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EXIT Podcast #38: Fintech Startup (feat. Raposa)
980 Plays2 years ago
Christian is an EXIT member who is one year into his fintech startup, raposa.trade, which an algorithmic trading platform that allows investors to create their own trading bots without code. We discuss the lessons of the first year, the surprises that came at launch, and why this project is his dream.
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Transcript
Introduction to Christian and Reposa
00:00:17
Speaker
Hey everybody, welcome to the Exit Podcast.
00:00:18
Speaker
This is Dr. Bennett.
00:00:19
Speaker
I'm here with Christian from Reposa.
00:00:22
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.
00:00:31
Speaker
And I wanted to have him on the show to talk about the fintech startup
Challenges of Bootstrapping a Fintech Startup
00:00:36
Speaker
game.
00:00:36
Speaker
What's it like to...
00:00:38
Speaker
bootstrap a software application like this from the ground up.
00:00:42
Speaker
And he's been at it for about a year.
00:00:44
Speaker
So it's an opportunity to harvest some of those first lessons and learn what that game's like from the inside.
00:00:51
Speaker
So welcome, Christian.
00:00:53
Speaker
Hey, thanks for having me.
00:00:55
Speaker
Great to have you.
00:00:56
Speaker
So most people in this game, either they fall into one of two camps.
00:01:04
Speaker
Either they are just looking for
00:01:08
Speaker
some kind of application that will be useful.
00:01:11
Speaker
And so they're just throwing stuff at the wall.
00:01:13
Speaker
They're trying all sorts of different things.
00:01:16
Speaker
And their goal is just basically to be a tech entrepreneur.
00:01:20
Speaker
They're not like trying to pursue one particular goal.
00:01:23
Speaker
And there's other people who are like,
00:01:25
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.
00:01:32
Speaker
And I'm interested to know of the two camps, which do you fall under?
00:01:37
Speaker
Is this, is this the thing or is this something that you're just, uh, trying out?
Christian's Background and Passion for Trading
00:01:44
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,
00:01:52
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.
00:01:59
Speaker
So I love the challenge of it.
00:02:01
Speaker
I love the math.
00:02:01
Speaker
I love it when the trade works out.
00:02:04
Speaker
But on the other hand, I'm also a lazy engineer.
00:02:06
Speaker
So I only want to do something once.
00:02:08
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.
00:02:13
Speaker
So algorithmic and quantitative trading was really natural for me.
00:02:17
Speaker
It was something that I gravitated to early.
00:02:20
Speaker
And I started getting involved in this field shortly after I finished my master's.
00:02:26
Speaker
And I dove into it and began to build my own trading system.
00:02:30
Speaker
So this was back in 2014, 2015 timeframe.
00:02:34
Speaker
And at the time, there were platforms out there like Quantopian.
00:02:37
Speaker
which would give you data and compute so you could develop strategies and backtest them on their systems.
00:02:42
Speaker
They had ideas about open sourcing, you know, quant development so you could submit your strategies to their system.
00:02:48
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.
00:02:55
Speaker
I think typically it was like a month or so.
00:02:58
Speaker
And then they would give you a cut of the rewards.
00:03:01
Speaker
And, um,
00:03:03
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
00:03:28
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.
Lessons Learned from Quantopian
00:03:38
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.
00:03:45
Speaker
So you could use these algorithms and develop them, but they weren't running on your own accounts.
00:03:49
Speaker
It was running on their accounts for their customers.
00:03:52
Speaker
And so- Just doing this from their end because they're just crowdsourcing this brilliant, brilliant,
00:03:59
Speaker
these brilliant algorithms.
00:04:01
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.
00:04:11
Speaker
Right.
00:04:11
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.
00:04:21
Speaker
So they would
00:04:22
Speaker
try to run it.
00:04:23
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.
00:04:30
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.
00:04:36
Speaker
So let's see what you can do.
00:04:38
Speaker
We'll give you all the tools and let you go and run and try to make something work.
00:04:43
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.
00:04:50
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
Reposa's Target Audience and Trading Strategies
00:05:00
Speaker
for me to do.
00:05:00
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.
