Andrew Einhorn from LevelFields shares insights into leveraging AI for financial market analysis. Their innovative platform is designed to detect key events affecting stock prices, enabling investors to react swiftly. The conversation covers the benefits of AI in democratizing financial information and the future implications for investment strategies. Disclaimer: Nothing in this episode should be considered financial or investment advice. Our aim is to provide information and insights to help you understand the evolving landscape of AI and investing. Always conduct your own research or consult a financial advisor before making investment decisions.
Please get in touch with us with any questions, comments and suggestions by emailing us at contact@economicsexplored.com or sending a voice message via https://www.speakpipe.com/economicsexplored.
You can listen to the episode via the embedded player below or via podcasting apps including Google Podcasts, Apple Podcast and Spotify.
About this episode’s guest Andrew Einhorn
Andrew Einhorn is the visionary CEO and co-founder behind Level Fields, a groundbreaking company leveraging artificial intelligence (AI) to revolutionize the way investors interact with the stock market. With a career deeply rooted in technology and finance, Einhorn has dedicated himself to democratizing access to advanced investment strategies, making it possible for the average investor to make informed decisions swiftly and with confidence. Before establishing Level Fields, Einhorn led a successful event monitoring system company for a decade, serving publicly traded companies and offering insights into how market events affect stock prices. His passion for utilizing technology to enhance market transparency and fairness has led to the creation of Level Fields’ AI-driven platform, designed to scan the market for events impacting stock prices, thereby leveling the playing field between retail investors and the larger, more resource-rich players in the market.
What’s covered in EP229
- Introduction. (0:00)
- Using AI to analyze financial news and announcements. (2:47)
- Using AI for stock market analysis and avoiding fraudulent companies. (7:19)
- AI applications and their limitations. (13:38)
- Using AI to analyze market data for investment insights. (18:24)
- AI-powered stock market analysis. (23:26)
- AI-powered investment research platform for retail investors. (28:01)
- Using AI to analyze audio transcripts for investment insights. (33:12)
- Using AI for event monitoring and investment analysis. (38:45)
- Using historical data for investment strategies. (44:10)
- AI’s role in investing and the financial establishment’s reaction. (49:19)
Takeaways
1. AI can help democratize access to investment strategies by scanning vast amounts of market data and financial reports that individual investors cannot monitor themselves.
2. Understanding how historical events have impacted stock prices can provide insights on predicting future price movements and avoiding losses from overreacting to news.
3. While AI is not a crystal ball, it can be a useful tool for investors when combined with human judgment, by automating tedious research tasks and identifying potential opportunities that may otherwise be missed.
Links relevant to the conversation
LevelFields website: https://www.levelfields.ai/
Andrew’s interview on the Side Hustle City podcast: https://www.sidehustle.money/1350142/14348901-revolutionizing-investing-andrew-einhorn-unveils-levelfields-the-game-changing-tool-in-stock-market-analysis
Transcript: Revisiting Ricardo: The Rise and Fall of Ricardian Equivalence
N.B. This is a lightly edited version of a transcript originally created using the AI application otter.ai. It may not be 100 percent accurate, but should be pretty close. If you’d like to quote from it, please check the quoted segment in the recording.
Andrew Einhorn 00:04
Just like any new tech in the market, you’re going to piss off some people. And, you know, we’re trying to give some of these strategies to the general population and democratise access and everyone likes that.
Gene Tunny 00:26
Welcome to the economics explored podcast, a frank and fearless exploration of important economic issues. I’m your host gene Tunny. I’m a professional economist and former Australian Treasury official. The aim of this show is to help you better understand the big economic issues affecting all our lives. We do this by considering the theory evidence and by hearing a wide range of views. I’m delighted that you can join me for this episode, please check out the show notes for relevant information. Now on to the show. Hello, thanks for tuning in to the show. Today we’re exploring an exhilarating intersection, AI and investing. In this episode, we’re joined by Andrew einhorn the CEO and co founder of level fields, a company that’s at the forefront of applying AI in financial markets. Andrew and his team have developed a platform that scans the market for events proven to impact stock prices, allowing investors to make more informed decisions rapidly. For Andrew is not just about speed, it’s about levelling the playing field between the average investor and the big players in the market. As always, I’m interested to hear what you think about the issues we discuss on this show. So please get in touch and share your thoughts. You can find my contact details in the show notes. Before we proceed, I need to make a quick disclaimer. Nothing in this episode should be interpreted as financial advice specific to you. Our aim is to provide information and insights to help you understand the evolving landscape of AI and investing. Always conduct your own research or consult a financial advisor before making investment decisions. Right? Oh, we’d better get into it. I hope you enjoy my conversation with Andrew einhorn from level fields. Andrew einhorn from level fields, welcome to the programme.
Andrew Einhorn 02:15
Thanks, Gene happy to be here. Appreciate you having me on.
Gene Tunny 02:18
Excellent. You’re doing some very interesting things in AI and in applying AI to financial markets that I’m delighted to have you on the show to talk about so your company is level fields and the pitch is find better investments 1800 times faster. Ai scans for events proven to impact stock prices. So you don’t have to. Okay, so can you explain I mean, what are you actually doing there? Andrew? What’s this? What’s this AI? What’s it scanning? Can you please talk to us about that place?
