funds for 12 years. We've always had this long-term mindset, but we are always evolving, we are always improving. And there are investments in the past that I realize that I wouldn't make today because what we're really looking for are opportunities to make like 100X on our investments. And a lot of times it will take many years. We're not just speculating on something that's like a commodity is going to go up or cost more or something. We're really looking at firms that will compound and are underpriced and maybe if something's 50% underpriced but it's growing by 50% a year, there might be a lot of opportunities. So when we look at, you know, you ask why do we sell Bank of America?  Well, you mentioned it's already owned by Berkshire Hathaway, which is totally true. And you also may not know that it's a big part of daily journal. So in a way, it's a redundant holding. Okay, so we had an opportunity that was a little more short-term than is typical. The opportunity was that, and maybe we'll talk about this a little bit. I'm not sure how familiar you are with our use of what we call structured value where we use puts as a tool to buy the stock. So we use puts to buy, which is very different, almost inverted from what most people think. They think calls are to buy and puts are to sell. We use our puts to buy. When the US went through the financial crisis, the global financial crisis and we had all these bailouts, there were special products that were created by the US Treasury like our tarp warrants. And tarp warrants were essentially tenure call options. But because they were so unique and misunderstood, the prices were everywhere, the prices were very wrong. And what we were able to do at one point is just buy Bank of America for basically below book value. And the bank was stabilized and growing and Buffett had already made a $5 million investment. And we were able to get a very, very attractive price on something that had some really asymmetric capability. So by the time the shares came to us, our expectations of the growth in Bank of America were not really as high as our expectations for the product that we were using for I guess our holding period was probably five or six years, which for us is very short. So once we had the shares, the growth wasn't there, it didn't necessarily belong in our portfolio for the long term. What we're looking for are things, oftentimes they're on the smaller side when we can find them. And so really the reason we exited is it's a redundant position for us because it's embedded in the others and it doesn't have the same growth potential over the long term as some of the others. So those are a couple of reasons. It's the opportunity cost of capital is very important in finance. So if you do A, you cannot do B. And so we have to be very selective with the companies that we are owning. And in the meantime, if the audience here, if you have any questions, you have this very exclusive chance to be able to ask Matthew himself as well. So make sure you type it in the comments. And while we go back to selling put options, because we do understand that in order to get the stocks, you really have to, the stock price do have to fall below the strike price before you can sell or you can buy the stocks. So there's always this risk of not being able to get the stocks and you miss the upside on it. So how do you mitigate that risk of not being able to buy the stocks eventually? That is a very good question. And there are a number of ways that you can handle that. So first of all, if we talk about options and there's a number of stuff that we have, we have a few different like YouTube presentations and things available on this topic, but we are actually writing. So when we write, I'm not sure how much your viewers understand all these concepts, but we are basically finding a firm that we want to own our portfolio. And maybe the price is a little bit higher than we'd like to pay. Or in fact, I will go as far as to say this, I never buy shares like a retail investor would. I never, even in my own personal portfolio, most of my money is in the fund, but I never would pay a market order ever. I would almost really never pay a limit order, set a limit order. I always sell a put as a tool by the stock because you get paid a premium and you get one for below the market price. So with that concept in mind, the calculation I typically am doing is I'm figuring out the annualized IRR on our premium versus the collateral because we hold the cash to buy the shares, our intention is to buy the stock. And typically when something becomes attractive, there's a lot of volatility and that's true in the value investing world. So in value investing, you're always looking to pay the lowest price. And when something comes down in price, if there's an event that takes place or there's some anomaly that occurs, as things come down and you're interested in buying, there's a lot of volatility. And volatility is part of the Black Scholes pricing model, which the world kind of forces to hold through. So as volatility increases, the price of the contracts increase. So just if something's falling down, you get a much higher premium. And so when I'm always a rule of thumb for me is that if I'm not getting double digit IRR in the premium collateral on our, in the premium on our collateral, then it's not something we're interested in. So, yeah, so Chloe to answer your question, if the shares run up and we miss them, it's a little, it is