Transcript
Speaker: Hey everybody, welcome to the Exit Podcast.
Speaker: This is Dr. Bennett.
Speaker: I'm here with Christian from Reposa.
Speaker: Reposa is an algorithmic trading platform that helps people set up essentially trading bots so that they can trade in a more sophisticated way without learning how to code.
Speaker: And I wanted to have him on the show to talk about the fintech startup game.
Speaker: What's it like to...
Speaker: bootstrap a software application like this from the ground up.
Speaker: And he's been at it for about a year.
Speaker: So it's an opportunity to harvest some of those first lessons and learn what that game's like from the inside.
Speaker: So welcome, Christian.
Speaker: Hey, thanks for having me.
Speaker: Great to have you.
Speaker: So most people in this game, either they fall into one of two camps.
Speaker: Either they are just looking for
Speaker: some kind of application that will be useful.
Speaker: And so they're just throwing stuff at the wall.
Speaker: They're trying all sorts of different things.
Speaker: And their goal is just basically to be a tech entrepreneur.
Speaker: They're not like trying to pursue one particular goal.
Speaker: And there's other people who are like,
Speaker: know ever since I was a little boy, I've felt that people needed to have their food delivered to them by, you know, gig economy, you know, whatever.
Speaker: And I'm interested to know of the two camps, which do you fall under?
Speaker: Is this, is this the thing or is this something that you're just, uh, trying out?
Speaker: Yeah, I think I'm more in the latter camp of, I think that this is something that that's, um, I'm personally passionate about, um,
Speaker: Because, so I guess a little bit of my background, you know, I had, I got started trading and investing back when I was 16 years old.
Speaker: So I love the challenge of it.
Speaker: I love the math.
Speaker: I love it when the trade works out.
Speaker: But on the other hand, I'm also a lazy engineer.
Speaker: So I only want to do something once.
Speaker: After I do something once, or if I have some rules or a repeated process, I just want to have a machine that does it for me.
Speaker: So algorithmic and quantitative trading was really natural for me.
Speaker: It was something that I gravitated to early.
Speaker: And I started getting involved in this field shortly after I finished my master's.
Speaker: And I dove into it and began to build my own trading system.
Speaker: So this was back in 2014, 2015 timeframe.
Speaker: And at the time, there were platforms out there like Quantopian.
Speaker: which would give you data and compute so you could develop strategies and backtest them on their systems.
Speaker: They had ideas about open sourcing, you know, quant development so you could submit your strategies to their system.
Speaker: And if they were in the top percentile, I don't remember if it was top five, top 10, top one, something like that, they'd choose it and trade it for a certain amount of time.
Speaker: I think typically it was like a month or so.
Speaker: And then they would give you a cut of the rewards.
Speaker: And, um,
Speaker: start playing around with this to just kind of get my feet wet and start playing with this and i was like oh i love this this is a lot of fun i can trade i can set up a machine that does it for me the math is is really cool you know so for me just for uh listeners you know my background i've got a phd in uh focused on optimization and machine learning so i love all the geeky nerdy math stuff that's uh you know kind of where that that's my background and i feel totally comfortable there but
Speaker: When I got involved with some of these things like Quantopian, I didn't stick there very long because it was a lot of work and very little reward comparatively to working my day job.
Speaker: You could be capped at, I think it was $5,000 a month and it wasn't guaranteed because you were always in competition with everybody else.
Speaker: So you could use these algorithms and develop them, but they weren't running on your own accounts.
Speaker: It was running on their accounts for their customers.
Speaker: And so- Just doing this from their end because they're just crowdsourcing this brilliant, brilliant,
Speaker: these brilliant algorithms.
Speaker: That's like with, I mean, like you're taking less risk because it's not your money, but at the same time, it's like you're giving away a huge amount of value.
Speaker: Right.
Speaker: And they had thousands of people working on this to try to develop a lot of these algorithms so that they could turn around and sell that to their institutional investors and clients and manage their money.
Speaker: So they would
Speaker: try to run it.
Speaker: Now, they shut down a couple of years ago, I think in 2020, they wound up closing down because they weren't able to make it a profitable business model.
Speaker: But yeah, that was the whole pitch is you don't have to worry about this, you know, be in the top, we think you're smart, we think you're smart.
Speaker: So let's see what you can do.
Speaker: We'll give you all the tools and let you go and run and try to make something work.
Speaker: At the end, it didn't, but they had a good run at it for eight, nine years, something like that, of actually putting some of the software out there and other things.
Speaker: But that's really kind of where I got my feet wet, running in this space of algorithmic trading and thought, man, this is something that's really cool and a lot of fun for me to do.