00:05:08
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.
00:05:20
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.
00:05:29
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?
00:05:36
Speaker
Like who's your target customer?
00:05:38
Speaker
Right.
00:05:38
Speaker
Ideally, we'd like to go after people who are trading according to trend following principles.
00:05:45
Speaker
They consider themselves trend followers.
00:05:47
Speaker
And the way I like to think of it is I like to break down all of trading,
00:05:51
Speaker
into two broad categories, trend following strategies and mean reversion strategies.
00:05:56
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.
00:06:08
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.
00:06:15
Speaker
either long or short, and be able to just ride a trend for a long period of time.
00:06:20
Speaker
And you can do shorter term or longer term trend following.
00:06:24
Speaker
We can talk a little bit about where I think most retail and individual investors should be.
00:06:27
Speaker
But the other side is mean reversion, where essentially you see something that you think is going to be overbought or oversold.
00:06:35
Speaker
It reaches to a high or a low within some type of range, and then you take the opposite position.
00:06:41
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.
00:06:48
Speaker
once it moves back, once it moves lower.
00:06:50
Speaker
That's the kind of, those are the two basic paradigms.
00:06:53
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,
00:07:05
Speaker
I realized that a lot of people were being pushed more towards the short term mean reversion type of strategies.
00:07:12
Speaker
And this is great and all.
00:07:14
Speaker
There's a lot of work there, but it's very crowded space.
00:07:17
Speaker
And part of the reason is that,
00:07:20
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.
00:07:28
Speaker
And that's where a lot of hedge funds are.
00:07:29
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.
00:07:40
Speaker
So when you start to move down towards those short term strategies, you're playing against those guys.
00:07:46
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.
00:07:57
Speaker
Cool.
00:07:58
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?
00:08:15
Speaker
Everybody, of course, right?
00:08:16
Speaker
Yeah, you target everybody and you get nobody.
00:08:18
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.
00:08:39
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.
00:08:48
Speaker
But what we allow you to do is to actually back test it first before you go and deploy it into the market.
00:08:54
Speaker
You can't really do this on an Excel sheet.
00:08:57
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.
00:09:07
Speaker
And so backtesting is just kind of out of the question for most people.
00:09:11
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.
00:09:18
Speaker
It's going to be just, it's a challenge.
00:09:20
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.
00:09:29
Speaker
I can't code.
00:09:31
Speaker
So I can use your system to actually tweak my trend following systems.
00:09:36
Speaker
And then
Building Reposa with a Long-Term Vision
00:09:37
Speaker
when I'm happy with it, I can just hit a button and I'll be emailed trade alerts every time.
00:09:42
Speaker
a system is going every time my bot decides to trade.
00:09:45
Speaker
And I can run multiple bots simultaneously, get the emails, and then go enter the trades myself.
00:09:51
Speaker
The future, we'd like to make it fully automated end-to-end.
00:09:54
Speaker
So that's where we're headed.
00:09:55
Speaker
That's on our roadmap.
00:09:57
Speaker
At least for now, we're sending people alerts when they make their trades.
00:10:01
Speaker
And part of this is, you know, we're focused on trend following.
00:10:03
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.
00:10:17
Speaker
So we're just basically sending our alerts.
00:10:18
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.
00:10:27
Speaker
Now, along with that, we have a lot of educational material and content on our site.
00:10:32
Speaker
We've got 80 or 90 different blog posts.
00:10:34
Speaker
We've started putting tutorial videos and other things like that on the website so that people can learn about different strategies.
00:10:41
Speaker
We show them how to build and use the tools with just a few clicks.
00:10:45
Speaker
We think it's pretty easy and intuitive, but we built it.
00:10:48
Speaker
So we're always trying to refine it to make it a bit easier for people to
00:10:52
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.
00:11:06
Speaker
So you decided to build this, you got started with this after Quantopian failed, right?
00:11:14
Speaker
Well,
00:11:15
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.
00:11:25
Speaker
But as far as the business was concerned, we didn't really get that started until last year.
00:11:30
Speaker
Got it.
00:11:31
Speaker
Okay.
