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Tasty Trade Inc. is a registered broker dealer and member of FINRA, NFA, and SIPC. Podcast. Boys and girls, what is up? Welcome to episode 198. On this episode is a special guest and someone who in 2018 landed a spot on Forbes 30 under 30 of finance, Christina Chi. In her early 20s, after graduating from MIT, Christina and two classmates, Luca Lin and Jonathan Wang, who had collectively been trading futures from a campus dorm room, founded Domeyard.
It was 2012 and Domeyard was to be one of the few high frequency trading hedge funds. This is a little unique because the majority of HFTs operate as proprietary trading companies. As Christina states during the interview, by all means we should have failed, given the three of them had little trading experience and minimal insight to the hedge fund industry. Not to mention the three had almost no money.
So Domeard is also one of the few hedge funds that went out and raised money from VCs, such as Softbank and Arentec co founder as a necessary means to launch. Now, eight years on, the Boston-based fund is well established and well past the startup phase. Domeyard trades thousands of times daily, sometimes exceeding 10,000 trades across various futures products. And during its biggest single day this year, the funded turnover in excess of seven billion dollars.
This episode includes talk of raising capital, building infrastructure, early hurdles, trading strategies, generating alpha, and plenty more. It was a real pleasure to speak with Christina and even inspiring to hear what her and her team have built from scratch. Uh it's just incredible. So please enjoy. Here is my interview with Christina Chi for episode 198. understand it, you had been trading European futures in the night with two other classmates.
while you were in uh college or university. How did this turn into the bold idea of starting a hedge fund? That's a really great question. We Let's see. Yeah, we were trading from a dorm room and uh you know it was interesting because we were surprisingly doing uh pretty well for uh a dorm room strategy, I guess. I mean, uh we would make uh we were only I think one of our
Uh one of my co-founders, he uh was at Harvard at the time and his roommate there, you know, Harvard has all these rich kids apparently and apparently one of his roommates uh his family runs a hedge fund actually and uh they were able to give us a little bit of capital initially to trade, uh and
It wasn't a lot, you know, it's like a hundred thousand bucks or something, but uh we were able to make about forty thousand bucks, take home forty thousand basically at the end of the day, which was a a lot for a bunch of little kids in a dorm room.
And uh and then we realized, oh, this could, you know, for him he was like, Oh wow, this could be, you know, a a really cool thing to do and um would be really exciting, you know, something that keeps you uh going and keeps you uh, you know, waking up in the morning and uh For me the reasoning was more because I had interned in finance and I had a couple of particularly uh well, one particularly poor experience in the industry where um there is a lot of politics, you know, despite
being a trading floor and most of the results were based on, you know, you're judged based on your performance, but There was still a ton of politics surprisingly. It's amazing how much politics is in every industry. So I was really bothered by the culture and the atmosphere there, the way they treated.
their uh younger people on the team, uh, as well as uh some of the minorities on the team, some of the women and minorities and and I just didn't feel comfortable in that environment and ended up uh you know, for me that was a big part of the reason why I wanted to start off on my own. I don't think I've ever said that in quite that detail before, but um there was a lot of hazing and a lot of behaviors that I just uh you know didn't want in a company.
Uh and didn't want in a daily environment, so decided to start off on our own. Um, you know, I wish I could tell you, Erin, I wish I could tell you, like, oh, this was the best. industry for me. You know, I had researched and read so many books and did all this stuff. Like, no, I didn't I didn't read any I was not an expert in machine learning or high frequency trading or finance at all at the time. It was just purely driven
by uh a desire to to have a company with a better culture on my end and a better, healthier environment. Uh and people always think it's ironic, you know, you're high frequency trading. Yeah, how can you be ethical and and moral? And it's like, well, you know, we've had a really great environment.
for the people on the team at least and uh and we can definitely talk about that more as well. So yeah. So you interned at a couple of different places. You weren't a fan of this. Uh Did your you have two other co founders at Dome Yard, did they have somewhat similar experiences to you? Uh, we all came from different backgrounds. We actually weren't friends before starting the company together, um, but we did have one thing in common, which was the same career goals in mind. Um we all wanted to.
do something, you know, related to finance or fintech and uh all cared about the startup industry as well. So uh we did have different backgrounds. So one of them uh had a more math and physics background and the other one was a computer scientist. And uh but we were all young. We were all inexperienced. So it uh Definitely, you know, it was helpful in certain ways in that we had different skill sets and backgrounds, but also unhelpful in that.
uh we our founding team, we didn't have someone like uh a thought leader in the space, you know, or someone with any amount of experience. So it was really an unknown path that we were kind of going down that we had never been down before. So this capital which you had initially that you were trading around with, um, how were you trading that? Were you using algorithms right from the get go or was it kind of click trading? How were you making trades in European futures?
Oh, it was a great question. I mean, we were literally using like interactive brokers. You know, we had set up some uh, you know, very wonky uh quantitative based strategies. They were still systematic. They still had certain triggers that we would use, you know, we might do
a basic main reversion strategy, you know, or a basic momentum strategy, is things that you um can implement relatively quickly and easily. Uh the holding we were were we intraday? Yeah, we were actually intraday by that time already. Um, but they weren't high frequency in terms of the amount of times they would trigger, you know, it's not that much during the day. So
uh you know it's impossible to create an HFT business overnight or in a dorm room. It's impossible. But we realized that the faster we were, the more of an advantage we would have. And surprisingly the more uh fair of a playing field it was for us, which I know sounds ironic, but, you know, the fact that the only thing hindering us was just being a little bit faster, you know, and uh that we didn't need any
Uh, you know, we didn't need any insider information. We didn't need any uh, you know, kind of broader sources of data rather just market data. That's all we needed. And Uh so that was really great to kind of see and uh we decided, you know, why not continue making this um seeing what we can do on the technology side to improve um the latencies we had.
And back then, you know, we didn't even know we knew it was high frequency trading, but um this was before Flash Boys came out, by the way. So this is before the reputation of the industry tanked. Um, so it was a a different time period, you know, altogether and uh we weren't driven by, you know, really anything that was written in the book because that the book hadn't been published yet.
As you've pointed out, you had minimal experience trading and in finance, like yeah, sure you had a little bit. Um, you also weren't well capitalized. But you had this idea to launch a hedge fund. How did you actually set out to get this off the ground? You're right. We had no money. Uh I also had no credibility and no connections at the time, which was not very helpful whatsoever. Um by all statistic, by all means, we should have failed.