Speaker: So I took some of my learnings there and started to actually apply that to my own accounts and started building my own systems and run from there.
Speaker: So the advantage to this process that you've developed is that you don't have to learn how to code, but you do have to learn quite a lot about trading.
Speaker: And so you're targeting a particular type of person who doesn't have the code skills, but has like these finance quant skills.
Speaker: Or are you trying to like educate people who maybe don't have that kind of knowledge into a place where they can kind of build their own bots?
Speaker: Like who's your target customer?
Speaker: Right.
Speaker: Ideally, we'd like to go after people who are trading according to trend following principles.
Speaker: They consider themselves trend followers.
Speaker: And the way I like to think of it is I like to break down all of trading,
Speaker: into two broad categories, trend following strategies and mean reversion strategies.
Speaker: So the basic idea behind that is that trend following, or sometimes called momentum trading, is basically when something moves in one direction, you want to jump on it and follow that momentum effects all the way through.
Speaker: So you can get these really big moves like Tesla or Bitcoin or some of this other stuff that's been making headlines over the past few years.
Speaker: either long or short, and be able to just ride a trend for a long period of time.
Speaker: And you can do shorter term or longer term trend following.
Speaker: We can talk a little bit about where I think most retail and individual investors should be.
Speaker: But the other side is mean reversion, where essentially you see something that you think is going to be overbought or oversold.
Speaker: It reaches to a high or a low within some type of range, and then you take the opposite position.
Speaker: So if it's really low, then you try to buy low and sell high, or you short it when it's high and try to cover your shorts.
Speaker: once it moves back, once it moves lower.
Speaker: That's the kind of, those are the two basic paradigms.
Speaker: And so we've tried to build this more for trend following approach because, you know, kind of going back to my experience with Quantopian and getting involved in quantitative finance and trading,
Speaker: I realized that a lot of people were being pushed more towards the short term mean reversion type of strategies.
Speaker: And this is great and all.
Speaker: There's a lot of work there, but it's very crowded space.
Speaker: And part of the reason is that,
Speaker: you know, Quantopian, they were doing like these kind of monthly challenges and want to know what was happening at the end of the month to appease their institutional investors.
Speaker: And that's where a lot of hedge funds are.
Speaker: That's where a lot of the big quant shops like Rentech or Citadel or others, they're focusing on kind of these monthly, getting these great results month over month, quarter over quarter for their investors.
Speaker: So when you start to move down towards those short term strategies, you're playing against those guys.
Speaker: And that's a tougher game to play than if you were willing to move a little bit more slowly and take kind of these longer trends that can develop.
Speaker: Cool.
Speaker: So from an education perspective, from like an investment education perspective, though, are you targeting like intermediate types or like who who's listening to this should be looking into Riposa besides everybody, right?
Speaker: Everybody, of course, right?
Speaker: Yeah, you target everybody and you get nobody.
Speaker: So basically, because I didn't really answer that question very well, but we're going after people who see themselves as trend followers, but maybe they would like to take it to the next level because backtesting is one of the big challenges that a lot of traders run into because they can't code.
Speaker: So they're just basically running strategies in Excel and they can get some rules that they can cobble together from books and from the internet or just trial and error and be able to run something.
Speaker: But what we allow you to do is to actually back test it first before you go and deploy it into the market.
Speaker: You can't really do this on an Excel sheet.
Speaker: You're gonna need to get 30, 40 years of history or whatever it might be, put it into an Excel sheet and then try to manually update things as you go.
Speaker: And so backtesting is just kind of out of the question for most people.
Speaker: You have to know how to code unless you're like super skilled at Excel in a way that I can't even imagine.
Speaker: It's going to be just, it's a challenge.
Speaker: So we have had a lot of people who are trend followers come to us and say, hey, I love this because this fills in that skill gap that I have.
Speaker: I can't code.
Speaker: So I can use your system to actually tweak my trend following systems.
Speaker: And then when I'm happy with it, I can just hit a button and I'll be emailed trade alerts every time.
Speaker: a system is going every time my bot decides to trade.
Speaker: And I can run multiple bots simultaneously, get the emails, and then go enter the trades myself.
Speaker: The future, we'd like to make it fully automated end-to-end.
Speaker: So that's where we're headed.
Speaker: That's on our roadmap.
Speaker: At least for now, we're sending people alerts when they make their trades.
Speaker: And part of this is, you know, we're focused on trend following.
Speaker: So it's a little bit slower than, you know, we can do this on daily data and you can make your updates at the end of the day or early in the morning, the next day before market opens, whatever fits your schedule and go from there.