Andrew Einhorn 03:01
Your Yeah, happy to, at a very, very basic level. It’s monitoring the market for events that are proven to move share prices, either north or south, and positively or negatively. If you know how a price is going to move, and you’ll learn about the event happening, then you can anticipate that move. And you can make short, mid or long term bets trades knowledge and information, you know, concrete piece of it would be you know, if the CEO departs from a large corporation like an Amazon, we have a data analytic system that shows that usually results for companies like Amazon in a price decrease of a couple percentage points, you know, what’s happened with Amazon. But the data also shows that within about three months, the stock is right back where it used to be in many cases, far above it. And we can see the different types of stocks, you know, smaller stocks versus bigger ones, profitable or unprofitable companies, they all react a little bit differently. If you take an unprofitable, struggling company, and the CEO leaves, the share price often goes up. People are celebrating that, hey, you know, hope is coming. Let’s bring somebody else in. And so the data set shows that and it alerts people of these kinds of opportunities, which happen in some cases 100 times a day, across 1000s of stocks that are in the market. And so we track all types of events, leadership changes, capital deployments, you know, being added to indexes. Investors coming in large billionaires coming in and buying positions and companies pushing for changes. We have lots of different event types and the ideas, you can just quickly find what’s going on in the market without actually reading very much, because the AI is out there reading all these company announcements, all the reports, they’re putting out the news that’s covering them. And just in the US alone, that amounts to about 6300. Companies, all making announcements constantly. And we get a large part of our information directly from those companies. But the reports can be long, it can be boring, and they can be tedious for somebody to read, even if they have the time to read the reports of 6300 companies, which is physically impossible. Unless you have a couple 100 analysts covering all the stocks, you’re never going to be able to do it as an individual. As a result, there’s a natural discrepancy in the market, where an average investor doesn’t have the resources or the time or even the knowledge sometimes to find out about all these events, to know what’s going on in the marketplace. So they’re constantly at a disadvantage to large hedge funds and asset management shops that do have the resources to scan the entire market to deploy capital. And if you want to test that theory, just ask an average person to name as many stocks as they can. I think you’re gonna stump people around the 20 to 30. Mark, everybody can name the seven, The Magnificent Seven, right? After that, they’ll start to slow down. Even very good seasoned investors will have a tough time after that. And as the reason is that, a lot of the media is biassed towards those mega cap companies, covering them all the time, making you aware of them all the time, because you click on it. And they can if you click on it, and you read about it, they sell more ads. So they keep writing about Elon Musk and everything he says on Twitter because it drives advertising revenue. But what it also does is really Rob, you have the opportunity to hear about all these other companies that are doing great things that the media doesn’t cover, or they don’t have the staff to cover. And so that’s where the AI comes in, it can monitor the entire market for you. And really, for the first time ever, you have a personal assistant in reading and understanding and analysing financial news and financial announcements. And you can take that and create a very customised AI search agents look for just this type of thing that you want. So if you say, You know what, I really love investing in energy companies, and you go out look for energy companies that are growing revenue, at least 10% growing earnings, at least 20% and recently increased their dividend by you know, whatever percent, I just alert me every time that happens, I don’t have to do anything, ever again, on my research, I’m gonna get an alert, right in my email, when my criteria is matched. And if that’s my investment thesis, then I just go along on on those investments. So there’s a lot of flexibility in the platform. And what we’re really trying to do is kind of break down that barrier that most people have, and not being able to monitor the market at scale, not being able to see those was really interesting. bull markets, or in some cases, bear markets, because we can go both ways, you know, in the, in the strategies, short and long, that are reacting to different macroeconomic events. And we see that on the basis of company financials, we see that in the basis of what CEOs are saying and our financial outlook. We see that in the basis of what the leadership is doing with capital allocation. And so, you know, an example is when, you know, when Russia invaded Ukraine, there was in the middle of a pretty decent sell off already in 2022. That was happening. And this really accelerated the market sell off. But there were some companies that were thriving. I doubt many people would know what those companies were could list them, but a lot of them were fertiliser manufacturers that are based in Canada and the United States. And the reason was, they couldn’t get fertilisers, which a large percentage of them came from Ukraine, Belarus and Russia, you couldn’t get them out of that region because of the conflict. So the price of these types of fertilisers was rising was doubling. And so companies that weren’t involved in the conflict and could export their product. Were then selling it for double the price. And so what we saw on the platform was a slew of fertiliser companies, increasing their dividends doing special dividends, increasing stock buybacks, and we’re sort of you know, beating earnings and we’re wondering what is going on with fertiliser companies? I had no idea I never bought a fertiliser company in my life. But you do two seconds of Google research you say okay, they sell this you know, potash potash is a lot of it coming out at Bell roofs, they can’t get it. Price is 100 percent bull market for fertiliser companies. And so this one company that I actually invested in, called nutrient because Canadian, you know, the share price jumped 75% In about two months. So, you know, if you’re an investor and you can go straight equity, you can leverage with options, stock options, you can make a lot of money on those types of things. But you have to have the awareness, you have to know those things are going on. And you have to have a system is sort of connecting the dots for you fast enough for you to react otherwise, you know, you’re kind of going to sit in the same 789 stocks forever, not really knowing why they’re going up and down. Yeah, gotcha.
Gene Tunny 10:43
Are you scanning social media too? Because I mean, some of the names, you mentioned them, and you think of some of these high flying CEOs. Many of them are engaging in risky activities, you know, go into space, and all of that. I mean, are you scanning social media for for, you know, hints of, you know, potential, you know, shock news,
Andrew Einhorn 11:04
we were a little bit, we kind of pulled back from it, because Twitter was cutting off access to their data sets and their API to third party developers like us. But we also found it for the most part, you know, we were relying wanted to rely on the company announcement as much as possible. We want to do overweight, potential pumping, dumps that, you know, market manipulation that can sometimes happen. We’re trying to protect, you know, the users and the investors on our platform. Because there are some savvy, bad actors out there that will utilise social media to pump up stocks and fake news. And, you know, sometimes, if you’re not watching closely, you can fall prey to that.
