markets speculation and risk this is the
chaplet traders podcast hosted by Erin
Fifield 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 she in her early
20s after graduating from MIT Christina
and two classmates Lou :
and Jonathan Wang who had collectively
been trading futures from a campus dorm
room founded Dome yard it was 2012 and
dome yard 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 trade experience and minimal
insight to the hedge fund industry not
to mention the three had almost no money
Saddam Yard is also one of the few hedge
funds that went out and raised money
from VCS such as Softbank
and Aaron tech co-founder as a necessary
means to launch now eight years on the
boston-based fund is will established
and will past the startup phase demure
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 it's just incredible
so please enjoy here is my interview
with Christina Chi for episode 100
and ninety-eight understand it you had
been trading European futures in the
night with two other classmates while
you were in college or university how
did this turn into the borrowed 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 you know it
was interesting because we were
surprisingly doing pretty well for a
dorm room strategy I guess I mean we
would make we were only I think one of
our one of my co-founders he was at
Harvard at the time and his roommate
there you know Harvard us all these rich
kids apparently and apparently one of
his roommates his family runs a hedge
fund actually and they were able to give
us a little bit of capital initially to
trade and it wasn't a lot in you know as
like a hundred thousand bucks or
something but we were able to make about
forty thousand bucks take home forty
thousand basically at the end of the day
which was a lot for a bunch of little
kids in a dorm room and and then we
realized oh that's good you know for him
he was like oh wow this could be you
know a really cool thing to do and would
be really exciting you know something
that keeps you going and keeps you you
know waking up in the morning and for me
the reasoning was more because I had
interned in finance and I had a couple
of particularly well one particularly
poor experience in the industry where
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 younger people on the team as well
as some of the minorities on the teams
and the women and minorities and and I
just didn't feel comfortable in that
environment and ended up 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 there was a lot of
hazing and a lot of behaviors that I
just
you know didn't want in a company and
didn't want in a daily environment so
decided to start off on our own you know
I wish I could tell you Aaron I wish I
could tell you like oh this was the best
industry for me you know I had
researched and bred so many books and
did all this stuff like no I didn't I
didn't really 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 a desire to to
have a company with a better culture on
my end and a better healthier
environment and people always think it's
ironic you know you're a high frequency
trading yeah how can you be ethical 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 and we
can definitely talk about that more as
well so yeah so you interned at a couple
different places you weren't a fan of
this did you you have two other
co-founders at Dome yard did they have
somewhat similar experiences to you oh
we all came from different backgrounds
we actually weren't friends before
starting the company together but we did
have one thing in common which was the
same career goals in mind we all wanted
to do something you know related to
finance or FinTech and all cared about
the startup industry as well so we did
have different backgrounds so one of
them had a more math and physics
background and the other one was a
computer scientist and but we were all
young we were all inexperienced so it
definitely you know is helpful in
certain ways and that we had different
skill sets and backgrounds but also
unhelpful in that we are founding team
we didn't have someone like 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
mmm so this capital which you had
initially that you were trading around
with how are we trading that we're using
algorithms right from the get-go or was
it kind of clicked trading how were you
making trades and European futures I was
a great question I mean we were
literally using like Interactive Brokers
you know we had set up some
you know very wonky quantitative based
strategies they're still systematic they
still had certain triggers that we would
use you know we might do a basic mean
reversion strategy in our basic momentum
strategist things that you can implement
relatively quickly and easily the
holding we were were we entered a yeah
we were actually intraday by that time
already but they weren't high-frequency
in terms of the amount of times they
would trigger you know is not that much
during the day so 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
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 that we didn't need any you
know we didn't need any insider
information we didn't need any you know
kind of broader sources of data rather
than just market data that's all we
needed and so that was really great to
kind of see and we decided you know why
not continue making this seeing what we
can do on the technology side to improve
the latencies we had and back then you
know we didn't even know and we knew it
was high frequency trading but um this
is before flash boys came out by the way
so this is before the reputation of the
industry tanked so it was a different
time period you know altogether and 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 you also weren't will 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 I also had no credibility and
no connections at the time which was not
very helpful whatsoever 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 said
about doing this and you know it worked
every waking minute and that that's
really what what drove
to get somewhere I think there are a
couple things we did do differently to
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 you know there's funds like
you know quanto peon for instance back
when they had a hedge fund you know they
also raised venture capital as well to
fuel their unique fund we've also done
the same thing we raised venture capital
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 that 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 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 is 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 we have a lot
of value valuable stuff in-house that we
can always capitalize on one day or you
know maybe we could decide to sell it
one day if we wanted to you know said
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
but the bad side the downside of it is
it takes forever I mean it was an
unknown timeline an unknown path and an
unknown timeline which is scary it's
like the last thing that you want to do
is not know when you're going to launch
you know as a hedge fund and it's it's
extremely frustrating 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 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
fitnah FinTech probably wasn't a thing