Speaker: So we're just basically sending our alerts.
Speaker: And so we're trying to target those people who are already interested in trend following and trying to practice it themselves, but really want to expand their capabilities.
Speaker: Now, along with that, we have a lot of educational material and content on our site.
Speaker: We've got 80 or 90 different blog posts.
Speaker: We've started putting tutorial videos and other things like that on the website so that people can learn about different strategies.
Speaker: We show them how to build and use the tools with just a few clicks.
Speaker: We think it's pretty easy and intuitive, but we built it.
Speaker: So we're always trying to refine it to make it a bit easier for people to
Speaker: to work with, put up that educational content so that anybody who's actually interested, maybe trend following or this type of momentum trading is new to you, you can go there and see a couple of videos and then run a profitable strategy and decide, hey, this is something I'm interested in.
Speaker: So you decided to build this, you got started with this after Quantopian failed, right?
Speaker: Well,
Speaker: We incorporated about a year ago, but I had been working on this probably since 2018, 2019, just on the side, here and there and putting some time into it.
Speaker: But as far as the business was concerned, we didn't really get that started until last year.
Speaker: Got it.
Speaker: Okay.
Speaker: And were you consciously like, say in 2018, when QuantToken was still around, were you consciously like...
Speaker: I want to supplant them.
Speaker: I want to replace what they're doing.
Speaker: Or were you thinking like, this is just sort of a, I'm going to swim in different water or what were you thinking there?
Speaker: Um, I kind of wanted to go in a different direction, uh, entirely.
Speaker: So I basically, uh, after my short year or so working on their platform, I had kind of abandoned them and more or less left them, left them behind, uh, because it was just, Hey, I can do this on my own.
Speaker: I know how to code.
Speaker: I can build these systems.
Speaker: I can get the data.
Speaker: And I don't really want to go into this really short term biased area that everybody was kind of being pushed towards.
Speaker: I found that I can be much more profitable as a trader by thinking more long term and by adopting some of these other strategies that weren't really embraced by some of the platforms and some of the quants.
Speaker: Because when you break it down, trend following, you know, this is going to turn to a pitch for trend following, right?
Speaker: is a pretty simple idea, right?
Speaker: You're looking for something that's going to be moving up and you have a number of different indicators that you can use.
Speaker: You can make it really basic, like look at a simple moving average.
Speaker: So if a price is above a long-term moving average, then you basically put a bet down that that's going to continue and you have a stop loss in place.
Speaker: So you take a small loss if it doesn't.
Speaker: And if it does continue, you know, you can get those type of Bitcoin, Tesla moves, those long term Google, Apple moves, other things like that, where you just hold on to it for a couple of years and keep on moving up your stop loss until it closes out and then close out with a profit.
Speaker: If it doesn't work out for you, you have a have a small amount of capital at risk and you move on.
Speaker: So that's how this kind of system works at a high level.
Speaker: And there are a lot of great mathematical properties to it that I like, and it's a bit counterintuitive and so isn't terribly popular, but it's very profitable.
Speaker: And there are tons of people with great track records for it.
Speaker: They don't blow up because of the mathematical properties, the way that you're actually building these systems.
Speaker: So yeah, going in this direction, I kind of abandoned where a lot of the more mainstream quantitative finance stuff was going on the AI machine learning type of approach.
Speaker: I've tried to run those models.
Speaker: I've put those models in place.
Speaker: Very, very difficult.
Speaker: You need a lot of data.
Speaker: If you're going to go towards the high frequency route, you've got to be co-located with servers.
Speaker: It becomes very expensive.
Speaker: Data costs start to shoot up.
Speaker: And it's, again, just a crowded space to play in.
Speaker: So kind of moving away from that into the slower area, I find it to be much easier.
Speaker: more, more comfortable for me personally, because I'm not worried about tail risks.
Speaker: I'm not worried about a lot of the other things that typically hit those mean reversion type of strategies.
Speaker: So when people get started on your platform, is it?
Speaker: Are you are you heart?
Speaker: Well, let me ask you this.
Speaker: So are you harvesting the information that you gleaned from all this back testing for your own purposes?
Speaker: I mean, I imagine you're still gathering tons of useful information from the bots that people create, right?
Speaker: Like, is there a plan to monetize that with your own trading or what are you doing with that information?
Speaker: To be honest, no.
Speaker: I mean, I couldn't care less what people are running on the strategy.
Speaker: We don't look at that data.
Speaker: The only thing that we might look into is if we see that there's some sort of error that's associated with a particular strategy, then we'll recreate it to try to debug it.