I think we were just driven by passion really was the biggest thing is it just we woke up every day very early and set about doing this and you know, I'd work every waking minute and that that's really what what drove me to to get somewhere, I think. Um there are a couple things we did do differently to um make sure that, you know, we would either have an edge or we could at least maintain some operating runway. One was
raising venture capital, which for a hedge fund is almost still almost unheard of, but it's becoming a little more common. Um, you know, there's uh funds like you know, Quantopian, for instance, back when they had a hedge fund, you know, they also raised venture capital as well to fuel their uh unique fund. We've also done the same thing. We raised venture capital um as well from some great folks in the industry who who believed in us and wanted to maybe pass the baton or
see what we were made of, you know, whatever it was. But um that that support was fantastic. It also gave us the credibility that we didn't have at the time, but you know, desperately needed. So so that was one way that we, you know, went about things. The other was building all of our technologies from scratch as well, which is
both good and bad. Um I don't know if I could really recommend that to anybody today because the the world is a different place than it was even five years ago or eight years ago. It's a different scene today in terms of what the technology landscape looks like. But there was not a lot of high frequency technology out there today. There was not a lot of open source either. So all we could really do is scrap it together, which meant actually the side effect of that is we have our own IP.
Uh we have a lot of value uh valuable stuff in-house that we could always capitalize on one day or you know, maybe we could decide to sell it one day if we wanted to, you know. So that that was really great. Also if something goes wrong, we can go in and fix it ourselves. I don't have to call.
you know, a hotline and wait on the line and stuff. So so that was great. Um, but the bad side, the downside of it is it takes forever. I mean, it was an unknown timeline, an unknown path in an unknown timeline, which is scary but it's like the last thing that you wanna do is not know when you're gonna launch, you know, as a hedge fund and it's it's extremely frustrating. Um
Happy to elaborate on that if you'd like to. Yeah, I'd love to ask you some questions around raising capital and also building out your infrastructure. Uh just before we do though. I have a question about why you were fixated on high frequency trading from the outset.
I wanted to combine finance and technology and didn't even know what fin you know, fintech probably wasn't a thing back then. Uh, but I have a more technical background, same with my co-founders. And uh, you know, during some of my internships we would
basically me, you know, make guesses on to whether let's say we'd guess whether Google stock would go up or down tomorrow. And I knew that wasn't the type of strategy I wanted to do. Uh I wanted to be a little bit more mathematical and uh you know, that's when you figure out, oh, there's, you know, you could do some market making and statar based strategies uh and have a more uh a more systematic approach uh to those strategies. And so so that was the biggest impetus of doing
um, I guess quant and then when we were doing quant we're like, Oh wait, you know, the the faster the the more money we made. And uh I know that sounds like a really I mean, to some people it's a really selfish reason, but um that was really the biggest thing was wow, we could really do this and um and being faster we could really start to compete against the big guys in our space and um, you know, make a name for ourselves hopefully one day. So
That was uh the naive goal back then. Okay. Okay. Now on the subject of raising capital. I guess you kind of explained it a little bit, but I'll just ask you again. Um Why did you need to raise capital and was that capital like the investors' funds? Were they intended for building out your infrastructure and building out the actual fund? Or were they intended to be were those funds intended to be used as trading capital? So I'll answer your second question first, which is
Um, this is meant purely for operations. So uh management company operations like paying for employees, buying software. uh getting data licenses, paying for data feeds, you know, all those expenses that uh and legal fees and, you know, whatever service providers, any kind of expenses that lead up to the launch of the fund itself. I think the other thing is like if we could have raised money if we could have raised enough money in the hedge fund on day one.
Um, maybe we wouldn't have to have, you know, raise venture capital to begin with. Um, and sell, you know, why sell a chunk of your company, right? That's uh pretty risky thing to do. But um we, you know, knew that on day one, given our backgrounds, we weren't even qualified or capable of raising enough money in the hedge fund. And so um the biggest thing we needed to do because we're high frequency trading as well, we couldn't just launch the fund overnight. We had to build
we decided, you know, to build the the order management system, feed handlers, execution gateways, you know, uh market engine simulators, like all those different tools uh pretty much from scratch. And so that was going to take a lot of time and that's why we needed venture capital. We told them we were going to use it to build
those technologies and then eventually, you know, get to a stage where we can launch the fund and raise a separate amount of money for the fund. Um the investors are actually largely separate. There is a little bit of overlap. There's some investors from you know, like maybe firms like Renaissance or somewhere where um they are both uh angel investors and also um, you know, hedge fund investors too. So they might serve two roles. But for the most part, um, our hedge fund allocators are
a very different group of, you know, their fund of funds or family offices, very different group than the, you know, traditional VCs and um, you know, other high net worth individuals that we raised from on the operating side. So um so we did do that and then I forgot your first question. Uh it you pretty much explained it. It was just why did you need to raise capital?
Oh yeah, I mean desperate. We were just desperate for money. I mean right in times like this when everyone's in a crisis too, right? It's like if you if you need the money, um, would I rather own
a hundred percent of a tiny pie or would I want to expand that pie and own a small slice of a big pie. And I was like, well, for my career path right now, you know, I'm not that greedy and I I'm just starting. So I was willing to own a small slice of a big pie if that meant stability for the next couple of years. That's really interesting how there's kind of two classes of investors which are invested in your business.
So you've got the the venture capitalists which were involved in helping to launch the business and then you've got your more traditional type investors who are invested in your trading performance. Is that correct? Right. That's correct. Yeah. So we had two different types of investors. We had the long term venture capitalist. who were in it for the, you know, it's like feels like a marriage, right?'Cause they're in it for like the ten year, you know, six to ten year haul.
Basically. And then there's the kind of shorter term investors on the fund side where, you know, they could redeem any time they wanted to, essentially. Okay. Can I ask you how you secured your first investor? And investor here I'm talking about the VC side of it. Given you had very little track record and, you know, to be honest, not much to show, how were you able to get someone on board? On the venture side is actually easier to answer because the venture side literally
you just go to the startup events and pitch, you know, at those events, usually at the angel and seed stage, people invest in people, right? They shouldn't be investing in numbers like revenue figures because you shouldn't really have any. And if And if they do judge you by that, uh it's a very inaccurate indicator of future success because most companies you look at like Twitter.
or I don't know, Uber, you know, certain companies like that. They didn't have any revenue until much later on. And some of them haven't even you know, a lot of firms haven't broken even yet, even though they've gotten millions billions of dollars in funding. So So it's based on people uh at that stage, um, which was great. But then when it came down to raising money for the fund, it was a different story. It's almost like
separate uh strategy in terms of, you know, having it was a little bit more about showing some numbers. Uh and we couldn't really because we didn't have any numbers at the time to really show for high frequency strategies. Um we had to you really just do what we can. So like we would show we would show like some back tests, for instance, uh, and then have to have a ton of disclaimers about like, you know, here's we only did one back test, you know, we don't overfit. We're not trying to
you know, show you the best one. And um, although most investors probably didn't believe it anyway, they're like, you know, they've never seen a bad back test before, right? So it's pretty much useless. But we still, you know, tried to explain our methodology. We explained what we were doing. Um we did offer day one investors more lower fees and higher controls, so more liquidity.