Gene Tunny 11:44
Yeah, that’s a good point. Yeah. So there’s a lot. Yeah, so yeah, you got to be careful, you don’t really know what, what’s true out there. So that’s a really good point. Whereas with the company reports, I mean, obviously, they’re, you know, they’ve got a legal obligation to tell the truth, but have been sometimes, of course, you know, there can be,
Andrew Einhorn 12:03
and that happens to they, you know, sometimes the reports are fake, there was a company. I forget the name, but the ticker was to T IO. And they faked all their financials. And it looked like, you know, they did this wonderful quarter, and they were growing by 5,000%. And it was like, wow, one of the scenarios in the events that we tracked is the short seller reports. So, in funds, you know, they specialise in kind of busting the fakers that are out there in the market. And so he saw in our platform, those short sale report went up on this, went out on this company to and said, you know, all the all the founders were criminals, and they had already been convicted fraud before. Looks like they’re doing fraud. Again, they investigated some of these alleged sales contracts that they had that were worth, like a billion dollars. And what the company had done was sort of open up like a shell LLC, create a fake purchase order back to the company, and use that as sort of evidence that they were driving sales up. And so the whole thing just fizzled out. And so you do you do see a good amount of that, you know, years back, it was luck, and Coffea, China, they were faking their arse. And a similar kind of hedge fund, you know, put up a camera and started counting how many people actually went into the luck and coffees and said, you know, if, if their numbers are right, then they’re they’re serving four times the number a couple of coffees and Starbucks. Yeah, yeah.
Gene Tunny 13:39
So I just want to talk a bit about the AI, because you mentioned you’re scanning these company reports and news from the companies. And so to an extent, you’ve got to trust what’s coming out of them. And what have you got, is it so people talk about, and this is what I want to explore with you, because I think pre show we were talking about how, look, there’s been applications of AI for years. And there’s been things like algorithmic trading, which I mean, I’d be interested in your thoughts on how close that is to the AI, whether that’s a true AI, that the public discussion about AI is just really taken off with these, what they call these generative, pre trained transformers, if you’ve got that, right, the GPT chat GPT, where we’ve got that interaction with a Can you talk about please Andrew, they’ll try to explain, like what you’re doing, is it a are you using a GPT? Is that right? And how does it differ from what other people have done in the past
Andrew Einhorn 14:43
now we developed our own proprietary artificial intelligence system. And the way you kind of think about it is, you know, the chat. gfpt is sort of the mouth of a body. And the stuff that we’re doing is more like The beating heart. Right. And so the interaction with AI through chat, GBT is obviously, you know, through chat, it’s a communication channel. And so that’s one deployment of AI. whereas ours is more sort of, like, you know, a monitoring, AI, it’s going and finding different pieces of information that are out there. It’s making sense of them putting them together, you know, it’s a little bit more like cognitive functioning, I should say, probably better, better than the heart analogy. And so AI, in general, can be anything, you know, very, very basic tasks, very, very difficult sort of self directed tasks, it sort of depends on on your goal. Chat. GPT is great, you know, for interacting, but it’s completely reliant on third party data that has already found the answer to the question that it’s now speaking, right. It’s not thinking and processing for itself, it’s going into a database of information that it knows. And then it’s extracting that information and then saying to you, and like, plain language, here’s what I found, you know, a little bit more like an advanced Google search. And so what we’re doing is we’re finding the answer, right? So if you ask a question, like, why was Apple stock down yesterday, you’re gonna get some message that says, you know, my, my training only goes to February 2023. We, you know, we don’t do real time analysis, or might say something like, Well, according to this one news article, you know, blah, blah, blah. It’s not doing anything on its own, it’s just summarization, our system is going out and coming up with an answer, because we are not only extracting what happened in that event. So let’s use the example of Apple. So Apple stock goes down yesterday, we find out that Apple made an announcement through our AI and AI identifies Apple doing a product release of vision, pro whatever. And then in the system, it’s identified that the share price moved down. And that was the only major event. So those pieces of information the AI then puts together and says the reason why apples down was this bullish event product launch, which, you know, seven times out of 10 is actually negative for Apple. Now that we have that piece of information, you could overlay something like a Chet GPT into our database and say, Hey, why was Apple stock down yesterday, it would look at our data, pull it out and be able to summarise, you know, coordinate a level fields. This was because of, you know, blah, blah, blah, like Apple stock was down because of a product launch that didn’t go well, instead of you. If you look at that at scale, and say, Okay, well, our system is more was a research agent that’s actively out there looking for information, assessing what’s going on analysing what’s going on, and then coming up with a data array of information, just showcase what happened. It gives you far more information about what’s likely to occur next. And I think the best example I can give is like a weather report. Yeah, here’s where it’s raining, here’s where it’s sunny, there’s an 80% chance that the rain is going to be four inches of rain. And it’s going to last for 12 hours. And that’s kind of what the analytics of historical data sets like ours can provide. And so if you are, you know, a type of person who wants to invest in stocks, but maybe doesn’t necessarily want to listen to someone’s opinion on CNBC, or, you know, one of these newsletter services, this is this is the next Amazon or these are five other stocks that are better than Amazon, you can actually look at the data set and see, well, this company had a big bullish event, this bullish event 80% of the time, ends up in a positive price return of 20% over the next X number of days, weeks, months. And so we’re trying to move away from that, you know, kind of human opinion driven stock market and move closer towards an understanding of how things normally play out. And a lot of the market, to your extent is is driven by algorithmic trading. And those trades, about 60% of the trades in the market are automated. And so why, how are they automated or automated on the basis of patterns that people are telling it to find? And so if you know how the algorithms are reacting, and you know what they’re reacting to, when you find the reason why they’re reacting, it’s easy to predict what happens next. And usually, they’re using some kind of technical analysis, looking at patterns and charts. And so the piece that we really plug in and say, well, these patterns and graphs and movements on the charts. That’s great. But events caused them. And so what we often see as the event happens, it starts to raise the price from the for the stock that that people are watching, then the algorithms see that price movement, because it breaks the pattern of some kind of technical analysis. And then the algorithms buy it and drive it even further. So you have that kind of double burst if you can get out in front of these events. Right. And that’s a lot of how the market moves. Yeah.