Speaker: But we have no intent whatsoever.
Speaker: I think we have it even in our terms and conditions that we aren't going to trade on this information.
Speaker: We're not going to sell it.
Speaker: We don't want to be like a Robinhood or other funds that are taking people's information and selling it without necessarily without their explicit consent.
Speaker: Sure, you click on the terms and conditions on Robinhood or some of these free brokers and you've consented, but who actually reads those?
Speaker: We don't want to do that because we really think that this type of approach is very valuable for a lot of individual investors and we want to try to empower them.
Speaker: We don't want to try to
Speaker: turn around and sell some of this stuff to people who are going to be trading against them or trying to look for those issues.
Speaker: And on top of that, we're quite small at this time.
Speaker: Hopefully that will change in the future, but at least, you know, we're a year old as far as the company is concerned.
Speaker: Nobody's going to be trying to buy our data right now, you know, to trade against it and to look at what those strategies look like.
Speaker: Obviously, we expect that to change.
Speaker: We hope that's going to change as we grow, but it's not in the cards.
Speaker: We go with a subscription model so that people pay for access to the data that we buy.
Speaker: to the platform that we've built and everything that we provide.
Speaker: And that's how we intend to monetize.
Speaker: We don't have any intention whatsoever of selling data.
Speaker: It's interesting as the next wave of tech startups hits the ground, it seems like there is this, at least among the people that are sort of ideologically sympathetic,
Speaker: to whatever extent, that there's this sense of being grossed out by how much data is being collected and monetized.
Speaker: And yeah, I agree with that.
Speaker: I think that's smart to be out front about like, hey, we're just selling picks and shovels.
Speaker: We're not competing with you to find the mother load.
Speaker: That I think is very smart.
Speaker: So how did you build your initial team?
Speaker: Yeah, so basically it's hitting the pavement and working the network, right?
Speaker: So I've been lucky to be at some great CS universities and so have a lot of good coding talent around me and people in my network already that I was able to tap.
Speaker: I have friends and colleagues that I've approached who are working for some of the big hedge funds or big investment banks like Goldman Sachs or Morgan Stanley that ask quants and kind of pulled some of them away to be able to work a little bit here and there.
Speaker: And then some other people who I've worked with are like, hey, this is interesting.
Speaker: This is cool.
Speaker: I'd like to be able to contribute and work.
Speaker: We've got a core team of about five, some other CS engineers, as well as people who have had some more experience working in the financial industry.
Speaker: And so we've been just hard at work trying to get the code up and running.
Speaker: So as of now, everybody's kind of doing it on apart from one person.
Speaker: a part-time basis.
Speaker: We've got one guy who's currently full-time.
Speaker: But yeah, we're bootstrapping everything, right?
Speaker: So we haven't taken on any investment because we want to be able to maintain control.
Speaker: I do get worried about some of the VC plays that kind of go on in the space.
Speaker: And some of our competitors have taken on some decent VC money.
Speaker: to be able to develop their systems and develop their platforms.
Speaker: And yeah, kind of going back to selling the data, I feel like you might be under a bit more pressure to do something like that.
Speaker: When you take on some of that money, you know, you're suddenly...
Speaker: uh in that realm where the big guys are are more aware of you they might want to try to uh speed up growth as quickly as possible at the expense of you know the customer experience uh they might not be in for as long as we want to be running this and providing this service and this capability and we don't just don't want to compromise with our values so we've taken the longer route even though we've had people approach us about hey how could we maybe invest in this how could we partner with you how could we work
Speaker: And we've rebuffed those approaches so far because we really want to keep it.
Speaker: Yeah, we want to keep true to our principles.
Speaker: We're not too worried about the long-term result.
Speaker: We're confident in our product.
Speaker: We're confident in what we're building.
Speaker: Yeah, I wonder if you could say more about the vision that undergirds this.
Speaker: Like, I understand it's a fascinating problem.
Speaker: It's...
Speaker: it's an, uh, an area of, of math and of business that interests you, but I get the sense that there's also this sense of kind of mission behind what you're trying to accomplish here.
Speaker: Could you, could you say more about that?
Speaker: Yeah.
Speaker: Um, absolutely.
Speaker: So, um,
Speaker: got to think of a good place to start with that because there are a number of different ways that we can go.
Speaker: When you look at finance and everything that's happening economically, you do see a lot of manipulation that's out there and it's hard to build trust.
Speaker: Since 2008, obviously, the banks and the
Speaker: brokerages, you know, the big names on Wall Street have come under a lot of fire.