Um that helped a lot too. And also, you know, higher communication channels in terms of um maybe I would send uh weekly emails to certain investors um so they would um, you know, feel more, I don't know, like feel better about, you know, what was happening or at least understand that we know what we were doing that week.
Um, and then, you know, obviously offering them a discount on the fees and um lower, you know, better liquidity terms so they could maybe redeem at any point in time, um, maybe get rid of the lockup period, you know, things like that. Um, that helped a lot. And one thing we realized is even if we got rid of the lockup period, you know, no not a single investor redeemed um, you know, within let's say one or two months or even within a year.
Usually, when an investor makes a decision like that, if they're a good allocator, they're in it for the long haul. But they just like having that free option available in case there's uh pandemic, you know, in case there's some event where they actually absolutely need the liquidity. So um but yeah, that was really helpful from day one to kind of get that. And then there also um what's interesting Aaron is there also are um quite a few investors out there that
particularly allocate to day one funds, you know. And they do expect the kind of lower fees and they expect, you know, maybe a side letter or whatever. But um, you know, the the purpose is that they are interested in taking that risk with newer managers and they might be interested, especially in the quant space, I'd say a lot of um They're interested in that new wave of
quant managers who, you know, they view as kind of geniuses from a dorm room basically. So hopefully people like us, I don't wouldn't call us geniuses, but, you know, just folks from that kind of background and and give them a shot and see, you know, if they have that next big thing.
It might be a little bit hard for you to compare, but did you find there was Perhaps some additional interest in your offering, given that there are very few funds out there which actually offer investors exposure to HFT strategies. That's a good question. Absolutely, yeah. Um especially
Surprisingly, I would say after Flash Boys came out, that was when we got the most amount of interest. Ironically, um, you know, there were a lot of allocators who had read the book and they were like, wow, you know, let's Google this.
what are the high frequency trading funds out there. And it turns out every other the, you know, the big high frequency trading funds, they all change their language on their website. Now they're, you know, they'll say electronic market making or low latency trading. You know, they'll try to get rid of that.
a bad reputation and image associated with high frequency. We were the only firm that wasn't afraid at the time to just proudly say, look, we're high frequency trading. You know, I've never bought order flow or front run or back run, middle run, a single person out there. Uh and uh but we do high frequency trading. We're exactly the definition that you would expect.
of uh what high frequency trading is because we're trading literally in the, you know, nanosecond resolution here, getting data at that, you know, at the high speeds and then trading thousands and thousands of times per day. you know, recently like this year, the the highest we reached um in terms of volume per day was 7.1 billion. So, you know, that that is pretty much the definition of what high frequency trading is.
Um and so we were doing that. We were like, look, we're HFT. So people Google us. We show up, you know, SEO. We're we would show up at the very top uh without really trying. And uh people would just reach out to us and be like, hey, you know, we heard about you. uh can we schedule phone calls so so that happened as well um a after a certain point in time and uh was
relatively, you know, nice and helpful. I mean, obviously people would always have concerns like, hey, you know, what do you do you front run? And like how do you handle order flow and things like that? And we would just simply say like we don't, you know, we don't buy order flow at all. Um and uh it's just not the type of trading that we do and uh we don't
you know, do uh what they described in Flashboys where they're blasting holes, you know, through mountains, under the river, whatever, uh, to try to wire between different exchanges. Back then, you know, we literally were just trading within uh a single exchange, actually. So we didn't need the speeds between, you know, transatlantic cables or whatever. We didn't need any of that kind of stuff. So um it made it a lot easier back then.
Uh and then, you know, over time as well, the I think a lot of the myths in the book have been debunked or explained um by folks over time. So most of the investors have gotten a lot more, you know, educated about our field, which has been helpful too. I'd like to spend a little time speaking about how you built out the infrastructure. So you mentioned earlier that you built everything from the ground up, from scratch, internally. Um, is this unique for a HFT fund to do so?
Um, I wouldn't say it's unique. It's something that, you know, especially If you're starting out in an industry that's relatively um still relatively new at the time or just hasn't quite been commodified yet, um, you know, it's something that you kind of just have to do to to get up and running. I will say today because after Flash Boys came around, actually there are a lot more startups that started doing HFT.
uh technology, you know, maybe like uh feed handlers for HFT or, you know, thinking about open source kind of tools like that as well. So That has made it a lot easier to get to launch for a lot of folks. And usually today when you know startups have a small budget, I just recommend look out there, see what
see what you can use that's either, you know, cheap or free or open source. And and surprisingly, there's a lot of stuff out there. Um, so, you know, it's that I guess centuries old question of buy versus build. To be honest, it felt like we didn't really have a choice but to We couldn't even if we wanted to buy, we couldn't afford it. So uh build it was on our end. Right, right. I mean
Yeah, it was probably a lot of cost up front and a lot of time spent, but does it feel like that's kind of optimal for you now? Like that's the you know, the the ideal scenario is that you ha own all your own software now. Uh it's great today. It was really awful before we launched. I mean, you know, there were many frustrating days, uh,'cause we just had such an unknown
timeline of like we had to we had roadmaps, we tried to map it out. You know, our investors demanded to see roadmaps and budgets and things like that. And we could try our best to do the roadmap. And then um it felt like a I don't know if you know like Xeno's paradox, maybe I don't know. It was like one of those paradoxes we fell into where one task turned into two, two turned into four, and it just kinda grew and grew. And you know, you would think a trading system sounds so
simple and then you look at all the nuances and details and all the data sets and every single nuance and every data set and and just all this stuff and it was quite a lot to to deal with for, you know, a small team at the time. So Um yeah, it was definitely unexpected and quite frustrating to be honest, um, before getting to launch. I think every every company underestimates how much time it takes to
get to launch. Unless you're like, um, you know, if you're non-quantitative or if you already know what technologies you're using, then sure, maybe you can hook it up overnight and, you know, start trading. But um even then it's it still takes time. You gotta set up the legal structure of the fund. You gotta
figure out, you know, who your auditors, administrators, et cetera. And they all have to be ready to turn it on with you at the same time. You know, so all those things combined uh made it quite a lot of uh work on our end and um, you know, pretty frustrating two and a half years before we got to launch. Yeah. Now this might sound like a bit of a naive question, but just for anyone who might not understand
What's the right word here? Might not understand what goes into building an HFT business, which is probably a lot of folks. What did you have to build? Like what took two and a half years? What were all the different components that had to be developed? There's so many. Um, you know, it's like pretty much
uh a type of we had to build the entire trading system and ecosystem from scratch. So everything from um because we need direct market access, right? So we're literally placing trades ourselves.