Gene Tunny 20:28
So yeah, a few follow ups. This is fascinating. Is your AI? Is it trying to then model how the algorithms will respond? Is it? Or are you just looking at the impact of events, so I know that you’ve from a previous interview, you’ve done your you’ve done a lot of deep research, we’ve looked at Google Scholar, you’ve pulled out studies, events, studies, which show how particular events impact the market, so you’ve got that information, or you also, and you know, there might be an immediate impact to you, then, are you trying to maybe to some extent, they’ve looked at this themselves, but are you then looking at how the market reacts through the reactions of all the other participants through the algorithmic trading, etc,
Andrew Einhorn 21:10
you look at an aggregate. So we think of market participants just broadly how it reacts, right, and in some cases, the system you can see, the speed of the reaction differs depending on the event type. For example, one of the events we track is an increase in dividend amount. You invest in dividend stocks are generally not moving really fast. You know, they’re there for longer term, they’re collecting dividends. And so the price action on that first event is relatively slow. Whereas other events, like a company being added to an s&p 500 index, there are big hedge funds that trade that specific scenario that have spent a lot of money to develop algorithms to buy shares, the second, the s&p organisation announces a new cause, you know, a new constituent in the index, that does trade very quickly. When we just show it, we just you can see it on the platform that they have, the average move is a percent done at an event like this. And if you start to look at some of the data, you’ll see it moves fast versus a dividend event, which may be moving slowly over several days, you know, and then if you’re looking at some of these things, in aggregate, like multiple dividend increases over the span of let’s say, a year, year and a half, you then can predict longer term gains, you know, a company that’s repeatedly saying things are good, so much, and they’re so good, we’re gonna give away money. And then that other pattern starts to reveal itself. And so it really depends how you want to use the system. And we’re, we’re very much the data provider using the AI to kind of showcase these patterns that exist all over the market. And in some cases, you can take kind of contrarian views or find these, you know, hidden gems that you would never see before. Just just just by having access to all of the data at kind of the palm of your hand. My favourite example is a stock called very, very active. It’s VR TV got bought out, but years ago, this was mid March 2020. We’re in the middle of COVID. And stock market selling off, we are going into lockdown globally. You know, the big ship is moving towards New York, you know, with extra hospital beds. And there’s there’s a there’s a panic. At that time, most companies, you know, are starting to slash their dividends. They’re looking at cost saving measures. There’s one company that came in started doing stock buybacks or buying back there shares. And it’s a very brave move. And you would think, stupid move for somebody to take their company’s cash right as we’re going into, you know, potentially a global depression and take that cash and start buying back their shares with it instead of using it for operating capital. Why would they do that? Well, this particular company is a engineering and kind of design firm. They build and sell direct to consumer product packaging, isn’t it that everybody used to sell through the big stores who had a product could no longer sell to the big box stores. They had to get it to your doorstep that required new type of packaging. In order to do that. The whole world was going through the same issue. Everybody’s Sitting at home buying stuff. And now you Commerce has completely shifted, this company is sitting in the middle of what ended up being a goldmine for them. And that precipitated a stock run of 2,600% growth over the next three years. And you would have never seen that had you not been following, you know, why would anybody be doing this random stock buyback in the middle of COVID. And so that’s the kind of thing that this system can can identify. And it’s, it’s, it’s a proof point that the macro economic event is either positively or negatively impacting, you know, these individual stocks. And you can’t, you can’t monitor the market for that kind of thing, because stocks still went down. That was a funny thing. And you hear people, you know, they’ll give a criticism, well, I just look to see what stocks are up. And when stocks are down, well, then it happens after Seminary has decided what to do. In this case, the stock kept going down for the next couple of weeks while the market sold off, and then began 26x run over the next three years.
Gene Tunny 26:09
Okay, we’ll take a short break here for a word from our sponsor.
Female speaker 26:15
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Gene Tunny 26:44
Now back to the show. Where are you guys? Do you in direct somewhere you’re in DC, the DC area or Baltimore? Is that right? Yeah, just
Andrew Einhorn 26:55
outside of Washington DC. We’re a Virginia based company.
Gene Tunny 26:58
Right authority. So Virginia rather than Maryland. And so if you’re you must have computer scientists on staff. Do you who develop this proprietary AI? I mean, what what’s your operation look like? Do you have? And you have people? Do you have actual analysts as well, I mean, you’re you solely relying on the AI to deliver the predictions.