Speaker: Everybody knew that they were sharks more or less, but it's become much clearer, the cronyism and how deeply that runs.
Speaker: And so we want to try to really provide a fintech solution that's very different and apart from, you know, the typical Wall Street group, Wall Street approach to things and really do something that's
Speaker: that stands apart.
Speaker: So we are contrarian.
Speaker: I mean, even the fact that we're building something that's trend following, it's not a popular strategy.
Speaker: It's a, it's a, again, it's a very successful strategy.
Speaker: There are funds that have been doing this for 40, 50 years and have like blown the S and P 500 out of the water.
Speaker: And a lot of the other traditional, um, uh, uh,
Speaker: metrics and indices and other things that you'd look at.
Speaker: But it's still not popular because it's hard to do from a psychological perspective, which I think is part of the reason why it's great to automate it and have a bot do it.
Speaker: They don't have the psychology to work with.
Speaker: So what makes it psychologically challenging to pursue this trend following strategy?
Speaker: Right.
Speaker: Because of the way that it works, it's a bit like fishing.
Speaker: So you are basically putting a worm on a hook and throwing it out there.
Speaker: And anybody who's fished, which it's been a long time since I have, so maybe I'm not entirely accurate with this, but you lose a lot of worms.
Speaker: Maybe it's just me.
Speaker: But you lose a lot of worms in hopes of catching a fish or two.
Speaker: So the idea is that you're putting these small bets at risk.
Speaker: And you're not really too concerned about each individual bet that you make because you're trying to catch a fish.
Speaker: So you'll lose a lot of worms along the way or lose a lot of you'll get stopped out of your trades quite a bit along the way.
Speaker: And so traders have a metric called a win rate, which is basically how frequently you have a profitable trade.
Speaker: Right.
Speaker: It's your batting average for trading.
Speaker: Right.
Speaker: And typically you're in for trend following systems, you can be 30 to 40 percent win rate, which is pretty low.
Speaker: And so that's hard for a lot of people to go through a lot of losing like that.
Speaker: But the reason why you do it is because just like fishing, you're willing to trade all those all of those small, tiny worms for the occasional big fish that you get.
Speaker: And so you have this large, this right tail distribution or the skew, if you want to talk about it statistically, where you have a positive skew of returns.
Speaker: So most of them wind up being losers, but you get a few really, really big winners on the other side.
Speaker: And those few big winners make up for everything and more than compensate for the losers.
Speaker: So this is also part of the reason why I've
Speaker: feel comfortable sleeping at night with this kind of strategy on is because I know that overall, I'm not going to be, even if everything gets stopped out the next day, you know, I'm down, you know, 10, 15% or whatever it might be.
Speaker: You might lose 1%, half a percent on each trade in the worst case scenario.
Speaker: But you're set up in this way so that, you know, you can hopefully get a 200, 300, 400, 500, even, you know, 1500% return, depending on the kind of trade that you have.
Speaker: because you're just trying to get on that trade early.
Speaker: Imagine if you had bought, you know, had a trend following strategy that was following Bitcoin.
Speaker: And depending on where your stops are, you know, maybe you were getting into that in 2014, wrote it up to 20K in 2017 and got out of it around, I don't know, 15, $16,000.
Speaker: I mean, that's a tremendous return.
Speaker: A lot of trend followers who are doing this kind of thing on Tesla had amazing returns.
Speaker: You know, they're basically just throwing...
Speaker: a lot of these hooks out there in the water, knowing that they're going to lose a ton of worms, but they're not worried about it because they know that they'll catch some really big fish in the process.
Speaker: So psychologically, that can be difficult to deal with because you can go through these losing streaks where you check every one of those hooks and it's like, dang it, I lost that worm, lost that worm, lost that worm.
Speaker: after 10, 15, 20 worms that you lose, it can get a bit discouraging.
Speaker: So having a fully automated system that you're just kind of monitoring at a high level, you can endure those drawdowns.
Speaker: You aren't second guessing your rules.
Speaker: You've done the back test, you've done the research, and so you can stick with it.
Speaker: So it doesn't do very well being marketed oftentimes by a lot of the big Wall Street firms because
Speaker: They're focused on those monthly or quarterly returns that they're trying to show investors.
Speaker: But when you actually step back and you look at it from maybe a yearly, you know, a couple of years, five years, 10 years out, this strategy has proven time and time again to actually be incredibly profitable on a compound annual growth rate perspective.
Speaker: Okay.
Speaker: So you've been in this game for about a year.
Speaker: And you just had your first launch.
Speaker: Now, everybody that I've talked to that's in tech basically has said, you know, no plan survives launch.