00:11:32
Speaker
And were you consciously like, say in 2018, when QuantToken was still around, were you consciously like...
00:11:38
Speaker
I want to supplant them.
00:11:40
Speaker
I want to replace what they're doing.
00:11:42
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?
00:11:49
Speaker
Um, I kind of wanted to go in a different direction, uh, entirely.
00:11:52
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.
00:12:04
Speaker
I know how to code.
00:12:05
Speaker
I can build these systems.
00:12:06
Speaker
I can get the data.
00:12:07
Speaker
And I don't really want to go into this really short term biased area that everybody was kind of being pushed towards.
00:12:15
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.
00:12:25
Speaker
Because when you break it down, trend following, you know, this is going to turn to a pitch for trend following, right?
00:12:30
Speaker
is a pretty simple idea, right?
00:12:33
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.
00:12:38
Speaker
You can make it really basic, like look at a simple moving average.
00:12:41
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.
00:12:51
Speaker
So you take a small loss if it doesn't.
00:12:53
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.
00:13:06
Speaker
If it doesn't work out for you, you have a have a small amount of capital at risk and you move on.
00:13:12
Speaker
So that's how this kind of system works at a high level.
00:13:17
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.
00:13:26
Speaker
And there are tons of people with great track records for it.
00:13:28
Speaker
They don't blow up because of the mathematical properties, the way that you're actually building these systems.
00:13:35
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.
00:13:46
Speaker
I've tried to run those models.
00:13:48
Speaker
I've put those models in place.
00:13:49
Speaker
Very, very difficult.
00:13:50
Speaker
You need a lot of data.
00:13:52
Speaker
If you're going to go towards the high frequency route, you've got to be co-located with servers.
00:13:56
Speaker
It becomes very expensive.
00:13:57
Speaker
Data costs start to shoot up.
00:14:00
Speaker
And it's, again, just a crowded space to play in.
00:14:02
Speaker
So kind of moving away from that into the slower area, I find it to be much easier.
00:14:08
Speaker
more, more comfortable for me personally, because I'm not worried about tail risks.
00:14:12
Speaker
I'm not worried about a lot of the other things that typically hit those mean reversion type of strategies.
00:14:17
Speaker
So when people get started on your platform, is it?
00:14:25
Speaker
Are you are you heart?
00:14:26
Speaker
Well, let me ask you this.
00:14:28
Speaker
So are you harvesting the information that you gleaned from all this back testing for your own purposes?
00:14:36
Speaker
I mean, I imagine you're still gathering tons of useful information from the bots that people create, right?
00:14:43
Speaker
Like, is there a plan to monetize that with your own trading or what are you doing with that information?
00:14:51
Speaker
To be honest, no.
00:14:52
Speaker
I mean, I couldn't care less what people are running on the strategy.
00:14:57
Speaker
We don't look at that data.
00:14:59
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.
00:15:08
Speaker
But we have no intent whatsoever.
00:15:11
Speaker
I think we have it even in our terms and conditions that we aren't going to trade on this information.
00:15:14
Speaker
We're not going to sell it.
00:15:16
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.
00:15:25
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?
00:15:33
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.
00:15:43
Speaker
We don't want to try to
00:15:45
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.
00:15:51
Speaker
And on top of that, we're quite small at this time.
00:15:55
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.
00:16:00
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.
00:16:08
Speaker
Obviously, we expect that to change.
00:16:10
Speaker
We hope that's going to change as we grow, but it's not in the cards.
00:16:13
Speaker
We go with a subscription model so that people pay for access to the data that we buy.
00:16:20
Speaker
to the platform that we've built and everything that we provide.
00:16:24
Speaker
And that's how we intend to monetize.
00:16:27
Speaker
We don't have any intention whatsoever of selling data.
00:16:33
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,
00:16:47
Speaker
to whatever extent, that there's this sense of being grossed out by how much data is being collected and monetized.
00:16:56
Speaker
And yeah, I agree with that.
00:17:00
Speaker
I think that's smart to be out front about like, hey, we're just selling picks and shovels.
00:17:06
Speaker
We're not competing with you to find the mother load.
00:17:12
Speaker
That I think is very smart.