Andrew Einhorn 27:21
We have all the above. You know, we have couple PhDs, some in linguistics, some in AI, some in physics, astrophysics, at do a lot of good in the modelling, and analysis work, we have those who have financial backgrounds, we have a lot of financial advisors that are from the street or certain hedge funds, previously, and sort of former lives that have helped devise the system. And so a lot of what we’re really trying to do is think, what are the big annoying, tedious, time consuming tasks that you have to do as an investor to figure out what to buy? And how can we automate that, all of it so that the barrier goes away. So you don’t have to sit there time and time again, doing a stock screen, or, you know, fiddling through a news feed for an hour and a half to keep up with what’s going on with your existing investments. We just want to streamline at all we want to give superpowers of investment research to an average person. So we started, you know, this process back in 2019. And it took several years to get it right. Part of it is built on historical academic models of others across the world that have studied, you know, how events impact share prices, some of them are original to us, others, you know, belong to hedge funds that we knew, use some of these event driven strategies and said, You know what, we could do this within our platform, let’s just put that on there. There should, shouldn’t need to have $10 million, you know, to be able to participate in the market. And so we saw subscription costs, very, very low, it’s the equivalent of $19 a month as our starting point. And then it goes up to 167 a month, depending on the tier that people are subscribing for, and the level of information that they want. But it makes it unique, more accessible to more people. So that you don’t have to rely on television stations, which frankly, are very often helping to push a narrative or push a particular stock, right? It’s often that these large asset managers are selling shares while they’re on TV talking about how great stock is because they need to sell 30 million shares. They need, you know, millions of buyers to offload those shares. Yeah,
Gene Tunny 29:54
yeah. So this is a you’re aiming at retail investors so you can Get this on while your browser or your phone, there’s an app for it, I imagine and you said their email alerts, is that right?
Andrew Einhorn 30:07
There’s email alerts. Yeah, we are, you can certainly access it from your phone, we don’t have a specific app, but we have mobile ready. And mobile accessible pages, you can get on your desktop, it’s very easy to use to try to make it as simple as like shopping for a flight on an airline. And unlike even unlike that, where you have to put in your destination, if you want, you can just browse to see, you know, what events that happened recently? And what are the price movements, quickly set an alert, and forget it, you know, and then the alert comes in, it will say, Hey, this is a bullish event. Share price typically moves, you know, X percent over time, or you can look into your own analysis, you know, based on the data that’s in there. So raw, we’ve tried to keep it very, very simple. Good one,
Gene Tunny 30:55
do you have any data on the performance of people who use your platform, or who you who use level fields,
Andrew Einhorn 31:03
we don’t track them. We have regularly, you know, get feedback, like thanks made a bunch of money on this are 1000 today that was, you know, bang for my subscription, 10 times, we do have a level we call it level two service. This is more of our white glove service where we have analysts that monitor the AI alerts. And they kind of cherry pick the best ones, and we’ve sent it out. And it’s really for people that want a little bit more help picking out your entry and your exit point that that service really outperformed our expectations. We we looked at the closed alerts for our first year of operating that and the return was 2,800% cumulative over the course of the year.
Gene Tunny 31:53
Right for the cherry picked alerts. Right. Okay. Do you have any data or any? I guess it’d be a very difficult thing to do. But of all the alerts, I mean, are you giving explicit bias buy or sell recommendations on with these alerts? Or are you just saying this, you should be paying attention to this?
Andrew Einhorn 32:14
Well, it will say, you know, this is a bullish event than in a bullish event, the share price goes up, right, so I tell them to buy, but it will say the share price is gonna go up, you can do whatever you want with that information, and it’s gonna go up by 3% in the first day, and then you know, 75% of the time by day 10, it’s going to be up this much. And so it’s really your job as the investor to say you how you want to play it, we have all types of users of the system, some will just buy it and make a quarter percent every single day. And others want to be able to just find the event that’s going to be up, you know, 100%, and they’re okay, waiting all year for two or three of those, which they do happen. They have others who have a lot of stocks in their portfolio. And what they’re looking to do is just find opportunities to make more money off the stocks that they have. So if they own apple, and Apple has a positive event, they get alerted to that. And they might sell an option contract for extra premium when this bullish event happens. Knowing that on day two, according to the statistics, that particular event actually pulls back to where it was people started to sell. So, you know, we’re we’re not trying to create the strategies per se, for folks, they’re there for the taking. And there’s a lot of guidance on the system. But the data itself is very revealing. It’s like, okay, if you knew every time you walk out the door, what the weather is, like, you know how to dress. This is the same thing. Like, you know what, what to do when these events happen. And that’s been a lot of the problem in the market is often people overreact, because they don’t know how bad the bad news is. They don’t know how good the good news is. And you see this like massive overreaction, you know, 2021, the whole year, but you see it all the time, you know, bow past where it’s supposed to be and then eventually pulls down and people get hurt because they buy at the top, and then they start selling on the way down and then stock goes back up. So, you know, it’s just as much about avoiding bad decisions, as it is finding good investments. And some of the events that we put on there we know, are 5050 they could go either way. You know, there’s a Tesla one on there as an example, and test the product launches. There’s a lot of traders that like to think, oh, every time there’s a new Tesla product, of course, Tesla’s gonna go up. It’s not true. After time goes down. And we we’ve gotten criticism for putting that event type on there. They’re like, well, like Can’t really trade this is 5050. And we’re sort of saying, well, that’s the point. Stop making bad decisions. That’s what we put it on there. So I knew it was like flipping a coin. Yes. Good point. Can I ask what? What markets you and you mentioned, you’re in, so equities in the US and there was what over 6000 companies on? Was it on the s&p. So New York Stock Exchange, Stock Exchange? Yep. Anything traded on the New York Stock Exchange anything on the NASDAQ, and we have some of the larger companies on the OTC so that includes foreign companies that have ADRs that trades in the US, it also includes, you know, the OTC Markets, which are some of the bigger European companies, like Volkswagen, is there. Yeah.
Gene Tunny 35:52
Okay. So just in equities? Are you in fixed income in bonds at all? Now?
Andrew Einhorn 35:57
Not yet, we’re just sticking to straight equities at the moment, although we do have a lot of option traders that use the platform to inform, you know, their particular option trades. Gotcha.