unfortunate, but because we've received an adequate IRR, we can find a new opportunity. So it's, we still have that return. In fact, usually we're just getting paid to wait. We're just getting paid to wait for the shares to come down to our price. And then if they, a lot of times, so I sort of think that they're presented on this few times, there's sort of four different things that can occur because our exposure is really to the notional of the shares. We're still committed to buying the stock. So that's the exposure that we have. So the very worst case scenario is that we're totally wrong and the shares go to zero. Okay, so let's say there's a $100 stock and we commit to buying it for 80 and they pay us $20. I mean, maybe I shouldn't use dollars, but what $20, as the shares come down below 80, we're still very happy for a long time. It's like we got $20, our net cost is gonna be only $60. If the shares were to go all the way to zero, which is the worst case scenario, we would lose $60 by using our approach versus $80 thing. With your buy out front. Traditional limit or market order approach. So it's still terrible, but it's not quite as bad as it could be. The other few are that it could go down just below 80 and we could buy and now we've only paid 60 and the market price never even goes that level. That happens quite a bit. And that's the most attractive scenario. The other is that the shares could be at 82 or 85. So we miss out on the owning the shares, but if this, let's say this was a one year contract, we would receive $20 on our $60 in collateral. That's a 33% return and we didn't own the shares. And because the shares didn't go up that much, we can actually maybe do it again. So we can write it on the same contract, same position a second time. The situation that is second worse, Chloe that you mentioned, is the shares go to 500, okay? And it feels, you're so right in a way it feels good. Wow, you really know where to find these. So that's right. So let's say in the fourth position here, the shares go up quite a bit. So we sort of do miss that opportunity, but we've returned 33% with the amount I've given you on $20 on an $80 strike. And now we may have to find a new opportunity. So it's disappointing, but actually our partners, they don't really realize, they're not disappointed because our returns are positive and good. So it's actually acceptable. It's mostly that we recognize how hard it is to find these rare gems that are so mis-priced that it feels like, oh, we have to start again and look all over for another opportunity, but there is one secret. And this is something we do in specific situations. But when there is maybe like a more of a binomial outcome or there could be a lot of operating leverage, there are situations where we sort of expect, if there's a difference between uncertainty and risk. Sometimes things are uncertain, so prices are down, but once an event passes or uncertainty resolves itself, shares can climb. And when we recognize that that might take place, which is by the way, kind of what's happening in Turkey, when we recognize that situation, we can actually use some of the premium that we receive from our puts to buy some call options. And so we don't miss the opportunity. So we still have net cash inflow. Yeah. And when you have a larger amount of capital, you don't have to have a single strike price. We can have multiple strike prices. We can have multiple expiration dates. We actually built out an entire matrix around it where we expect to sell, we expect to buy some of the puts that we sell, but not all of them, that's quite attractive because we're like getting extra premium and our cost basis is going down and down and down for that security. It's quite attractive to buy really long dated call options that are deep in the money. If this hypothetical scenario where the shares are coming to 80 and maybe we think they're worth 600 or something, we could actually buy, maybe we would buy a $50 strike call and we would pay, somehow we would find a way to pay like $32 for that. And then we would use some of the put premium to lock in a little bit of that call. And of course, if it just goes parabolic, we'll make a lot of money on those calls. And ultimately, the intention is to own those shares and then really own that business for, in our documentation, we call this section as like our infinite compounders. So these are companies that we have no intention of selling, we are very transparent with our partners, with the world, we own these businesses. When we own one or two or 3% or 5%, we are so pleased to own it and we are just waiting for that company to grow into the billions and trillions of dollars and we'll still own two, three, four, five percent of that firm. I see. And I'm also very curious in terms of, I think you are talking about like this, these are the seven major holdings that your current fund is holding. So when you are making investment into them, how do you make allocation in terms of, oh, right now, for example, you decide to allocate maybe 10% in daily journal or maybe 10% in virtual halfway, that 10%, would you allocate some money to sell put or would you allocate some money to buy stocks? Like do you separate it or how do you manage your funds using options at the same time buying stocks? Yeah, so it's quite interesting when you get into this level of detail, very seemingly similar value fund managers actually treat things quite differently at these levels. So what I mean by that is, there are, I believe the right way to invest and we can even talk at a high level about one of these NASPRs is actually 10 cent less, it's absolutely 10 cent. But Pete, the reason why it's 10 cent is quite interesting in itself. The reason is that they are great capital allocators and they have the right philosophy where they've actually made many dozens of venture investments all over the world. 