Team Building and Funding Philosophy
00:17:14
Speaker
So how did you build your initial team?
00:17:18
Speaker
Yeah, so basically it's hitting the pavement and working the network, right?
00:17:26
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.
00:17:40
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.
00:17:55
Speaker
And then some other people who I've worked with are like, hey, this is interesting.
00:17:59
Speaker
This is cool.
00:18:00
Speaker
I'd like to be able to contribute and work.
00:18:03
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.
00:18:12
Speaker
And so we've been just hard at work trying to get the code up and running.
00:18:17
Speaker
So as of now, everybody's kind of doing it on apart from one person.
00:18:21
Speaker
a part-time basis.
00:18:22
Speaker
We've got one guy who's currently full-time.
00:18:26
Speaker
But yeah, we're bootstrapping everything, right?
00:18:29
Speaker
So we haven't taken on any investment because we want to be able to maintain control.
00:18:34
Speaker
I do get worried about some of the VC plays that kind of go on in the space.
00:18:38
Speaker
And some of our competitors have taken on some decent VC money.
00:18:44
Speaker
to be able to develop their systems and develop their platforms.
00:18:48
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.
00:18:56
Speaker
When you take on some of that money, you know, you're suddenly...
00:19:00
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
00:19:27
Speaker
And we've rebuffed those approaches so far because we really want to keep it.
00:19:31
Speaker
Yeah, we want to keep true to our principles.
00:19:35
Speaker
We're not too worried about the long-term result.
00:19:38
Speaker
We're confident in our product.
00:19:40
Speaker
We're confident in what we're building.
00:19:43
Speaker
Yeah, I wonder if you could say more about the vision that undergirds this.
00:19:50
Speaker
Like, I understand it's a fascinating problem.
00:19:54
Speaker
It's...
00:19:55
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.
00:20:06
Speaker
Could you, could you say more about that?
00:20:09
Speaker
Yeah.
00:20:09
Speaker
Um, absolutely.
00:20:11
Speaker
So, um,
00:20:13
Speaker
got to think of a good place to start with that because there are a number of different ways that we can go.
00:20:20
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.
00:20:31
Speaker
Since 2008, obviously, the banks and the
00:20:35
Speaker
brokerages, you know, the big names on Wall Street have come under a lot of fire.
00:20:39
Speaker
Everybody knew that they were sharks more or less, but it's become much clearer, the cronyism and how deeply that runs.
00:20:46
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
00:21:03
Speaker
that stands apart.
00:21:04
Speaker
So we are contrarian.
00:21:06
Speaker
I mean, even the fact that we're building something that's trend following, it's not a popular strategy.
00:21:10
Speaker
It's a, it's a, again, it's a very successful strategy.
00:21:12
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.
00:21:18
Speaker
And a lot of the other traditional, um, uh, uh,
00:21:22
Speaker
metrics and indices and other things that you'd look at.
00:21:26
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.
00:21:35
Speaker
They don't have the psychology to work with.
00:21:38
Speaker
So what makes it psychologically challenging to pursue this trend following strategy?
00:21:45
Speaker
Right.
00:21:47
Speaker
Because of the way that it works, it's a bit like fishing.
00:21:51
Speaker
So you are basically putting a worm on a hook and throwing it out there.
00:21:56
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.
00:22:04
Speaker
Maybe it's just me.
00:22:05
Speaker
But you lose a lot of worms in hopes of catching a fish or two.
00:22:10
Speaker
So the idea is that you're putting these small bets at risk.
00:22:15
Speaker
And you're not really too concerned about each individual bet that you make because you're trying to catch a fish.
00:22:20
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.
00:22:26
Speaker
And so traders have a metric called a win rate, which is basically how frequently you have a profitable trade.
00:22:33
Speaker
Right.
00:22:33
Speaker
It's your batting average for trading.
00:22:35
Speaker
Right.
00:22:36
Speaker
And typically you're in for trend following systems, you can be 30 to 40 percent win rate, which is pretty low.
00:22:43
Speaker
And so that's hard for a lot of people to go through a lot of losing like that.
00:22:48
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.
00:22:57
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.