um at the exchange level. And so because of that, we had to build a system, you know, order management system basically, system to be able to place orders, to see orders, to track orders, you know, to to figure out what's going on, to cancel things. Um and that also included uh risk management tools that we had to um get
basically verified by all the different, you know, brokers exchanges, et cetera. Everyone had to make sure that our risk checks were enough and that they were stable and that if there was a some uh you know, a crazy event that happened that um, you know, our systems wouldn't go rogue. And so we had different ways to check.
those types of strategies as well, um, to make sure that we didn't accidentally, you know, um, tank the markets ourselves single handedly or make any big errors or mistakes on that end. So
So that requires quite a lot of work. Um it's very different from a tech startup, by the way. And that's one thing I've noticed was, you know, with tech startups, you can launch an MVP and it can be bare bones, it can be broken, it can be pretty bad, and and that's okay, you know, your clients, early stage day one clients should forgive you.
for that because they know you're a startup. When you're trading, it has to be perfect. You can't have any error, any room for error at that level because you're literally if you mess up you know, you're done for. You don't have a second chance in this space. So that kind of process of making sure everything was perfect um definitely took a a lot of patience and uh you know energy and effort and uh a lot of
you know, checks making sure all the checks and balances, whatever else, you know, was in place as well. Um, yeah, so that that was a big thing. And then um, you know, how do you process data, right? It's another big question of uh what are
How do you get the data that we, you know, we wanted and we had data directly from the exchanges, but then how do you process that data and turn that data into uh an actionable, you know, some kind of uh value that we could extract from it? And so how do you do that as well? You know, so that took uh a lot of time to figure out and to process and to and then you know data pipelines would they would always break. We would always have some kind of issue that happened. And so
um figuring out how do we timestamp that data, how do we process that data was also a big uh question that we would have in mind as well. Yeah, in general it's a it's It's quite a nuanced process and it it just had to all be relatively perfect on day one or else um you know, a l no hedge funds rarely get second chances, I would say, unless you have unless you're famous and uh your name is already known and or you try to make yourself known. But um back then we weren't so
Um, you know, we literally just had one shot and um knew that we couldn't mess it up. So a little kind of scary, but um we're uh we do feel fortunate and lucky to have made it this far today. In saying that, what gave you the confidence, you know, after two and a half years of building this out, that when it came time to switch everything on, what gave you the confidence that the strategies were actually going to be profitable? Oh man. Uh to be honest we we didn't.
It's hard to say. You can do as many back tests as you want. We had a simulator as well. You could we could simulate, you know, strategies and orders and fills basically uh in the live environment too, which was great. But um even then, you know, it's hard to replicate a hundred percent what's gonna happen in reality. So Um We did as much as we could, test as much as we could. And then one day, I remember the first day we launched, we were just kind of like, you know what, screw it.
Let's just trade. Let's just do it. You know, we gotta take her we were very risk averse at the time too, and we're scared, you know, to do something we've never done. And we're just like, you know what, let's just let's just try it, turn it on, see what happens, and hope for the best. And uh that's literally
you know, what we did and uh thankfully things didn't blow up on day one. Thankfully nothing, you know, crazy happened and we were like, Okay, this is great. Actually we could, you know, we figured out, you know, we needed that kind of feedback from the markets and um were able to fine tune the strategies even more and um just continued going from there. So
Um, but yeah, it was definitely a relief to finally have launched and to be able to tell people, Okay, we finally launched. We're no longer uh, you know, felt like I was a fraud all the way up until we launched and so we're like, Oh, we're finally a real hedge fund, you know. we can uh have a real track record to show people, which was fantastic. You're in business, yeah. Are you ready to get serious about trading? Then join Tasty Trade, Investopedia's best platform for options trading in 2026.
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Just recapping those first few years, looking back on it, what would you say were some of the, you know, the breakthrough moments which you had and also some of the unexpected challenges which you came up against? Oh, there's so many. Um, I don't even know where to start. I would say like when we first started the business.
Uh we wrote down, you know, some of the things that we wanted to save money on and some of the things that we wanted to spend more money on before getting to launch, uh, because we had such a limited budget, but there were some things that were worth. Uh hopefully, you know, we thought we're worth spending some money on like a good lawyer is a good example or maybe
finding a good broker, you know, uh like someone with a reputation as well, auditors, et cetera. Um, we could splurge on and then, you know, things that we valued, like we wanted to be a flat organization. Uh back then everyone was called partner. And uh, you know, see, and then it actually did not go too well. And I have so many reasons for that. And um, we wanted to have perks.
Almost like I don't know, we're a bunch of naive kids, right? So we literally thought about like, let's make this like Google, like a Silicon Valley company with like free food and unlimited vacation and all these great perks. And we quickly realized like that those are both really bad ideas on the organizational side. Um, you know, you don't want to call someone we hired like literally like head of HFT from firms like Citadel and uh you know Gecko back then and other firms. Um
And a KCG back in the day as well. And uh they would come in, they'd be like, wait a second, you know, why do I have the same title as this kid who graduated, not, you know, not necessarily me, but like, What about this kid you just hired, right? Who just came out of school? You know, why is why is he or she called a partner and we were like, Oh gosh, you're right, you know, um, we realized that
Um people actually felt less equal because of that rather than more equal, uh, which was pretty bad. And then um in terms of perks as well, just didn't work out. You know, people abused the perks like crazy and uh it was kind of unfair. It made it more unfair and gave people kind of almost giving people too much choice sometimes is a bad thing. So
Things like that. And then, you know, also splurging on things like lawyers and brokers and stuff, we realized quickly that um it also wasn't worth it to hire just the biggest companies out there. Um, you know, that it's okay to go for a smaller as a small hedge fund.
that uh, you know, it's okay, your investors aren't gonna look down on you for hiring a a smaller lawyer, you know, so long as they are still qualified to do their job, right? Um, so just things like that we made a lot of mistakes on. Um trying to think of what else we We did so much wrong that it's just hard to even begin to um imagine. So I'm just trying to think of what else there was.
Oh, I mean we had a settle we started off in my apartment actually after graduation. Um we worked in my apartment for some time uh until we were kicked out, we were evicted. And uh the reason why we were evicted was actually kind of a random reason. Well, the cops knocked on my door late at night. But um what happened was the uh oh, we were we had built our server cabinets, uh, literally in the closet of uh one of the like the master bedroom basically.
uh and we rigged our own electric, you know, basically we rewired the electric system and built our own box and stuff. Um and I think uh Jay Wing, one of my my co-founders, he actually electrocuted himself in the process. So we were clearly uh not experienced at all.
we should have hired a, you know, a unionized, I don't know, person ride to do this. So we were doing some pretty sketchy things. We ended up, you know, we're trading so much. We're having we had so much going on on the server side that um we were literally using up all the electricity in the building.