10 cent just works best. They never sold it and they never trimmed it and they're doing a little trimming now. A little bit now, yeah. But regardless, it became 10 cent because they didn't, they allowed the concentration. It's like what happened with Nick's Sleep. Nick's Sleep is famous for owning these three securities for so long and then kind of giving it back to its investors and saying, we're just holding these securities, it's ridiculous to charge you. You do yourself. Yeah, here's your shares back. But if you read the early letters, they made a number of investments and what happened was three of them grew and they didn't trim and they left them alone. So, Chloe, what we're doing is, we're evaluating the opportunity based on, there's a lot of unique diversification that I think is unrecognizable when you just look at the seven securities. In fact, if you open it back up for a second, I'll just, for your audience perspective, I'll just share with you how a few of the unique aspects, but we're really looking to incorporate things like key diversification. So if you think about Berkshire Hathaway, this is like $700 billion market cap. Everybody knows Berkshire Hathaway, okay? It's a very stable, long-term grower. If you look at Daily Journal, this is a very different type of company but it's run by Charlie Munger in this whole group but this is only 400 million market cap firm and they have like 300 million in an equity portfolio and we're actually watching more the software business growth of Daily Journal. Daily Journal, this can be a multi-billion dollar firm. It will just take time. So the whole point is, we don't trim Daily Journal. We're not trimming Berkshire Hathaway. Dando here is actually the firm, the Indian-focused fund that's run by Manish Pabrai. So we're not invested in the fund. We own the GP of the fund and this is like a 30 million. It's actually not public, okay? So this is like a 30 million enterprise value business and we own a few percent of it. So if Dando becomes a trillion dollar business, we will still own a few percent of that and our firm will just be considered Dando at that point. It will be a little like the NASPR story. So when we're making a new allocation, I'm thinking roughly in terms of the Kelly criterion and we're looking for ways to really diversify our existing portfolio, like adding something unique and new that will add true diversification but also incorporate the themes I mentioned before, like this super high quality management, super wonderful business model. And then we need a low price. So it's very hard for value investors, for example, to catch these fang stocks in the United States. All the fangs ran away from everybody over a decade and it was very hard for anybody to consider them but some of them come back down. So we're very fortunate to be able to sell some puts on Alphabet, for example. We accumulate a few shares of Google but that's a very different sort of piece to this larger puzzle. So generally in the Kelly criterion, it would make very little sense to have a smaller than 10% position. And there's a few things that I will, I don't mean to go on for so long. So it will be up to me. But Chloe, I will, and Pete, I will share that. If you, it's sometimes valuable to have a little toe hold position. So what we typically do is we buy, we will start with an allocation of like a 2%. We'll move it to roughly 5% and then roughly 10%. That is typically our approach and that can happen relatively quickly. And but that is typically what we're trying, what we're looking at doing is sort of a two, five and 10% and if it doesn't ever make it to 10, it's because we've decided to exit. We learn a little more. We understand that it's really a little deeper. We maybe understand where our mistakes were or what we were overlooking because there's usually analysis and opinions on both sides of every investment. So we're usually looking to do two, five, 10. And at 10%, the plan is to sort of continue to hold. Although we also, as you get to know the firms, the level that we know these firms, when you know them at this level, it becomes really attractive at times. When you see an event that just pushes the price down, sometimes we're able to sell a few more puts, maybe out of the money puts and just collect free premium. We have a full position in Berkshire, for example, but a few years ago when it falls to, I don't know what was the price, like 170 during, I think it was 2020, was that when it happened maybe? Yeah. I mean, we just sold puts again because it was just silly. You know, it's just free money for us. So it's a little bit irresistible at times. But yeah, this is the typical approach, two, five, 10. And then we just leave it. And it really, we do not intend to take anything out of the infinite compounders. Recently, we removed Saratich from the infinite compounder list, which is kind of this, it's kind of been studied in the value investing community for a while. And the commercial real estate market in the US caused that and there's no longer the same growth potential