Gene Tunny 36:09
Okay. So as your competitive advantage, you’re getting this information quicker, because you’re getting a you’re looking at these reports that other analysts may not you’re getting a feed? Is it? Is it an API, you’re tapping into an API to get these reports? And then you’ve got the, the AI that analyses them all? Quickly? And there’s some AI magic there, it’s a neural net or some or something? Is that what is that what’s going on? You’re able to get this information in your Hoover it up, analyse it extremely quickly, and then push out the the advice is that essentially, what it’s about, in
Andrew Einhorn 36:51
a way? Yeah, I mean, it’s not necessarily a speed issue. You know, we certainly try to get the information as fast as we can. And largely, we get it within 45 minutes of an event taking place. Or being announced. We get the information ourselves, which means we data mined it ourselves, we pull it in, and we have it. And what the AI is really doing is it’s like a speed reader. So it’s reading 30,000 documents a minute. Yeah, okay, you just got through 30,000 reports. And then within that extracting 21 million events per year. And then looking at a group of events, saying okay, of these 21 million events, which ones actually move the share price and which ones don’t matter. And so then it’s selecting out about five or 6000 events that are known. We call them material events in their material to the share price movement. Once that happens, we’re then identifying what company had that event, pairing it with real time price action from the markets, to then correlate whether or not that particular event has had an impact on that particular equity. And then as we do that, for groups of events, let’s just say, you know, CEO departures, we have every CEO departure in an aggregate data set. And then you can look and say, Well, how to co departures, typically affect share prices, and it’s one click away. And there’s summary statistics that will show you okay, it moves in 4%. And it’s usually a bullish event. And then you can filter that information if you want. So, you know, is it the same cases in energy companies, as in tech companies? Is it the same case in large tech versus small tech, which is not the same case. So very quickly, you can kind of see, you know, with a couple filters, what’s going on there. And now that we have the data, yeah, you can get alerted to it. And you can act on it, if you want to trade it. Or you could just use it to do faster research. You know, by having all that you don’t have to read all that information yourself, because you just knew you now know what the main events are. For the equity that you’re doing research on, let’s see, pull up apple. In the platform, you put Apple Company page, and then you pull up a chart. And typically when you look at a stock chart, its ups and downs, ups and downs. Don’t know why it’s ups and downs, right? We’re just looking at it. And then normally, you would have to say, Okay, why did Apple drop 20% On this day? Let me go to look at a news feed. Let me go to the day of the news and look at the, you know, 300 articles that were about Apple that day and try to find information that would tell me why was it down 20% In this one day, you no longer have to do that. Because right on our charts, we have the event appended there that move the share price. And so you save yourself all that hassle all that time as you look at In Apple graph, you know, there might be 20 events, and each event is right before all those big movements on the graph, you can look at it that way, you could just scroll down the screen and see a list of all the recent events that Apple has has happened product launches, buybacks, dividends and so forth. And you just get within 15 seconds of view of, you know, what are the recent things that have happened to this company. And a lot of that is, is missing from the market today. Because if you were to go to something like a typical stock screener, and your brokerage system, and you’re gonna go, oh, I want to find out, I want to find a stock that has a great dividend, right? You’ll find these companies that have a 12% dividend. And you got to then then your research really begins because you get to find out, is there a weird reason why they have a 12% dividend, and then you pull up the share price? stock chart, and it shows that it was $60. And now it’s a $20 stock, which is why the dividend is now 12%. But why did it drop from $60 to 20? Now you have to go and do that research on our platform, you know, we would tell you, hey, you know, they’re filing for bankruptcy. You don’t need to do any research like that. But then it’s still what it is, they haven’t got it yet. So it’s time savings. It’s finding it investments, monitoring the market at large, setting your research process to be automated, but he’s AI search agents that you can use out of the box that we have or customised yourself, and really just see a lot more of what’s going on in the market and why it’s moving the way it’s moving. Right? So
Gene Tunny 41:43
you say AI search agents, out of the box that you have? Is this stuff you’ve developed? Or you’ve you’ve licenced from somewhere else?
Andrew Einhorn 41:54
No, we build everything from scratch, build everything. Right? Okay. So
Gene Tunny 41:58
you’ve How long have you been going have you been going before GPT and the GPT 3.5, for
Andrew Einhorn 42:06
where we started in 2019. Although I will say we had a company before this for 10 years that we operated, which also was an event monitoring system of sorts. Our client base was actually the publicly traded companies. And so the software system we built in that company did similar monitor events for large corporations. But it wasn’t geared towards investors, it was geared towards the public relations professionals that publicly traded companies. And so we’d see these patterns, and that, you know, something bad would happen, like if it was a train company, that train would come off the tracks for ash into a river or spill pollution, then the share price would plummet on the stock. And they would lose billions of dollars in market cap. And this would happen again. And again. And again, you know, same same type of event, same type of company. In other situations, you might have, you know, a data breach, like a cybersecurity data breach, then the company’s share price would fall. And so our software monitor that, and would send alerts to the corporate affairs and corporate communications people and they would get up in front of the podium where they would get the press releases out. And they would say, well, this wasn’t our fault. You know, they was actually the oil company that overloaded the train. And they would try to shake, save the share price by kind of blame. And so we have a lot of experience in that for 10 years. And then, you know, during that time, we’re like, maybe we on the wrong side of this issue, you know, we’re saving these people, billions of dollars a year. Maybe we should be using, you know, our knowledge and events to help make investments. And we sort of put that aside for a little while, sold the company and then started a new company and started checking with different ideas of what we could do with AI and how do we prove what we did the last 10 years. And then COVID hit in 2020. And it was like Aha, events, events, change everything that’s focused on events.