Speaker: Like there will be changes, there will be hiccups, something's going to surprise you.
Speaker: What has surprised you from the launch of this thing?
Speaker: Right.
Speaker: So, um, even the way that we've approached the system has, has changed because, uh, we launched, um, you know, a little over what, I guess it's about six weeks ago now.
Speaker: And, um, we, we had actually done, had a lot of our marketing around building a more general system.
Speaker: that can handle a wider variety of strategies, and our system still can.
Speaker: But at heart, it was really built for trend following.
Speaker: And so we realized that focusing in and narrowing down on that niche, because it's something that we are trend followers, we like that approach, that's something that we're more comfortable with, and that's something that we kind of built the system.
Speaker: in mind, with trend following in mind.
Speaker: So we narrowed down on our results or on our target market a bit more, which has helped.
Speaker: And that also came from a lot of the feedback from our customers.
Speaker: So we've had to pivot a lot of our marketing material and our blog content and other things to really kind of go down harder on that niche.
Speaker: And that's gotten us some good results.
Speaker: It's gotten us some additional customers.
Speaker: It's gotten us better feedback and really helped out quite a bit.
Speaker: just to go even more narrow than just people who are looking for algorithmic trading, but really focus on trend followers who are looking for algorithmic trading and they can't code.
Speaker: So that's one area that we've focused on.
Speaker: Another, I mentioned my background and
Speaker: is, and everybody on the team really is much more technical in their approach.
Speaker: And so having to learn the skills of copywriting, having to learn the skills of, you know, even just speaking a bit better so that we can get our information out there, video editing, all that other stuff that we're trying to work on and trying to improve has been a learning process.
Speaker: a learning process that's very valuable for us that we're trying to work on and always trying to improve and trying to build the feedback.
Speaker: I'm confident that we can deliver great systems.
Speaker: We can get all the code working.
Speaker: We can do all that stuff and build excellent technical tools from an engineering side.
Speaker: But then it's all the sales and marketing that actually makes a business that we have to work on more.
Speaker: I definitely found that
Speaker: you really don't, you really can't get to know your, well, you can't know who your customer is until you're actually trying to sell the thing.
Speaker: Like it has, it has to be actually in contact with the market in, in communication with, with your prospective consumer before you can figure out who that person is, who that was really going to sing to.
Speaker: If you, if you could do over your development year before you launched,
Speaker: Is there anything that you would have done differently?
Speaker: Anything you would have outsourced?
Speaker: Anything you would have accelerated or decelerated?
Speaker: Yeah, I think we would have probably launched with a more bare bones product.
Speaker: I think that we added some features that are helpful and useful, but they aren't necessarily the features that are really kind of pushing it for the customer.
Speaker: And we would have found that out sooner if we had done so.
Speaker: So I think that...
Speaker: That was a learning that we could have.
Speaker: Yeah, I wish I had a year ago because we held off on launching for about another six months of development time just to just to try to polish things a little bit better.
Speaker: And then when you when you throw it out there and you start getting feedback from your customers and it's very important, like you said, to get feedback from your customers and a customer, somebody who pays you.
Speaker: Not just some random person online who's sending some comments or like asking you some questions about your strategy or about, you know, what your system and your product is going to do.
Speaker: That's all fine.
Speaker: But until they pay for something, they're at the back of the line.
Speaker: And so, you know, getting those customers sooner, even if it's just a handful, even if it's just, you know, a dozen or so customers that you can get and get some real feedback and try to build those relationships and develop that.
Speaker: The sooner you do that, the better.
Speaker: So we would have launched with a more bare bones product, we would have cut back on some of the indicators would have cut back on some of the
Speaker: data sort feeds and other things that we're tying in, some of the different bells and whistles, the nice payment integrations and all the other stuff like that.
Speaker: We've just been like, hey, look, let's just get around to some of these headaches of getting a polished product out there and just get it in people's hands, even if it's not the best thing.
Speaker: And then we can iterate and we can iterate much more quickly and be much more focused instead of trying to cast a broader net.
Speaker: Yeah, I found in several cases...
Speaker: Some people that I have known to be sort of in this analysis paralysis mode or over-engineering or overthinking a product, often it is very much like they really don't know who their customer is.
Speaker: And I can't tell, even if I'm trying to help them figure it out, I'm like, I don't know who your customer is.
Speaker: It's going to have to be attacked that way and minimum viable,
Speaker: is a cliche in this world, like just get to a minimum viable product, but it's so important to start that conversation.
Speaker: And another thing that I'm finding is like, people are sort of like, well, I don't want to be embarrassed by the thing.