And uh you could also, you know, people thought that we were like we had a marijuana farm or something. Like literally people thought we were running some kind of marijuana farm. And so that's why the cops knocked on our door thinking like they were expecting to find us.
growing pot or something or, you know, harvesting drugs, whatever it was. And they came in, they're like, wait, what is this? And they saw there's computers and monitors everywhere. And they're like, What? Are you guys some genius hackers? Like they thought we're hackers. And we're like, no, no, no, this is
you know, this is a small business here and uh, you know, I did live in the other bedroom. So technically it's my home my home business, right? And uh and they were like, No, this is not gonna work. You gotta you gotta get out of there and get a get a real office and then um the next day we literally packed up and
um moved to uh We work. Uh back when We Work first opened in Boston at the time. Our rent shot up. We were we used to pay four thousand per month for rent. And then at WeWork it was twelve thousand per month. And uh this is three times as much and the room we were stuck in Uh you know, we work they pack you like sardines in these tiny little rooms and literally um it was the size of the c server closet that we were um that we had at the apartment. So it was just
what a crazy just a turn of events like that um that really changed, you know, changed the environment and stuff. But lots of adventures like that that we were willing to go through and, you know, finally we're very lucky to finally get to a point where we could launch, I guess. What a story. That's hilarious. Dome yard where it is today. Uh, I'd love to just ask you a few questions around kind of some trading metrics, if you will.
So can you tell me how many trades do you average per day currently? Of course it varies, but just on average. Yeah. Um recently two thousand five hundredish, a little under two thousand five hundred trades per day, which Uh recently has not been a lot. Uh we've done more more in the past, uh, you know, depending on the market environment and stuff like that. But in general it's in the up in the thousands, you know.
uh and completely automated, you know, people always like, are you really high frequency tra yeah, you know, we're this is high frequency trading. You know, they're all intraday. uh and uh holding periods anywhere between I mean
I know this sounds like I'm I'm not marketing and we're not fundraising. I'm just gonna clarify that right now so that people don't, you know, SCC doesn't come after me again. Um I'm just saying we're not fundraising. Um, but uh, you know, we are holding period wise anywhere between You know, less the split.
sec you know, like less than a second, microseconds, all the way up to hours these days. And we consider the hourly, you know, holding periods we call we call them midterm strategies, but to Every single one of our investors that's still high frequency to to them because mid frequency is like weeks so days, you know, it's a different um we live in kind of different universes it feels like a little bit, but but yeah, um happy to answer any questions as much as I can without getting in trouble.
Okay. So are you flat at the end of each day like you don't carry anything overnight? We are. Um, we used to do some overnight stuff, but um, you know, realized that our niche was still in the the high frequency, you know, uh mid, I guess, intraday type of strategies. And we also figured that. the additional edge we would get from holding overnight, um, wouldn't uh it was mainly a constraint that we put on ourselves to be flat, but um
It's just something we've gotten used to over time. I would say there's really these days we could technically do overnight strategies again, but um it's just something that we haven't really um done yet for various reasons of, you know, just profitability, risk, you know, all those different factors that we need to keep in mind if we did that. Okay. That number you gave before, uh two and a half thousand, I actually for some reason thought that number would be a bit higher.
Oh yeah. Uh it could be up to Uh, I don't know how much. Ten thousand, you know, twenty five thousand. Uh it really depends on what we're trading and uh how the markets are reacting and how much um you know, what the liquidity profiles look like and all the other things like that too. So, you know, sometimes it's just
Actually during the virus, you know, the the volumes did shoot up uh quite a lot because there's, you know, lots of speculators, lots of um day traders and and uh a lot of institutions. Everyone's just very active right now. So um it did shoot up a little bit, but for now, you know, it's uh down to the two thousands. Uh the number of trades you make, uh is that somewhat correlated to the the volatility of the market?
Uh good question. Uh s kind of yes and no, depends again on what kind of strategy we're implementing. you know, usually during very high volatile, you know, periods like like this, basically, um, we tend to have a lot higher volume. Uh and uh the hope is that we perform better uh and can maintain
some kind of neutrality to the markets. So that's uh that's definitely the case for I would say of actually most high frequency trading firms as well as just during periods of um you know higher volatility. uh there t tends to be just more naturally more opportunities uh out there for folks to to see and utilize. Right. And are you able to share your win rate?
Uh oh man. I actually did not that's one thing I did not ask the lawyers about. Um, but uh in general, I will say, you know, we were really happy with our performance this year. Uh we did have like two very particularly disappointing months uh in general, but um Overall, you know, we we're definitely still
by a huge margin beating, you know, all of our benchmarks. So um it's it's been a great time for us to and also because it's oh, this is also the first recession we've been through too, because we didn't go through O eight. I was still in school. So Um so the other thing is because of this, we were able to prove ourselves and be like, ha, you see we we can finally show we've been through
you know, the ringer. We've been through this bad uh these crazy times and that that we c you can show that we can, you know, go through those and more. Um so, you know, we've had some disappointing months, but uh in general it's it's been all right. Okay. And how about average daily turnover? Of course that would vary with the number of trades, but uh just broadly speaking Oh man, just turning over so much. Um, it it can really add up to quite a lot. I mean
you know, we would trade like recently again, like the most was seven point one billion, I think, per day this year. Um, so we've gotten quite uh high and substantial in terms of the volume and and turnover rates. And uh it'll probably continue like that for hopefully for some time. Right.
And given that you're trading so much and I I I don't know your win rate, but I presume it's it's, you know, above fifty percent, are you profitable at the end of each day? Like I presume a losing day would be pretty rare. Uh, so we are not necessarily profitable at the end of each day. And I think that's something, you know, unfortunately um for us and maybe even for other firms as well, it's um become a lot more common. Like I know we read articles about Virtu.
you know, not having a single losing day in years, right? And you're like, wow, is that Is that standard for the industry? Um, I'll say probably not. Most um HFT firms, you know, we can end the day losing, uh, you know, having a negative uh, you know, much less money than like the day before.