back then but I have a more technical
background same with my co-founders and
you know during some of my internships
we would basically me I'll 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 I want it to
be a little bit more mathematical and
you know that's when you figure out oh
there's you know you could do some
market making and stat are based
strategies and have a more a more
systematic approach to those strategies
and so so that was the biggest impetus
of doing
I guess quant and then when we were
doing quote were like oh wait you know
the faster the the more money we made
and I know that sounds like a really I
mean to some people it's a really
selfish reason but that was really the
biggest thing was wow we could really do
this and and being faster we could
really start to compete against the big
guys in our space and you know make a
name for ourselves hopefully one day so
that was a 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
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 where they intended
to be those funds intended to be used as
trading capital so I'll answer your
second question first which is this is
meant purely for operations so
management company operations like
paying for employees buying software
getting data licenses paying for data
feeds you know all those expenses that
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 maybe we wouldn't
have to have you know raise venture
capital to begin with and sell you know
why sell a chunk of your company right
that's a 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 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 order management system feed
handlers execution gateways you know
market engine simulators like all those
different tools pretty much from scratch
and so that was gonna take a lot of time
and that's why we needed venture capital
we told them we were gonna 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
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 they are both angel
investors and also you know hedge fund
investors too so they might serve two
roles but for the most part our hedge
fund our locators are a very different
group of you know they're fun to funds
or family offices very different group
than the you know traditional VCS and
you know other high net-worth
individuals that we raised from on the
operating side so so we did do that and
then I forgot your first question pretty
much explained it it was just why did
you need to raise capital oh yeah I'm
desperate right in times like this when
everyone's in a crisis - right it's like
if you if you need the money would I
rather own a hundred percent of a tiny
pie or what I'd want to expand that pie
and known a small slice the big pie and
I was like well for my career path right
now you know I'm not that greedy and 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
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
capitalists who were in it for the you
know it's like feels like a marriage
right because they're in it for like
that ten year you know six to ten year
haul basically and then there's the kind
of shorter term investors on the fun
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 heard
very little track record and you know to
be honest not much to show how are you
able to get someone on board on the
venture side is actually easier to
answer because of entry side literally
you just go to the startup events and
pitch you know those events usually at
the angel on 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 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 at that stage 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 strategy
in terms of you know having it was a
little bit more about showing some
numbers and we couldn't really because
we didn't have any numbers at the time
to really show for high-frequency
strategies we had to you really just do
what we can so like we would show we
would show like some back tests for
instance 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 over fit we're not trying to you
know show you the best one and although
most investors probably didn't believe
it anyway they're like you know they've
never seen a bad back to us before right
so it's pretty much useless but we still
you know tried to explain our
methodology we explained what we were
doing we did offer day one investors
more lower fees and higher controls so
more liquidity and that helped a lot to
you and also you know higher
communication channels in terms of maybe
I would send
weekly emails to certain investors so
they would 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 and then you know
obviously offering them a discount on
the fees and lower
you know better liquidity terms so they
could maybe redeem at any point in time
maybe it get rid of the lock-up period
you know things like that that helped a
lot and one thing we realize is even if
we got rid of lockup here you know no
not a single investor redeemed you know
within let's say 1 or 2 months or even
within a year usually when an investor
makes decision like that if they're good
allocator they're in it for the long
haul but they just like having that free
option available in case there's a
pandemic you know in case there's some
event where they actually absolutely
need the liquidity so but yeah that was
really helpful from day one to kind of
get that and then there also what's
interesting Aaron is there also are
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 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 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 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 it's a good question
absolutely yeah
especially surprisingly I would say
after flash boys came out that was when
we got the most amount of interest
ironically 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 changed
their language on their webs
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 bad reputation and image to
associate 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 frontrunner
background it'll run a single person out
there and but we do high frequency
trading we're exactly the definition
that you would expect of 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 of thousands of
times per day you know recently like
this year the the highest we reached 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 and so we were doing that we
were like well we're hft so people
Google us we show up you know SEO we're
we would show up at the very top Without
Really Trying and people just reach out
to something like hey you know we heard
about you can we schedule phone calls so
so that happened as well after a certain
point in time and was relatively you
know nice and helpful I mean obviously
people would always have concerns like
hey you know what do you do 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 and it's
just not the type of trading that we do
and we don't you know do what they
described in flash boys were there
blasting hole you know through mountains
under the river or whatever to try to
wire between different exchanges back
then you know we literally were just
trading within 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 it made it a lot easier back