Speaker: And I think what they don't maybe realize is how invisible a startup can be on like day one and how like, like hardly anybody is,
Speaker: has any idea what that first couple of weeks is like because you're so little.
Speaker: And so you have this opportunity to sort of test and play around and get things wrong and, you know, maybe alienate a handful of people.
Speaker: But in the scheme of things, the lessons that you learn are so much more valuable.
Speaker: So that's a good insight.
Speaker: Right.
Speaker: And I think that's, it's one of those things that I hesitated even a bit on reaching out to our email list.
Speaker: So that was one of the things that we were trying to build.
Speaker: It was, is a decent email list.
Speaker: And I hesitated because in the back of my mind, I'm thinking, well, you know, I'm not really happy with how this looks.
Speaker: I'm not really happy about how this functions.
Speaker: Sometimes there's a bug here that the backtest fails every now and then, like, you know, 5% of the time, but
Speaker: If we get these people using it, I don't want them to drop the product because it's not working.
Speaker: And you just got to kind of suck it up because you're going to have some errors and you're going to make some mistakes along the way.
Speaker: And so it's better to get those out of the way sooner than later.
Speaker: So even just reaching out to the email list and getting feedback
Speaker: encouraging people to come and try it and to play around with it and to break it.
Speaker: You know, you can learn a lot from that because there were a couple of, uh, you know, minor bugs, uh, none, none were a big deal, but, um,
Speaker: that our users found for us pretty quickly.
Speaker: And so we were able to turn that around and get a better product after just being notified.
Speaker: And they were actually quite happy with that, with getting that feedback and being like, oh, hey, this isn't working.
Speaker: And then within a day or two, it's working properly the way that they expect it.
Speaker: And I think that goes a long way to building customer loyalty and to show them that you're responsive.
Speaker: and that you're really trying to work for them.
Speaker: And that's another thing that, you know, we're really trying to emphasize within the company.
Speaker: It's almost, I think there's an element of fun in feeling like you're building the thing with them.
Speaker: Like, like, I think, I think they get into it.
Speaker: Like, especially in the beginning when you're, you're attracting, I think in your case, probably attracting like quant heavy type people that you already know.
Speaker: And, and it,
Speaker: you give them an opportunity to like kind of put their stamp on it.
Speaker: Like I, I found the thing and I, I, it, and now it's better because I was part of it.
Speaker: And, you know, you give them a deal on the front end, you, you, you, you give them a break on the price and, and it does, it creates this, uh, I'm, I'm, I'm thinking of exit now.
Speaker: Like, uh, you know, we, we gave the, we gave the early adopters a pretty serious discount and, and, um,
Speaker: absolutely invited and encouraged them to constantly give us feedback about what's working and what's not.
Speaker: And I would say 95% of what we do now is a result of that feedback.
Speaker: It has, it has,
Speaker: The initial thing is so different from what it is now.
Speaker: So with that in mind, I wanted to ask you, so you're an exit member and I wanted to learn from you what appealed to you about it, why you signed up and what you've seen in the group.
Speaker: A number of people who are like-minded kind of in their pursuit of freedom, trying to be able to get out of the rat race and just people who are like-minded community of entrepreneurs, people who are builders, doers, not simply just moaners and complainers.
Speaker: Yeah.
Speaker: about everything that's happening and, and, and to be able to, to plug into that.
Speaker: Um, you know, my wife and I, we, we, we've moved a lot.
Speaker: So we've met a lot of people from all over the world.
Speaker: You know, we moved, um, we lived in Switzerland, the Netherlands, Ireland, Germany, you know, here in the, we moved to the States about four years ago.
Speaker: Um, you know, I grew up here, she's from Brazil, you know, so we know people from all over and, um,
Speaker: it's hard to keep a lot of those contacts going, especially because they wind up, even though they're great people, it's just, you have, you wind up being in touch with a lot of people who are, just because you see them on a day-to-day basis, right?
Speaker: And so getting plugged into a more ideologically aligned,
Speaker: organization that is dispersed and is distributed, I think is helpful for people like us too, because we're on the move quite a bit.
Speaker: And that's just the path we've been on.
Speaker: And so I think Exit fits that niche quite nicely of people who are trying to build something, trying to do something, and not necessarily confined to a geographic location.
Speaker: And so I've gotten some great advice.
Speaker: A lot of people who have provided support, who have given me a lot of good feedback, you know, even just getting the opportunity to come here and be able to talk about my company and other things, you know, is a great benefit.
Speaker: And, you know, some of the things that come out of it.