Gene Tunny 44:09
I do and day they’re doing day. You’ve got a fascinating backstory there. And I might, I’ll link in the show notes to a interview you did with on the side hustle city podcast, which was really good interview. And yeah, you told the full story and how you did consulting work for the Pentagon. I think it was and and then yeah, yeah. And your management, did management consulting, you did a grad, you did graduate studies at George Washington, if I remember correctly. So you’ve got an academic background, too, which is great. Yeah, so I’ll put a link in the show notes to that. I’ve just got a couple more questions. I’m wondering about hedge funds because one thing, some of the points you’re making, I’m thinking of that’s similar to the Ray Dalio Philosophy of because he’s he’s very interested in history and looking at how historical events played out and learning from those learning from events in the past. Imagine something, you know, Bridgewater or other hedge funds around the place, they must be interested in this sort of thing. Are they? Do you have any hedge fund clients? Are they like competitors of yours? Or how do you see? How do you see the other financial market players?
Andrew Einhorn 45:25
We don’t have a hedge fund clients, we certainly have some that have come to us. I don’t know if they’re pretending to be client or wanting to be a client, but they’re certainly interested in our methodologies and technology. I think, you know, just like any new tech in the market, you’re going to piss off some people. Have they cornered? And, you know, we’re trying to give some of these strategies to the general population and democratise access, and not everyone likes that. So we’re expecting it, you know, and the right now, you know, we’re for a self directed investor construct. The platform says it’s for personal use, commercial use, you know, will we make an API, you know, that can be accessed in the future? For certain types of data? Maybe, you know, we’re we’re looking at different ways that we could look, take our massive amounts of data that we have, and kind of enable different levels of processing of that data set. So yeah, I mean, it’s, it’s it’s an interesting marketplace, and that there are a lot of different strategies that people are deploying, there are large firms that have event driven strategies, some of them are fairly straightforward. Some of them are complicated. And it is a factor of historical information. But how you can utilise these patterns in the market to make better investments to make quicker money. I mean, the most famous trade in the world at this point was Bill Ackman straight during COVID, where he shorted the market while being on television, telling everybody to panic on CNBC, and made, you know, a couple billion dollars on that market short. And so the fund returned something like 75% that year. So when you can do those massive trades, then it’s great. You know, why? Why would you sit in the market all year, and watch, you know, these constant ebbs and flows of events, change the trajectory, or you’ve got wars that are breaking out, we have, you know, freighters that are being shot at oil prices are up, oil prices are down to nothing like you can’t, you know, and then you’re trying to be an investor and buy and hold philosophy, and then maybe you got a gain or you lose for the year, it doesn’t make sense to sit there forever, when you can just make that in a short period of time, hang out in cash at 5% yield, and then go back into the market when it’s safer. So our kind of method, or general philosophy really puts the buy and hold method on notice. And raw calls BS, okay, and says, you know, what, buy and hold is great if you’ve got the greatest stocks in the history of the market. But most of the time, it doesn’t work out so well. You know, GE, was the biggest stock in the s&p 500 in 2002. Now, it’s below where it was trading 20 years ago, that you’re buying and holding, you’re constantly losing money for two decades. You know, likewise, if you were to buy the s&p 500, in 2000, you would not make a single dollar until 2013 13 years later. So yeah, there’s a lot of these market myths about how long you should be holding and, you know, dollar cost averaging and things like that, that are that are kind of baked in narratives pushed by asset managers, banks, so you keep your money parked with them, and they can make money off your money. Yeah, look,
Gene Tunny 49:19
I think you make a lot of good points there, we might have to have you back on the show served over the future to have to have this discussion. Because I mean, I’m, as an economist, I am sympathetic to the view of, you know, just, you know, it’s time and time and time in the market beats timing the market, if you know what I mean. So I’m sympathetic to the view that the best thing you can do is just, you know, invest in the index and just let it grow over time. But I have to I do take your points. I don’t want to have a I don’t want to debate it out now. But it might be good to have a discussion in the future because I think it’s yeah, it’s a really important issue that you’re getting out there in terms of how we think about Investing.
Andrew Einhorn 50:01
Oh, yeah. And you know, I would just add that the argue, but it depends on your timeline. Right. Like it’s great. Yes. He’s got unlimited time. Fantastic. Eventually it’ll be right. Yeah, someday. But for a lot of people, they need to access their money. It’s an unreasonable assumption, you know that you’re not going to touch your money for 20 years.
Gene Tunny 50:19
Yeah. Yeah. I think one of the points. Yeah, it’s, it’s a, it’s an important point you’re making and I mean, one of the challenges like in Australia here, we’re we’ve moved towards individual retirement accounts, we move toward that in the 90s. And so a lot of people ended up, they’re relying on Super, and then, you know, what happens if you’re a retiree? And then, you know, the market goes down? 40%, like it did in the financial crisis, right. And then yeah, I mean, it’s
Andrew Einhorn 50:49
bad times every time when you’re 78 years old.