because it's actually going through a liquidation. So there's reasons that things could get pulled out, but I tell my LPs, I tell our partners in the fund, you should be alarmed if you see me selling something from our infinite compounder list. You should be very comfortable if we do nothing and you should be panicking if we're selling because I'm not supposed to be selling. That is the entire point of the portfolio. You need to be long-term, you need to be patient. You know, you've all heard the quotes like the money's not made in the buying and selling, it's not made in the waiting and it's very true. You need this steadily compounding thing, but to get that steady compounding, you need to withstand some drawdowns and prices. And it just, it cannot phase, you know, your investment philosophy. Again, you need to just, sometimes, Munger says, you know, sometimes the tie will be with us and sometimes it will be against us and we just keep swimming either way. And we hold these companies and sometimes the price will be going down, sometimes the price will be going up, but the businesses are growing, they're run by great management teams, extraordinary management teams, and they're very fairly priced, cheaply priced in many cases. I remember when I went to the Bobby Hill party organized by Matthew and when I asked him, oh, how long have you been holding Berkshire?  And then he said, oh, I'm just like, as compared to those investors, in fact, they have way longer than me. I'm like, wow, like there's like a lot of great investors, like I think one of the key success factor is that true patience. And just like what Matthew was saying, money is made in the waiting. Yeah, I mean, I think one of my good friends, Gary Dvorak, who is often on CNBCs, now living in China, I believe he was bringing his class from Kellogg University in the, maybe he doesn't want me to say this, but I think it was the old movies, he was bringing them all. And so, he's been holding now for maybe 30 or 40 years. Wow. And there are other people, we sometimes do a poll in Switzerland, so without sharing too many names, I know people who are 50 year holders of Berkshire. I believe I bought, I know for a fact, I bought my first share of Berkshire, but this was long before they were splitting in things. So this was a B share. I bought it at a good friend's house who was working at the Federal Reserve Bank in New York in 2003. It was 2003, so it's 20 years. And we own those shares still and many more. So we are buying and we are net buyers for the last 20 years and I think we'll be net buyers for the next 20 years. Yeah, but net buyers of business, like that's what Warren said, right? Wow. Pete, do you have other questions that you want to ask Matthew? No, I'm just so happy to learn that the strategy because Matthew just gives some background. We also share with a lot of our followers that selling puts to get the share and even selling call options to get rid of them later on is a fantastic strategy just to get that premium. And you can kind of choose to decide what you want to do with the premium. And today, I think Matthew, you shared about using it for a call option. So it's very comforting to know that this strategy is also used by yourself as well. Time for validation and so yeah. It's very... Okay, go ahead Chloe, please. Yes, yes. It's just another question that Matthew, you can say first, yeah. Pete, I was just going to add that I don't know if your viewers recognize this, but it's very valuable what you're teaching and it's really unique. It's not well understood. In fact, I used to, I would go to the Chicago Board of Exchange website, years ago I would visit and I don't know if they changed this, but they would explain on there, what is a call and how does it work?   That was it. They never said to sell a put. It's so strange and so I came to this conclusion totally independently back when I was doing the work at Goldman, I was analyzing some different products for a number of the different desks. I recognized that a bunch of the trading desks were sort of hedging out each other's holdings. And this concept, it's very simple. It's like algebra. You get paid and now you're, the denominator is lower, so of course your IRR is higher. It's very logical. It's very rational. In fact, people don't realize that Warren Buffett does this. Warren Buffett, when he was buying Coca-Cola, he was selling puts and then he was buying Burlington Northern, he sold puts everywhere and then bid a higher price than the strike for the whole company. It's amazing what you can do, but yet even value investors totally fail to recognize this. Very good friends of mine, very good investors aren't interested for various reasons. Maybe they're already wealthy. They don't wanna deal with it or maybe they don't want anything between themselves and the stock or maybe it's just a little confusing. But eight, 10 years ago, I couldn't find anybody doing it. I couldn't find every once in a while, I would read an article in Barron's and maybe somebody would get it partly right. Now I think there are a few more people that understand it, people like yourselves that are sharing with their audience, but because it's so unique, your viewers might think it's common. It's really rare. So this opportunity, like people are using the products for the opposite thing. And it makes systematically higher price. There's more demand for puts to buy puts and calls than there is to sell puts and calls. So you wanna be net sellers of these highly priced things and you're adding real value to your viewers if they're following your instructions. Thank you so much. Yeah, Maddie, I'm just curious, right? Because Warren Buffett always talk about the importance of management, right? Do you, how do you assess the management? Like you as a fund manager, do you think that you have some exclusive insights that like you get to hang out with those management and all this so that it gives you more confidence and understanding the person's integrity and everything because we as retail investors, how do we assess all this information? So it's very important because basically what you're looking for what really what you want, you of course want integrity.  