Speaker: So what is the five-year plan, the 10-year plan, or what is the dream?
Speaker: Like if this thing blows up and goes to the moon, do you want to...
Speaker: run this thing until you retire?
Speaker: What do you, what do you, what's, uh, what's the vision for you, for your life?
Speaker: I would like to get it set up, um, so that I'm a VP in my own company, you know?
Speaker: So I think that there are some times when founders, uh, sit on a company for too long and it, and it outgrows them.
Speaker: Um,
Speaker: you know, if it gets to that scale, then I'm fine taking, you know, a backseat because I don't care for the big bureaucracy that comes with a larger company.
Speaker: Now, when would that be?
Speaker: Like, how big is the company going to be to get to that level?
Speaker: I'm not sure.
Speaker: But, you know, just from reading a lot of entrepreneurs, you know,
Speaker: they might have say a company that's doing 20 million a year.
Speaker: And then they, um, push that to four to, uh, to, to 80 to a hundred million a year, um, just by pouring money in and scaling.
Speaker: And it's just a, it's a, it's, it winds up being a drag on their lifestyle.
Speaker: Now, if this is something that is really popular and it can help a lot of people, I'd love it to get there.
Speaker: Um, but I don't necessarily want to be the one who is, uh,
Speaker: uh, in charge of that.
Speaker: I feel like it slows down.
Speaker: I like being more agile and faster.
Speaker: And so if I can, you know, work with our customers, work with others, um, at that kind of scale, you know, thinking five, 10 years down the road, I I'd be happy with that.
Speaker: Um, you know, as I mentioned too, you know, just the mobility that my wife and I have enjoyed, uh, you know, I like to keep that going.
Speaker: We, we like to travel.
Speaker: We like to move, uh, long-term, you know, just even talking about, um,
Speaker: you know, our goals.
Speaker: We don't necessarily see ourselves staying in the U.S. for a while.
Speaker: I mean, that's where we happen to be at the moment.
Speaker: But, you know, ideally just, you know, having a tech business that can be done anywhere is great.
Speaker: It's a great benefit because it does give you that freedom and that mobility if you so desire.
Speaker: If your money problem is just solved 100% and you can do whatever you want,
Speaker: What are you doing?
Speaker: I mean, to be honest, if it was just solved, I really like, I like teaching.
Speaker: I like teaching people.
Speaker: I like helping them learn in a number of different areas.
Speaker: So, you know, I, you know, helping people with their, with their finances is great.
Speaker: Also just a little bit about me is that I also have a master's in Christian philosophy.
Speaker: And so that I had picked up on the side.
Speaker: And so that's an area that I haven't explored as much as I'd like to in recent years.
Speaker: I loved it when I was involved in kind of those big thoughts and big ideas and reading philosophers, theologians throughout history for the past couple thousand years.
Speaker: But something that, yeah, just life hasn't made time for at the moment, especially running a startup, learning languages, that's something
Speaker: else that I get a lot of weird pleasure from.
Speaker: I speak German, a bit of Portuguese, Swiss German, and I've been really wanting to learn Arabic for a while and haven't gotten back to that in a bit.
Speaker: Okay, yeah, I studied Arabic in school, so...
Speaker: So we'll have to put on... So what we did was we watched Disney movies.
Speaker: They've got Disney movies translated into Arabic.
Speaker: And of course, since you're like... I'm a millennial.
Speaker: So all the Lion King, Aladdin, Beauty and the Beast, you watched those as a kid and memorized them basically.
Speaker: So you know exactly what each line is.
Speaker: And it's really useful to go back and forth to the Arabic.
Speaker: Yeah, I've always found it easy to learn watching kids shows too.
Speaker: So I have a one-year-old daughter now, and so she doesn't get much TV time, but I can at least know all the songs now for stuff that she watches on the iPad on car trips or the airplane or what have you.
Speaker: So that's helped out with some additional Portuguese practice.
Speaker: Right on.
Speaker: Well, this has been great, man.
Speaker: It's great to hear from you and great to have you in the group.
Speaker: The website is riposa.trade.
Speaker: You guys can go check it out and sign up if you're interested in algorithmic investing.
Speaker: And if you want to learn more about what we do at Exit, you can check us out at exitgroup.us.
Speaker: Thanks, Christian.
Speaker: Yeah.
Speaker: And also, if anybody is interested, we do have a promo code available for listeners.
Speaker: If you put exit 22 at checkout, you can get 30% off of your order.
Speaker: So we have a yearly and a monthly subscription available for you, but just put exit 22 in and then you'll get a 30% discount.
Speaker: Thanks, Christian.