Um, that does happen as well. So um, you know, the goal is though that we do aim for 100% winning days nonetheless. And um, you know, when a losing day happens, that's that's okay. You know, we try to deal with it. Usually what happens for on our end is like we might have twenty nine uh winning days and then one big losing day that just wipes out everything we made during those twenty nine days. Sometimes that kind of stuff, um, you know, does happen to all companies, all firms, but um
It's uh it's life, right? And um we've learned to how to deal with those types of days, how to mitigate those risks and and learn from those uh, you know, crazy experiences. Okay. And now I haven't asked you what products you're actually trading, like what markets are you most active in? Pretty much almost everything. We're not as active in like we're active in primarily US markets right now, but um, you know
US equities is probably the one big market that we're not as active in at this point in time. We've we've traded before in the past, but um at this point in time uh it's just not the market for for us. Most of our strategies are concentrated in in futures. Um and we have a lot of effects at this point in time as well. Um, we do have some option strategies that we're utilizing at this point too. So uh yeah, a a lot of uh I guess, you know, Delta One strategies and uh not a lot of
equities, although it's something that, you know, we've every year, every month we consider like, oh, maybe we should go back into equities again and try it out. Um, it really just depends on the conditions and, you know, what uh what we're testing. We're constantly testing things behind the scenes and
uh figuring out whether or not it's the the right time to pursue something. Okay. And is that all futures uh in the US? Well not all of them, but is it or are you more um Uh more focused on like indice futures or commodity futures or pretty much the the whole mix.
It's a whole mix. Yeah. We're pretty agnostic within the future space at this point in time. Um, they do have to be products that are, you know, relatively frequently traded, uh or else it would, you know, not be worth it for us to deploy a strategy within. So Um, they're they're heavily traded products that we can hopefully take up um, you know, a chunk of the ADV, not a lot, maybe like, you know, aim for one to three percent of the average daily volume of that product. But um
Yeah. So uh, you know, we do look for things like that. But in general we try to be agnostic in terms of sector. Okay. Now, this might be a bit of a a broad question, but just on your strategies. In such a highly competitive area of the market that you compete in, um, how do you seek to generate alpha? In terms of generating alpha, there's uh a lot of different things to kind of keep in mind on the parameter side. So
I think the biggest thing is figuring out what are some niche areas that we can really take advantage of. Um, what are some products that, you know, we we can kind of uh be able to map out and um be able to make predictions on. So a lot of it's based on, you know, small predictions, um, maybe a few seconds ahead of time on where different uh trades and products will go. So
Um, so that's a big portion of it. Um, but then also um looking at other I'm trying to think of other things we we do on this side. Let's see, just mapping out in general. uh, you know, hundreds of different signals in gener, like finding the different signals that we can trade.
mapping those all out. And then we actually do use a layer of machine learning as well to do some signal selection throughout the day as well. So figuring out, you know, what those signals are and what's going to make the most money during this
certain environment and then when the environment changes, you know what what kind of strategies we want to pull back and what do we want to deploy. So that's always a really tough question. But um it's Surprising because most HFT firms, you know, I would never say that we're an AI-driven machine learning based firm, but we do use just a little bit to do some, you know, basic strategy selection type processes on our end.
What data drives the majority of your trading signals? Is it order book alone, like looking at the market depth, or is there additional input from other data sources too? Uh it's mainly market depth, yeah. So just order book data uh is extremely helpful for us. We do have a little bit of what we call metadata. uh you know, you might call it alternative data um in different types of
areas too, um whether that's usually it's like, you know, things like calendar data, right? Like every uh high frequency trading firm needs to know when bank holidays are and things like that or um, maybe things like SCC filings or um big economic, you know, announcements or um, you know, Fed meetings, things like that. You know, that kind of stuff does need to be factored into
um, you know, the strategy as well. So we can't just be completely um focused on the market data, but we just also keeping in mind all the other components of data um as well. So yeah, in general though, I think the biggest source is still, you know, just market data. That's the the bread and butter we need to kind of survive. And then from there, you know, it's almost like a bonus if we can get um other sources of al of alternative data that could help us out here and there as well. Okay.
Can you speak to almost like the strategy survival rate or the signal survival rate? Like What's the edge decay like on these signals? Like are you continually, you know, innovating and revising your signals or Do most of them kind of last for a long period of time? I mean, I perhaps didn't really word that question very well, but I I think you probably understand what I'm asking here.
Yeah, absolutely. I mean, the half life of these strategies, you know, can be relatively short. It could be a month, uh one and a half months, you know, and then within three months the strategy is uh you know, pretty much almost worthless at that point in time. And so it's a process of constantly revising those strategies, a process of constantly finding new strategies as well.
um and uh modeling those strategies in different environments to see, you know, how they would do. And uh and then also figuring out why did the strategy die and they could die for so many different reasons. You know, a lot of it's because competition has caught up or um maybe because the environment's changed and the, you know, signals that you're looking at just are no longer valid for whatever reason that happens too.
So there's there's all kinds of different reasons, but um it's uh just important to be able to figure out when it happens and why uh and be able to move on quickly and not get too uh attached to one or two, you know, strategies. But um, you know, we have like hundreds and hundreds of different types of signals to potentially deploy and take a look at. So
So um just making sure we're careful there. Um I know there's stories about like, I don't know if you've heard there's stories of like Renaissance, for instance, and other types of funds where, you know, when people leave their those types of firms that are doing really well, one of the biggest reasons why Um, it's hard to spin out of certain, you know, successful HFT firms and to just do your own thing and be more successful.
is a lot of it's because they're constantly revising their strategies over at Renaissance as well, I'm sure.
Um and uh, you know, when you steal a strategy, by the time you get to launch three months later that strategy's already dead and it's just no longer um effective. So that's uh definitely Something that we do as well on our end is just um, you know, it's not on purpose, but just the nature of high frequency trading is just that the the opportunities you find um may not necessarily last uh for a very long period of time and they might be really niche.
So uh once we find it and once uh that niche kind of goes away, then um we are on to, you know, hopefully the next thing. During the trading day, what level of human input or decision making is there? Obviously the trades are all automated, but is there any human intervention uh during the trading session?
Oh, it's a really interesting question. Um Well, first I will say like a lot of people have this vision of high frequency trading being, you know, a bunch of robots taking over the world or, you know, machines and uh, you know, that are out of control with, you know, humans not being able to
really understand what's going on in this black box. And and that's really not the reality at all. You know, the these trades are being heavily monitored and um, you know, by humans throughout the day when we're trading. And uh, you know, really just gathering all kinds of data about what we're doing and stuff like that. Uh, there's a a huge human you know, obviously we're not having a human sit there and click to to make those trades. You know, there's no it's just being placed automatically.