Gene Tunny 50:53
Yeah. People ended up having to keep working for for several years. But yeah, that was a that was an awful event. Right. Yeah, that bill, that was it. Bill Ackman. You mentioned with a, I’m gonna have to look up that. I mean, that’s outrageous. And that’s why, you know, that’s what outrages the public about, you know, the activities on Wall Street’s I remember seeing
Andrew Einhorn 51:14
it live. I mean, he just, he scared the hell out of me. When I was watching TV. I was like, I didn’t think it was gonna be this bad. But now I do. Yeah. Shocking. If you just Google greatest trade of all time. Yeah. You’ll you’ll see the data sources on it. But you know, the fact is, was that a lot of this stuff, that historical data gives you plenty of ammo for how to navigate the markets, for instance, the look back at Zika and SQL, but yeah, that was spreading and in 2016. And they closed the ports of Miami. And the cruise ship stocks, on average dropped about six and a half percent when they close those ports. COVID had a transmission inside the country for the first time in the US, I think it was in Houston. And cruise ship stocks went down six and a half percent. Same reaction to the virus just seven hours later. So there’s always historical reference. And you gotta remember that the people who are moving the markets are also looking at the history of
Gene Tunny 52:21
IT. Yeah. People like Ray Dalio is crew at Bridgewater. Yeah, absolutely. Very good point. Right. Final, final question. I just want to ask you, like, what’s the reaction among the financial establishment to this approach? Because there’s a, I was just wondering about it, because there was a very negative opinion piece by Gregory Zuckerman in the Wall Street Journal last year. So April 12 2023. Ai can write a song, but it can’t be the market quants have tried for decades with limited success. At the biggest challenge, all very negative about it. I mean, how do you react? What do you think about what do you think about that? I mean, what’s the what’s the reaction out there to what you’re trying to do?
Andrew Einhorn 53:12
Well, there’s there’s two questions there. The first is, you know, the, the article itself, I think is, has a little bit of a misnomer about what AI is, and only is right, there’s this belief that AI is sort of the profit, right, it’s sort of the crystal ball that can see the future because it’s, you know, super crunching all these numbers and coming up with perfect algorithms that humans can’t possibly imagine. And there are certain people that are working on that. But largely, that’s not what AI is, AI is, for the most part, replacing kind of grunt tasks that we don’t want to do anymore. Things that humans can do, the computers can just do faster and at scale. And so you know, when you say something like aI can’t beat the market, but it’s really saying is an AI created algorithm to beat the market won’t beat the market. And there’s been very little development of sort of AI generated algorithms. It’s usually a human using AI to crunch numbers and then coming up with the algorithm that it then allows AI to execute. So the human is integrated through the whole process. And just by that biassing, the outcome of this, you know, assessment. I would take the view that, you know, AI is a tool in the toolbox of doing whatever you want to do much like a hammer versus a power drill. Difference. Yeah, you know, you could go hammer out the nails, or you could have a nail gun. And the AI is the nail gun for most tasks. And so if you’ve got a nail gun, you’re gonna get your job done faster than the guy that’s sitting there. with a hammer, gotcha.
Gene Tunny 55:00
Yeah, yeah. Okay, so all fascinating. Andrew, really, really enjoyed the conversation, are you looking at extending into, say, Australia or the UK because your us focused or have I got that wrong, where
Andrew Einhorn 55:14
us focus, but we, we actually collect data in about 35,000 different equities. We’ve just been rolling out, kind of slow and steady to make sure we don’t overwhelm the user. Those stocks do include Australian stocks, they do include, you know, the London Stock Exchange. So, you know, if demand is high enough, we’ll provide access to that and the same model. A lot of the large stocks, you know, it’s in both of those exchanges, like AstraZeneca, for example, or, you know, forget big mining companies that are ADRs that do trade in the US. Trade in the US market, I was trying to remember what the big mining companies in Australia but not remembering Olga bhp,
Gene Tunny 56:01
Rio Tinto, so yeah, so
Andrew Einhorn 56:05
those are in the system, you know, as an example, okay. Because global again, and you know, anything above generally, about $10 billion market cap is going to be traded in the US exchanges. Gotcha. Okay.
Gene Tunny 56:19
Excellent. All right. Andrew, on hold, this has been terrific. Any final points before we wrap up,
Andrew Einhorn 56:25
I would just say, you know, if, if you’re interested, and you’re out jogging, or you’re working out at the gym, while you’re listening to this, the company name is level fields, AI, you know, text yourself, write it down. If you don’t feel like you can use it for your own investments, you probably know somebody that might please get the word out. We have a discount code of podcast 23 that you can apply. And you can get a discount on this subscription. Rod. Is
Gene Tunny 56:56
that all caps? So
Andrew Einhorn 56:57
does it matter? It doesn’t matter? No. Okay, excellent. The number 23 for level fields
Gene Tunny 57:03
mastering Okay, enter on well, and thanks so much for your time. I really enjoyed the conversation. And yeah, I really learned a lot. And for sure, this is this is part of the, the way of the future. So it’s fascinating to learn what people are doing out there like yourself. So all the best with it in the future. And I look forward to seeing more of what you’re doing in in future years. So thanks so much.
Andrew Einhorn 57:29
Thank you. I appreciate having me on and happy to come back and have that buy and hold debate. Good
Gene Tunny 57:35
one. I think about that for sure. Okay. Thanks, Andrew.
Andrew Einhorn 57:38
Thank you,
Gene Tunny 57:41
Rocco. Thanks for listening to this episode of economics explored. If you have any questions, comments or suggestions, please get in touch. I’d love to hear from you. You can send me an email via contact at economics explore.com Or a voicemail via SpeakPipe. You can find the link in the show notes. If you’ve enjoyed the show, I’d be grateful if you could tell anyone you think would be interested about it. Word of mouth is one of the main ways that people learn about the show. Finally, if your podcasting app lets you then please write a review and leave a rating. Thanks for listening. I hope you can join me again next week.
58:28
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Credits
Thanks to Obsidian Productions for mixing the episode and to the show’s sponsor, Gene’s consultancy business www.adepteconomics.com.au. Full transcripts are available a few days after the episode is first published at www.economicsexplored.com. Economics Explored is available via Apple Podcasts, Google Podcast, and other podcasting platforms.