00:23:08
Speaker
So most of them wind up being losers, but you get a few really, really big winners on the other side.
00:23:13
Speaker
And those few big winners make up for everything and more than compensate for the losers.
00:23:19
Speaker
So this is also part of the reason why I've
00:23:21
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.
00:23:33
Speaker
You might lose 1%, half a percent on each trade in the worst case scenario.
00:23:39
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.
00:23:49
Speaker
because you're just trying to get on that trade early.
00:23:50
Speaker
Imagine if you had bought, you know, had a trend following strategy that was following Bitcoin.
00:23:55
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.
00:24:07
Speaker
I mean, that's a tremendous return.
00:24:10
Speaker
A lot of trend followers who are doing this kind of thing on Tesla had amazing returns.
00:24:15
Speaker
You know, they're basically just throwing...
00:24:17
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.
00:24:26
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.
00:24:36
Speaker
after 10, 15, 20 worms that you lose, it can get a bit discouraging.
00:24:41
Speaker
So having a fully automated system that you're just kind of monitoring at a high level, you can endure those drawdowns.
00:24:46
Speaker
You aren't second guessing your rules.
00:24:48
Speaker
You've done the back test, you've done the research, and so you can stick with it.
00:24:51
Speaker
So it doesn't do very well being marketed oftentimes by a lot of the big Wall Street firms because
00:24:57
Speaker
They're focused on those monthly or quarterly returns that they're trying to show investors.
Importance of Early Launch and Customer Feedback
00:25:02
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.
00:25:19
Speaker
Okay.
00:25:21
Speaker
So you've been in this game for about a year.
00:25:26
Speaker
And you just had your first launch.
00:25:30
Speaker
Now, everybody that I've talked to that's in tech basically has said, you know, no plan survives launch.
00:25:39
Speaker
Like there will be changes, there will be hiccups, something's going to surprise you.
00:25:46
Speaker
What has surprised you from the launch of this thing?
00:25:50
Speaker
Right.
00:25:50
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.
00:26:02
Speaker
And, um, we, we had actually done, had a lot of our marketing around building a more general system.
00:26:08
Speaker
that can handle a wider variety of strategies, and our system still can.
00:26:12
Speaker
But at heart, it was really built for trend following.
00:26:17
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.
00:26:30
Speaker
in mind, with trend following in mind.
00:26:33
Speaker
So we narrowed down on our results or on our target market a bit more, which has helped.
00:26:39
Speaker
And that also came from a lot of the feedback from our customers.
00:26:42
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.
00:26:51
Speaker
And that's gotten us some good results.
00:26:53
Speaker
It's gotten us some additional customers.
00:26:54
Speaker
It's gotten us better feedback and really helped out quite a bit.
00:26:58
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.
00:27:08
Speaker
So that's one area that we've focused on.
00:27:11
Speaker
Another, I mentioned my background and
00:27:14
Speaker
is, and everybody on the team really is much more technical in their approach.
00:27:19
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.
00:27:37
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.
00:27:45
Speaker
I'm confident that we can deliver great systems.
00:27:49
Speaker
We can get all the code working.
00:27:51
Speaker
We can do all that stuff and build excellent technical tools from an engineering side.
00:27:57
Speaker
But then it's all the sales and marketing that actually makes a business that we have to work on more.
00:28:05
Speaker
I definitely found that
00:28:09
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.
00:28:17
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.
00:28:30
Speaker
If you, if you could do over your development year before you launched,
00:28:38
Speaker
Is there anything that you would have done differently?
00:28:41
Speaker
Anything you would have outsourced?
00:28:43
Speaker
Anything you would have accelerated or decelerated?
00:28:50
Speaker
Yeah, I think we would have probably launched with a more bare bones product.
00:28:56
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.
00:29:05
Speaker
And we would have found that out sooner if we had done so.
00:29:10
Speaker
So I think that...
00:29:11
Speaker
That was a learning that we could have.
00:29:15
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.
00:29:27
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.
00:29:35
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.
00:29:45
Speaker
That's all fine.
00:29:46
Speaker
But until they pay for something, they're at the back of the line.