Um but there's always a human behind the scenes to uh tweak the strategies or to tweak some parameters or you know change some of the risk parameters, things like that. Um and a lot of it's in code, but just kind of changing that coding of um what the strategy might look like. So so yeah, there's a surprisingly large human element in terms of uh what we do and uh
you know, the strategies also they're only as dumb as the humans uh who are, you know, creating them. I hopefully as smart, but, you know, I would say they're you're they're as dumb as the the person who created it. So Um absolutely you know, we need that human intervention constantly to make sure that nothing goes
uh rogue or, you know, crazy. Um the other thing is like I'm trying to think of, you know, the markets as well, right? Because um this isn't like a closed loop game. It's not like a game of go or I don't know, chess where there's rules and everyone's going for the same goal.
Um, you know, in the financial markets, things are constantly changing to the point where even today, right, you know, we see a lot of things like oil going negative, you know, things that economically, like in your textbook, you know, you would never have, it just makes no sense. You know, and that happens all the time. And a lot of that might be just is just driven by human, very human behaviors. And so um you need to have a human
behind the scenes to understand those behaviors in order for your strategy to do well. Um you can't just have a strategy that, you know, you can you know, even if it's a some kind of deep learning model or, you know, if it's learning by itself from its own inputs and stuff like that. Like that's That's great, but again, you can't quite model the financial markets and we've seen
startup after startup, you know, including Watson as well. You know, IBM Watson trying to model the markets with their ETF. And you look at how they're performing and you know, some is just not the best start um to to the ETF, AI driven, you know, stuff. Yeah, absolutely my my personal opinion as a high frequency, you know, ironically as a high frequency trader is that they're is an important human element that um, you know, we we can't forget in behind the scenes.
Now, as you are a high frequency trading fund, uh obviously speed and reducing latency is a big factor in what you do. What measures do you take to reduce latency, both uh internally and externally? You know, the the biggest thing people always imagine is like, oh, you're doing, you know, what they did in Flashboys. Uh, but we we don't do any of that. Um, you know, biggest thing is on our end is is purely uh pretty much, you know, just internally making sure, okay, let's um
you know, gather data the fastest we can. Let's make sure that once the data is in place, uh, you know, between getting raw data and processing that and turning it into a s an actionable strategy. um that we can reduce the amount of time it takes to be able to do that.
And then also be able to run that strategy, you know, um, on live data and be able to, you know, place those trades as fast as you can. And and uh, you know, for latency, it's basically, you know, as as soon as we discover a decision we wanna make.
the time between that decision and actually implementing it, you know, that kind of um that time we do try and reduce as much as we can. Um, you know, whether that's just uh through direct market access, you know, with the exchange or uh making sure that, you know, our order management system is structured in a way that is is fast and efficient and um can process, you know, a bunch of orders at the same time without having, you know, too much lag. Um I know we've had I'm trying to think of
Uh we've had some I know on the development side, like uh we'll maybe consider like sh you know, even just things like shortening names of stuff uh might help a little bit too. So
Um just making sure that our names are a little bit shorter so that computer wise, you know, th it takes a little less time to process. Um so stuff like that might might work as well. And then um making sure that we optimize for different strategies on the latency side, you know, the strategies themselves. So making sure
that um we're optimizing on that front so that they can be uh, you know, code wise, right? To be a little bit faster and uh take a little less um processing time in order to complete. So so that's definitely important as well. I will say one other thing though is um You know, I know everyone obviously talks about speed and thinks about speed when it comes to high frequency trading, but um
Uh on our end, I think we found our niche in terms of um, you know, we're we're not trying to aim for being like the top fastest uh high frequency firm out there. And I think most firms are like that these days where You know, we don't play the hardware game actually. So um we used to. We used to like, you know, uh assemble our own hardware, buy the best thing out there, and then we realized
Every year they're gonna release a better, I don't know, FPGA, a better, you know, piece of hardware somewhere out there. And um, do we really wanna pay an extra million dollars? Is it really worth it? Or you just realized it it just wasn't at some point, and there were lower hanging fruit um in different areas. A big reason, by the way, is also because. Um at the exchange level, um, if their latencies are slow.
um and there's a lot of jitter happening at the exchange level, then um even if we did place an order really fast, uh, you know, the the decay, there's still a little bit of a decay in terms of the timing it takes and the alpha that we end up getting. And so we're like, well, why don't we just figure out you know, um we call it lower hanging fruit in terms of um maybe better signals or um looking at better products out there that, you know, we could take more advantage of without having to
um compete at the the, you know, microsecond level all the time. So thus, you know, going for strategies that are uh have longer holding periods as well and uh may not be, you know, what you would typically expect of high frequency trading just trying to be fast, fast, fast. Now one of the things which I understand about HFT strategies is that they have um capacity constraints.
And that's what's kind of interesting about what you guys do is you are a fund where most traders who are running HFT strategies are mostly prop model. Uh, whereas Eurofund. And I guess that's one of the reasons is because um HFT strategies typically have constraint capacities. How do you deal with that aspect of it? That was a great question. It's one of the biggest things that
keeps me up at night actually is um, you know, HFT is although people always assume it's this menacing thing, you know, we're not a scalable business. Um the industry is just not scalable given the nature of what HFT is, you know. And uh and that's that's fine. I think that that could be a fair thing and, you know, it's just how things are. The capacity constraints, you know, the reason why we're a hedge fund to begin with was we just didn't have we didn't even have
you know, a million dollars or a hundred thousand dollars. You know, we were literally negative money because we were in debt. So we didn't have any money at the time to trade. And uh we supposed, well, you know, even if we could start a small fund. In the meantime, it would be better than nothing and at least give us uh enough of a boost in our early stage careers to
you know, how have a uh to know the industry better and also to hopefully um, you know, learn a a thing or two. So um so that was the big thing there. But um, you know, if we could like let's say if we could start today, yeah, we would probably be a prop shop um instead of a hedge fund structure. Because the hedge fund structure, you know, it's great in that, yeah, you can you have all these external investors coming in, you know, and uh and that's
Good for us to get to know the industry better and to see what's happening out there and to meet some great investors. The bad part is obviously it's just it's a lot of extra work. Um, you know, to have to do the weekly, you know, sending newsletters out or sending emails and um, you know, answering questions and stuff. But also uh regulatory wise too, you know, registering with
uh all the different s you know SEC, NFA, uh whatever other uh countries and jurisdictions that we want to be involved with. Um so that is, you know, just a lot of administrative work. It costs you time and money. uh having a director in the fund, you know, thinking about the legal setup of the fund structure, all this other kind of stuff like
that costs a surprisingly a lot of money even before getting to launch. Um, and so so yeah, that was kind of the trade off that we uh had to make, I guess, in order to start the hedge fund structure. Right. Now Christina, just one last question before we uh close it out here. Is high frequency trading as profitable as everyone understands it to be? I'm not sure if this is public information or if you're able to share it but If if so, are you able to share some performance numbers?