You want a situation where if there's bad news they'll tell you and if there's good news they'll tell you. But really what you're also looking for is somebody who has really exceptional capital allocation skills because the role of the top managers is really a capital allocation role but as you progress through business that's usually not the skill set that's required to get you to that level. So what happens is you get a whole C suite of managers who are maybe paid with incentives that are not aligned with shareholders and then they'll make mistakes. You know, the C suite can, if you have a company that's bringing in tons of cash flow it's these managers that get to direct that cash flow. So they could pay off debt or they could buy back stock. They could make an acquisition. They can do a number of things with the cash and that's the decision they have to get right for the business to continue compounding. They can actually destroy capital quite easily if they make the wrong choice. So where I have started for years which is a helpful place to start in the US we have these 13F filings. 13F filings are done by funds that have 100 million plus in AUM. Every quarter a fund needs to report to the SEC and then it's public. You can just go look it up at scc.gov. You can look up the snapshot of what they hold and that doesn't help you if you're looking at a high-frequency trader because it's reported 45 days after the quarter the positions will move but if you're looking at a very concentrated well run value-based fund they hold eight positions, 10 positions for the change. And they never change. And when they do change it's a really big decision. It's a notable observation. And so if you start, so I've been, we look at and now we automate some of this but we look at about 100 different funds that are really strong value-oriented funds and we get a super set of the current holdings each quarter and it's a big matrix that I review. And we basically come up with the super set. So if there are like 10,000 investable securities in the United States, the efficient market hypothesis mostly is true. Most information in the US is flowing pretty quickly into the stock price. There's, it's really unique to find the rare thing that's mispriced. So the shortcut is to go through these 13 Fs. You know, if you're looking at what Bill Ackman and David Einhorn and Guy Spear have been doing over the last quarter or years, that's really valuable information because they've had teams of people doing maybe millions of dollars worth of research for a long time. And now they just told you, here's the answer that we, here's the conclusion we have, we bought. Okay, great information. Doesn't mean that we have to buy, but we find that there are usually about three to 400 securities in the super set of all of their portfolios. So we have immediately just eliminated 95% of the US market. It has to be something, and you'll see, not all of our compounders are within this piece of portfolio, but there are just small breadcrumbs that can lead you to the other things. If it's not in anyone's portfolio, we need to really understand why the whole world missed it and why we think we are right. But really, if you have 300 securities, that's much more manageable. And now we can start evaluating the management and the capital allocation capability of those teams of individuals. So, you know, if you have a Warren Buffett or a Charlie Munger running the show, that's terrific. But for example, with Daily Journal, people don't recognize, you can go through the board members and you can just see, you know, who is Charlie Munger going to select to be on the board of his firm? They're gonna be the most extraordinary people with diverse skill sets. And they really are truly special, like Tom Murphy's daughters on the board, Howard Mark's partner is on the board. These are exceptional people with great character, capital allocation capability, integrity, et cetera. So, oftentimes, they just shine out. It's unique to find that skill set. And so when you discover it, it is oftentimes like some dominoes falling, like, wow, if there's this person as the chairman, who did they select to be the CEO? Then you do some research, you find out that's an extraordinary individual. And then the CFO is an extraordinary individual. They tend to hang out together. Wow, I think what you share with me is something that very, very aligned with one of the book that recommended by one of our fellow investor as well. His name is Hardy. Hardy, in fact, also went to your party. I'm not sure if you remember him. He actually introduced me this book, which is called The Rebel Allocator. And yeah, it talks about the importance of capital allocation as well. I think this is a