00:29:52
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.
00:30:03
Speaker
The sooner you do that, the better.
00:30:04
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
00:30:11
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.
00:30:20
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.
00:30:30
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.
00:30:36
Speaker
Yeah, I found in several cases...
00:30:42
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.
00:30:59
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.
00:31:04
Speaker
It's going to have to be attacked that way and minimum viable,
00:31:11
Speaker
is a cliche in this world, like just get to a minimum viable product, but it's so important to start that conversation.
00:31:17
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.
00:31:26
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,
00:31:38
Speaker
has any idea what that first couple of weeks is like because you're so little.
00:31:44
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.
00:31:53
Speaker
But in the scheme of things, the lessons that you learn are so much more valuable.
00:31:58
Speaker
So that's a good insight.
00:32:02
Speaker
Right.
00:32:03
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.
00:32:08
Speaker
So that was one of the things that we were trying to build.
00:32:10
Speaker
It was, is a decent email list.
00:32:12
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.
00:32:18
Speaker
I'm not really happy about how this functions.
00:32:21
Speaker
Sometimes there's a bug here that the backtest fails every now and then, like, you know, 5% of the time, but
00:32:27
Speaker
If we get these people using it, I don't want them to drop the product because it's not working.
00:32:32
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.
00:32:37
Speaker
And so it's better to get those out of the way sooner than later.
00:32:41
Speaker
So even just reaching out to the email list and getting feedback
00:32:46
Speaker
encouraging people to come and try it and to play around with it and to break it.
00:32:50
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,
00:32:58
Speaker
that our users found for us pretty quickly.
00:33:01
Speaker
And so we were able to turn that around and get a better product after just being notified.
00:33:08
Speaker
And they were actually quite happy with that, with getting that feedback and being like, oh, hey, this isn't working.
00:33:14
Speaker
And then within a day or two, it's working properly the way that they expect it.
00:33:18
Speaker
And I think that goes a long way to building customer loyalty and to show them that you're responsive.
Community and Sustainable Growth Vision
00:33:25
Speaker
and that you're really trying to work for them.
00:33:26
Speaker
And that's another thing that, you know, we're really trying to emphasize within the company.
00:33:29
Speaker
It's almost, I think there's an element of fun in feeling like you're building the thing with them.
00:33:37
Speaker
Like, like, I think, I think they get into it.
00:33:39
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.
00:33:52
Speaker
And, and it,
00:33:55
Speaker
you give them an opportunity to like kind of put their stamp on it.
00:33:59
Speaker
Like I, I found the thing and I, I, it, and now it's better because I was part of it.
00:34:05
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.
00:34:13
Speaker
Like, uh, you know, we, we gave the, we gave the early adopters a pretty serious discount and, and, um,
00:34:22
Speaker
absolutely invited and encouraged them to constantly give us feedback about what's working and what's not.
00:34:28
Speaker
And I would say 95% of what we do now is a result of that feedback.
00:34:36
Speaker
It has, it has,
00:34:38
Speaker
The initial thing is so different from what it is now.
00:34:44
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.
00:35:00
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.
00:35:21
Speaker
Yeah.
00:35:22
Speaker
about everything that's happening and, and, and to be able to, to plug into that.
00:35:26
Speaker
Um, you know, my wife and I, we, we, we've moved a lot.
00:35:29
Speaker
So we've met a lot of people from all over the world.
00:35:32
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.
00:35:40
Speaker
Um, you know, I grew up here, she's from Brazil, you know, so we know people from all over and, um,
00:35:45
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?
00:36:00
Speaker
And so getting plugged into a more ideologically aligned,
00:36:04
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.
00:36:15
Speaker
And that's just the path we've been on.
00:36:18
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.
00:36:28
Speaker
And so I've gotten some great advice.
00:36:30
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.
00:36:42
Speaker
And, you know, some of the things that come out of it.
00:36:45
Speaker
So what is the five-year plan, the 10-year plan, or what is the dream?
00:36:50
Speaker
Like if this thing blows up and goes to the moon, do you want to...
00:36:57
Speaker
run this thing until you retire?