Yeah, yeah, absolutely. So I would say It depends on who you are because some people imagine that HFT is just this money-making, you know, cranking machine that uh, you know, never loses and stuff like that. And that's definitely not the case at all. It's a very uh, you know, it's fallible, it has issues and uh a lot that's the reason why a lot of HFT firms, you know, that existed ten years ago are no longer around today, right? It's because they they still
uh died for one reason or another or they got acquired or they just were no longer uh the profitability that they used to be. I think a good analogy, by the way, is like in the crypto space as well, you know, where if you started a crypto hedge fund, I don't know, back in twenty twelve or thirteen. Yeah, maybe you were great, you know. You you're good congrats on being one of the, you know, earlier funds, right, in that space. But um, if you started a crypto fund today,
you know, most of the alpha is gonna be uh pretty much gone. You know, so it's a it's kind of a similar thing where uh it it gets harder and harder to compete as more people uh flood the industry like that. Um, but I will say like it was really
surprising for me'cause we had spent two and a half years literally making no money at all, which is, you know, for any startup that's extremely frustrating and uh, you know, almost like heartbreaking to to see. And then the day that we started launching the strategies and stuff, um You know, we were super nervous and I remember turning it on and literally it was nothing. Like we weren't trading at all and just
nothing was happening. Um, and it was we're just waiting around the the table, you know, at our in our office, just huddled there being like, What's going on? you know, why is anything happening? And then
We just kind of gave up by the end of the day, just went to go grab uh I think I went to go, you know, eat some ramen or something. And then uh someone called me over like, Christina, no come back is finally starting to trade. I was like, oh my gosh, you know, the market's right about to close and we literally
started trading at the close and we checked our balance and we had made seventy thousand dollars, you know, in like a minute. And we were like, oh my gosh, that's that's more money than my parents made combined in a year.
You know, and and that feeling of like, oh my gosh, the have the tables turned, you know, and hopefully we won't lose, you know, um hopefully we won't lose the money. But uh, you know, that that kind of feeling of, oh my gosh. And then thankfully that, you know, continued for for some time and then And uh, you know, we we felt very uh just like, holy crap, this the wait was worth it. And what about like annualized returns, that type of thing? Are you able to share that info?
Uh unfortunately I can't because um we've gotten in trouble for sharing it in the past. Um for like uh it it's considered marketing uh and uh it just does not go well with uh we were audited. quite extensively in the past couple of years or so.
Uh, and this was always one of the things that they always get us on is they'll listen to the podcast and be like, oh, you know, you were why did you say that? And why did you why why did you have this tone when you said it, you know? And like this could be construed as you know, uh, marketing in one way or another. So unfortunately, um, we're not allowed to market. I would love to though, because I
I'm so proud of, you know, what we've done. Unfortunately not the you know, we're not the type of fund that can market that kind of information. Understood. That makes sense. I mean, the last thing you want is is legal hassles. So uh totally understand. Uh well, Christina Just such an amazing job. It's really inspiring to see what you and your your co founders have done and what you've achieved.
over the past, I think it's eight or nine years now. So, you know, especially having started from scratch, like built everything from the ground up. It's just incredible. Awesome talking with you. I'm very grateful for your time and I know we've been trying to set this up for a little while. So
I'm glad we could make it happen. Uh if somebody wants to find out more about you, uh I know you've given a few talks and that type of thing, which are available on YouTube. Um, you're also on Twitter. Uh can you please share your Twitter handle? Sure. It's just my name. It's at Christina Chi, uh which is spelled Q I.
Um yeah, please feel free to check it out. I'm a little crazy on Twitter, which uh a lot of people don't like. But uh I think it there needs to be more loud vocal voices in in this industry. So um and hopefully Hopefully I have some reason in terms of most of the stuff I say uh and am not just completely crazy uh like some other folks in this industry, which is fine, but you know, uh everyone has a different personality. So uh feel free to
you know, check that out. And then also um recently I I've been working on a data venture as well. So if you guys are interested in uh market data uh and uh infrastructure co location, that kind of stuff. Um, you know, definitely feel free to reach out as well'cause we do some uh really cool stuff on that front too. I I did mean to ask you about that actually. I mean, if you have time, do you want to just give a quick summary of what you're working on there?
Sure, sure. Um basically, you know, one of the biggest challenges we faced when we were launching the hedge fund was we had spent Over a million a shameful amount of money. Over a million dollars on uh data. and infrastructure and uh and we feel like that barrier to entry is way too high. We wanna lower that barrier for other folks out there.
Uh and just so you know, this has nothing to do with Dome Yard. We're completely unaffiliated. You know, the we're not front running, you know, Domeyard's not taking that data at all from anybody. So it's a completely different venture. Um but basically just offering um you know data that a lot. It's the quality that we expect. uh from you know institution quality data.
But um we sell it a la carte. So it's broken down. You can buy literally just one security if you wanted to, uh, or you know, the entire thing if you wanted to. But the goal is like we make it a lot cheaper for folks and lower that barrier to entry.
So it's called data bento, if anyone's ever curious, like bento as in the bento box. Um and the goal is like, you know, people can purchase data from various different sources. Um and it's we do live and historical, so um, you can have live data feeds from various different sources, uh, but uh in smaller chunks than uh what we typically see in the market. So um yeah, that's uh it's been fun to work on that. It for me it's meaningful because uh you know, I've been spending
People al always ask me questions about morality, like uh, you know, you're an HFT, right? Like how how immoral can you be? Um and I've always wanted to do something that hopefully would bring some value to the industry and have some meaning. And so uh for me, Data Bento has been fantastic in terms of bringing that kind of value. And I'm very lucky to, you know, be able to have um you know, to have the hedge fund reach a stage where I can be more hands off now.
And that we have a team and that, you know, the team is fantastic to to kind of take over a lot of the day to day um, you know, operations and things that I didn't want to do as much. So Um so that that's been very lucky and then, you know, to be able to start this data venture and hopefully help people out. Um, that's been a dream come true for me.
Yeah, that's cool. That's really cool. Uh I'll make sure to include a link to that in the show notes. And if someone wants to find out more about Domeyard, uh what's the website? It's just Domiar dot com. Okay. Nice and easy. So f people know we were named after the uh MIT dome in Harvard Yard back then. Uh we didn't want to name the fund after ourselves. And then by coincidence the uh dot com was uh, you know, pretty much free. So we were able to snag that qu pretty quickly and
Uh got pretty lucky with the name. Nice, nice. Well, Christina, very grateful for your time. Really appreciate you doing this. Thank you very much. And uh we'll talk again soon. Thank you, Erin. It's been an honor. You've reached the end of this episode of Chat with Traders, but rest assured there are more episodes. soon. if you'd leave a rating.