very good book. In fact, it recommended by Charlie Munger, right? So, yes, and Jake Taylor is a friend of mine. In fact, Jake was at the barbecue two years ago. I don't think he was there this last year. Do you know Jake? I'm sure Jake would come. Maybe Jake would come on your program as well. That would be great. Yes, I've read the book. I love the book. Jake takes a really different approach to telling the story. It's much more like a fiction narrative. And it's a great story. And of course, Jake's views align very closely with mine. So it's the lessons that he's talking about are the same lessons I'm sharing with you. Yeah, it's a wonderful book. Guys can go and read it, go and find out a little bit. Because I think just like what Matthew said, Jake write it in a way that it's like storytelling. So it's not like other investment books that you find sometimes it's a little bit hard to consume. But this is very easy to consume. And there's a lot of great investment lessons from Charlie Munger, from Warren Buffett, and he condenses it into a very storytelling format. It's a great book. Yeah. That's right. All right, so maybe we have, because we also don't want to hold you up for too long, yeah, Istanbul as well. Maybe one last question from one of our followers as well. And the inverted world he's asking, do you expect a sector rotation from tech into other sectors in the later part of this year? For example, the finance sector. It's a very interesting question because I don't always think about it that way. And in fact, I don't. I think that it's everything, you need probabilistic thinking for your analysis, but I think there's a high probability that a lot of the AI factors and things that are coming online in the chat, GPT, et cetera, or BARD, that these help fuel further tech growth in certain spaces. Maybe FinTech can do well, but is there going to be like a sector rotation? It's basically asking, will the psychology of market participants shift from technology to finance in Q4 of this year? I think it's a unknowable answer, a question. It's an unknowable situation. Howard Marks talks about this because Buffett talks about this, for something to be, and a lot of people, I talk about this, for something to be really valuable, it needs to be correct and it needs to be knowable. So if you're asking, and you need to be able to recognize what is knowable and what is not knowable, because it would be of course great to know what interest rates are gonna do next year. It would be so nice to know what's gonna happen whenever there's threats on debt ceilings or what's gonna happen to the tertiary, that would all be really, really valuable, but it's not knowable. So it's not something that's worth basing an investment thesis on. You can sort of have an opinion. I look at how the world is operating. I have macro opinions and views, but we don't base investment decisions on those. So I'm not going out to look for finance firms because I expect capital to move from tech to finance. It's a bottom-up analysis. Where are the greatest companies in the world, the greatest business model in the world with really sustainable large margins that can compound decades and decades and decades. And I'm somewhat sector agnostic. If it's in Turkey, great, if it's in China, great. Tell me something in Singapore I should look at, terrific. We'll look if there's something cheap enough in finance that your viewer has found, sure go buy that, but I wouldn't base it on expectations of like sector rotations or capital flows. It's super important and would be very valuable, but it's truly not knowable. How could anybody know? People actually ask quite often, they make assumptions and things based on like US interest rates, rates are rising. Now we might see that Chinese rates are maybe coming down. We've just seen something happen there. Of course, knowing what rates are going to do later this year, at the end of this year, people are speculating all over the place. People go on CNBC, Wall Street Journal, Bloomberg. All they do is talk about what our interest rates going to do. And they either know they don't know or they don't know they don't know. But I know they don't know. I know they don't know. And I know actually that Powell doesn't know. So how do they know? And so these, if it's unknowable, it's not worth making a decision on investment. You need to go from the bottom up. So when you're in the value investing space, you're looking at, you know, Druckenmiller might know or he's very good. There's very few people who might have this superior insight, right? He worked with George Soros for years and years. He may know, but he also changes his mind very quickly. So it's just something, I'll say, I don't know the answer to that question. It's an unknowable answer. And I would make, I would encourage you to make your investments on a bottom up analysis. So you look at the unit economics of the goods or products that are being provided and you analyze what is revenue going to do and are the margins sustainable and how much are earnings and what sort of multiples are you getting? Are you getting a good margin of safety? Can you sell a pot and get a nice premium? If you take that approach, you're much more likely to have a successful outcome because those are knowable things. It's a, I think superior way to analyze the markets than sort of anticipating interest rates, macro, big trends, sector rotations. Those are much less knowable factors. Oh, that's simply