00:36:58
Speaker
What do you, what do you, what's, uh, what's the vision for you, for your life?
00:37:03
Speaker
I would like to get it set up, um, so that I'm a VP in my own company, you know?
00:37:10
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.
00:37:18
Speaker
Um,
00:37:19
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.
00:37:28
Speaker
Now, when would that be?
00:37:30
Speaker
Like, how big is the company going to be to get to that level?
00:37:32
Speaker
I'm not sure.
00:37:33
Speaker
But, you know, just from reading a lot of entrepreneurs, you know,
00:37:38
Speaker
they might have say a company that's doing 20 million a year.
00:37:40
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.
00:37:47
Speaker
And it's just a, it's a, it's, it winds up being a drag on their lifestyle.
00:37:51
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.
00:37:56
Speaker
Um, but I don't necessarily want to be the one who is, uh,
00:37:59
Speaker
uh, in charge of that.
00:38:00
Speaker
I feel like it slows down.
00:38:02
Speaker
I like being more agile and faster.
00:38:04
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.
00:38:13
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.
00:38:19
Speaker
We, we like to travel.
00:38:20
Speaker
We like to move, uh, long-term, you know, just even talking about, um,
00:38:24
Speaker
you know, our goals.
00:38:26
Speaker
We don't necessarily see ourselves staying in the U.S. for a while.
00:38:30
Speaker
I mean, that's where we happen to be at the moment.
00:38:32
Speaker
But, you know, ideally just, you know, having a tech business that can be done anywhere is great.
00:38:40
Speaker
It's a great benefit because it does give you that freedom and that mobility if you so desire.
00:38:44
Speaker
If your money problem is just solved 100% and you can do whatever you want,
00:38:51
Speaker
What are you doing?
00:38:53
Speaker
I mean, to be honest, if it was just solved, I really like, I like teaching.
00:38:59
Speaker
I like teaching people.
00:39:00
Speaker
I like helping them learn in a number of different areas.
00:39:04
Speaker
So, you know, I, you know, helping people with their, with their finances is great.
00:39:11
Speaker
Also just a little bit about me is that I also have a master's in Christian philosophy.
00:39:16
Speaker
And so that I had picked up on the side.
00:39:19
Speaker
And so that's an area that I haven't explored as much as I'd like to in recent years.
00:39:27
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.
00:39:36
Speaker
But something that, yeah, just life hasn't made time for at the moment, especially running a startup, learning languages, that's something
00:39:47
Speaker
else that I get a lot of weird pleasure from.
00:39:50
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.
00:40:01
Speaker
Okay, yeah, I studied Arabic in school, so...
00:40:05
Speaker
So we'll have to put on... So what we did was we watched Disney movies.
00:40:08
Speaker
They've got Disney movies translated into Arabic.
00:40:11
Speaker
And of course, since you're like... I'm a millennial.
00:40:15
Speaker
So all the Lion King, Aladdin, Beauty and the Beast, you watched those as a kid and memorized them basically.
00:40:24
Speaker
So you know exactly what each line is.
00:40:26
Speaker
And it's really useful to go back and forth to the Arabic.
00:40:30
Speaker
Yeah, I've always found it easy to learn watching kids shows too.
00:40:34
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
Invitation to Experience Reposa
00:40:48
Speaker
have you.
00:40:48
Speaker
So that's helped out with some additional Portuguese practice.
00:40:53
Speaker
Right on.
00:40:54
Speaker
Well, this has been great, man.
00:40:55
Speaker
It's great to hear from you and great to have you in the group.
00:40:58
Speaker
The website is riposa.trade.
00:41:01
Speaker
You guys can go check it out and sign up if you're interested in algorithmic investing.
00:41:06
Speaker
And if you want to learn more about what we do at Exit, you can check us out at exitgroup.us.
00:41:10
Speaker
Thanks, Christian.
00:41:11
Speaker
Yeah.
00:41:12
Speaker
And also, if anybody is interested, we do have a promo code available for listeners.
00:41:17
Speaker
If you put exit 22 at checkout, you can get 30% off of your order.
00:41:23
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.
00:41:30
Speaker
Thanks, Christian.