Short answer: Jordan Metzner says he pulls prices from Polygon about every fifteen seconds to avoid Public rate limits, with Public as backup, then prompts ChatGPT with his portfolio and aggressiveness. Emily Kurtz says this is not investment advice.
Watch this answer from Episode 8 (starts at 7:00) · Episode 8 notes and transcript
From Episode 8: Can Public Make You a Better Investor?, starting at 7:00.
Emily Kurtz [6:59]: Well, Jordan, I love this. This is awesome. Obviously, you're pulling in from Public's APIs, portfolio orders, history, etcetera, but it also seems like you're piping in from other data sources that Public doesn't yet have available via APIs. So some of the potentially predictions, it sounds like maybe on the analytics side, you have some stuff around its ratings, performance, analyst reports, etcetera. So can you speak to sort of what else you're using?
Jordan Metzner [7:26]: I didn't want to be overly aggressive in the rate limits on calling the API for pricing too aggressively. So I found a public API that was free that I could call, like, every fifteen seconds to get the price called Polygon. So I chose that to get the price. And if I run over my rate limit, I have backup as public as my backup. So I get the price about every fifteen seconds. And then we use ChatGPT APIs all the time. So I created a new API key with ChatGPT. I created a public API key as well. And then I created a prompt basically kind of going through ChatGPT, telling it where I was, what my aggressive levels were, what my portfolio was at. And since we're only trading one stock, it's pretty easy. I'm I'm sure like this would get infinitely harder as you started to trade more and more stocks. But in theory, you could paralyze it. So you could have a bot that only focuses on each stock and, I don't know how good ChatGPT is at like making money. So it'd be fun to run it, like, for a few weeks to see, like, how well it does. But, you know and especially, like, this stock is, like, pretty highly volatile.
Jordan Metzner [8:33]: So, probably, like, the more volatile it is, that might be, like, better or worse for the returns. And it's hard to say because I really don't know, and I'm not, like, a pro day trader or anything like that. And I just kinda let ChatGPT do its thing. I had the prompt ready, but I don't know where it is now. But, from a high level, I just give it, like, what I have in my portfolio, how much shares I have currently, how aggressive I wanna be, my trading history, and then, like, how much I how much buying power I have and how much money I wanna save and, like, my extra float just in case kind of thing.
Emily Kurtz [9:06]: That that's awesome. And just saying it out loud, obviously, this is not investment advice, but it's fun to be able to show something like this with a more volatile stock since you can really see and showcase algorithm.
Jordan Metzner [9:17]: Totally not investment advice. This is not investment advice. I would not trade real I would not trade real money at scale using this algorithm, but the cool part is you could trade it against the history and you kind of see how well it would perform. It'd be good to at least inform traders on whether or not there'd be an opportunity to make a trade. And I think that's probably, like, the takeaway here is that, you could use it to inform you to decide, like, hey. This is a good opportunity to come in or maybe a good opportunity to come out.
Emily Kurtz [9:42]: Exactly. We talk a lot about trigger based trading. Right? When a price hits a high or a low, when it grows by x percent, and so all of those things are really helpful. Maybe an inflation report and economic report, etcetera. And so being able to sort of trigger trades based on things is exactly what you're showcasing and something a lot of our customers, like and expect. Another question for you is, like, obviously, you built this with a bunch of REST APIs. How would this evolve, change if you had WebSockets for prices or WebSockets sockets for order updates?
Jordan Metzner [10:14]: Yeah. So, I mean, the more streaming, the better, I think, because, like, then we can stream the price rather than call the price without rate limits and things like that. So it just allows the entire thing to be smoother and smoother. One thing I think I was gonna ask Jake about, I just chose ChatGPT, like, the newest API as, like, the API of choice, but I don't really know enough about does Gemini do a better job at kind of financial analysis for trading? Or does Claude, Opus or Sonnet have, like, better analysis for trading? So that might be another, like, weighted thing to do would be is, like, see if you could have it run against multiple models and get their feedback and try to do some consensus. I think if I was able to stream, I'd be able to do, like, more trades even faster. I also presume the cost of trading is zero. And, it is, but, every time you're in a trade and out of trade, there is, like, some time that it does take even though, obviously, it's pretty quick. But every trade is an opportunity cost against another trade.
Jordan Metzner [11:13]: Right? So if you're trading in one thing and then something happens somewhere else, and so, again, going back to the simplicity of, like, having only one stock is really easy to follow. When you have a more diverse portfolio, the complexity scales, obviously. Anybody can do this, just this was Replit, just talking to Replit. I probably use ChatGPT maybe to write a PRD or something like that to write a product requirement stock, but, yeah, it's stored on my API keys.