amazing. And then you can see that just really focus on the fundamentals, right? Like the true business, is it really a valuable business from the bottom up approach, not based on speculation, like thinking about things that he cannot control but really analyzing what is already out there and really see whether it's the business valuable and continue to be able to withstand the test of time. So I think that is true gem of being a value investor and that's how he is able to grow his fund so well for the past decade and will continue to do so, right? Because it's like an infinite wealth loop. That's super amazing. Thank you so much, Matthew, for coming up here. Thanks, Matthew. And for those who are interested to find out a little bit more about Matthew's fund, maybe Matthew, you can share with us where can they find out more about you as well. Sure, petersonfonds.com is our website. So you can go there and we have a lot of information. We have a media as a material section. We have years and years of annual reports and all sorts of letters that we've written. We also have, and there's a 2022 letter in fact, we also have Talis Capital is another place you can go. If you wanna look at the Talis opportunities, the Turkish focused fund. But I'm also on social media. You can find me, I think it's Matt Peterson's CFA as I think my Twitter handle. We have a YouTube channel. And if anybody wants to speak further, I'm happy to have conversations and they can write me an email, matthew.petersonfonds.com. Yeah, so I think Matthew has been providing a lot of great insights to his followers as well. So follow his Twitter, follow his YouTube as well. He will definitely be continuing to share a lot of great insights over there as well. And in the meantime, while we are going to wrap up this special live, do you have any words of advice to our followers to help them to really continue their investment journey better? Words of advice. I mean, I guess, well, I think what's very important is that people are really patient. They do this bottom up analysis. They're looking for great business models and great management teams and extraordinary prices. And if you couple that, combine that with selling puts to getting access to firms at below market prices, and then you're very patient and holding for a long period of time, not selling, not panicking when the price moves and watching the business, right? Not watching the price of that business. You will do very well. And I also think it's worth saying it is very difficult to outperform the market. It's professionals fail to outperform all the time. I mean, I think the standard statistics are that 80% of professionals underperform the market each year. And over a few years, the professionals outperforming change because there's a few just speculating and getting it right by luck. And so it becomes this very, very small group. So as a retail investor, you need to understand what niche you're having. It's like, if you're gonna go into a sporting event against professionals, I mean, this is a very competitive place. So you need to find a niche opportunity to outperform. Otherwise, you should just be buying the market. There's no shame in doing something like that.  So these are kind of two words of advice, but either you need to be bottom up to outperform. And of course, maybe it's an enjoyable hobby for people, things of that nature that's totally understandable. But really a lot of times people do much better if they just buy the market. And thanks for being so honest to all our audience here. And I think that is truly true, right? Like if we don't spend that effort to do the bottom up research, we might as well be better off buying the market and let the market to work for us in the long run. Once again, it's really about patience. And I can see so many people are super thankful to your sharing tonight. Some of you say thanks so much for your perspective, for your answer. And Sebastian says thanks. I learned a lot as well. So if you guys learn a lot and really find this video helpful, remember to give it a thumbs up and share it out or I share it out so that more people can also learn from Matthew's insight. And I think he has really shared a lot of golden nuggets throughout the close to one and a half hour of sharing. All right, fantastic sharing. Thank you so much for everyone for tuning in as well. I know the majority of our audience are from Singapore, from Malaysia and it's late night, but yet they are still so committed to learn. And thank you so much Matthew for being here as well.  So, oh, some of you are asking what's the book again? Oh yeah, the book, okay, it's called The Rebel Allocator, right? So go and read it, it's a great book and go and follow Matthew. He has a lot more insights that he shared on his social media channel, for example, you can follow his Twitter, his YouTube channel as well, or maybe just check out the fun website, right? Matthew Peterson, yeah, Peterson Capital Management. So with that, okay, we will see you guys in our next sharing. There's a lot more things that we are going to share, give you guys a lot of insights as well. Maybe next round we are able to bring out another guest, right? From the US, that would be fantastic as well. All right, so thank you everyone for tuning in and thank you once again Matthew for being here. Really grateful and thank you Pete for being here with me as well, all right? So we will see you guys in our next live. Thank you, see you.