then and then you know over time as well
the I think a lot of the myths in the
book have been debunked or explained by
folks over time so most of the investors
have gotten a lot more you know educated
about our field which has been helpful
to I'd like to spend a little time
speaking about how you build out the
infrastructure so you mentioned earlier
that you built everything from the
ground up from scratch internally is
this unique for HFT
fun to do so 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 still relatively new
at the time or just hasn't quite been
commodified yet you know it's something
that you kind of just have to do to get
up and running I will say today because
after flash boys came around actually
there are a lot more startups and I
started doing hft technology you know
maybe like feed handlers for hft or you
know thinking about open sourced 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's 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 so you know that I guess
centuries-old question of bio versus
build to be honest I felt like we didn't
really have a choice but to we can even
if we wanted to buy we couldn't afford
it so I build it was on our end right
right I mean oh yeah it was probably a
lot of cost upfront 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 ideal scenario is that you
own all your own software now it's great
today it was really awful before we
launched I mean you know there were many
frustrating days because we just had
such an unknown timeline of like we had
to we had roadmaps he tried to map it
out you know investors demanded to see
roadmaps and budgets and things like
that and we could try our best to do the
roadmap and then it felt like I don't
know if you know like Zeno's paradox
maybe I don't know it was like one of
those paradoxes we fell into where one
task turned into to to turn into four
and it just kind of 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
deal with for you know a small team at
the time so yeah I was definitely
unexpected and quite frustrating to be
honest before getting to launch I think
every every company underestimates how
much time it takes to get to launch
unless you're like you know if you
non-quantitative or if you ready 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 got to set
up the legal structure of the fund you
got to figure out you know who your
auditors administrators etc they all
have to be ready to turn it on with you
at the same time you know so all those
things combined made it quite a lot of
work on our end and 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 and
hft business which is probably a lot of
folks what did you have to build like
what took two and a half years what all
the different components that had to be
developed there's so many you know it's
like pretty much a type of we had to
build the entire trading system and
ecosystem from scratch so everything
from because we need direct market
access right so we're literally placing
trades ourselves 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 figure out what's going on to
cancel things and that also included
risk management tools that we had to get
basically verified by all the different
you know brokers exchanges that everyone
had to make sure that our risk checks
were enough and that they were stable
and that if there was some 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 to make sure
that we didn't accidentally you know
tank the markets ourselves
single-handedly or make any big errors
or mistakes on that and so so that
requires quite a lot of work 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 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
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 definitely took a
lot of patience and you know energy and
effort and a lot of you know checks
making sure all the checks balances
whatever I'll see how it was in place as
well yeah so that was a big thing and
then you know how do you process data
right it's another big question of what
are how do you get the data that we you
know we wanted we had data directly from
the exchanges but then how do you
process that data and turn that data
into an actionable you know some kind of
value that we could extract from it and
so how do you do that as well you know
that took a lot of time to figure out
and to process and to and then you know
data pipelines we they would always
break we would always have some kind of
issue that happened and so figuring out
how do we timestamp that data how do we
process that data was also a big
question that we would have in mind as
well yeah in general it's a it's quite a
nuanced process and it just had to all
be relatively perfect on day one or else
you know hedge funds rarely get second
chances I would say unless you have
unless you're famous
and your name is already known and order
you try to make yourself known but I'm
back then we weren't so you know we
literally just had one shot and knew
that we couldn't mess it up so a little
kind of scary but I'm where we do feel
fortunate and lucky to have made it this
far today hmm and sign that what gave
you the confidence you know after two
and a half years of building us 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
to be honest we we did it 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 in the live environment -
which was great but even then you know
it's hard to replicate a hundred percent
what's going to happen in reality so we
did as much as we could test as much as
we could and then one day I remember the
FIR
they'd be launched we were just kind of
like you know what screw it let's just
let's just try it let's just do it you
know we got to take her we were very
risk-averse at the time too and we're
scared hey 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 that's literally you know
what we did and 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 for the markets
and were able to fine-tune the
strategies even more and just continue
going from there so 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
you know felt like I was a fraud all the
way up until we imposed and so we're
like oh we're finally a real hedge fund
you know and we can have a real track
record to show people which was
fantastic you're in business yeah just
recapping those first few years looking
back on it what would you say was some
of the you know the breakthrough moments
which she had and also some of the
unexpected challenges which she came up
against there's so many I don't even
know where to start I would say like
when we first started the business 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
because we had such a limited budget but
there were some things that were worth
hopefully you know we thought were worth
spending some money on like a good
lawyer was a good example or maybe
finding a good broker you know they
someone with reputation as well auditors
etc we could splurge on and then you
know things that we valued like we want
it to be a flat organization back then
everyone was called partner and you know
see and then it actually did not go too
well and I have so many reasons for that
and we wanted to have perks almost like
we 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 those are both really bad
ideas on the organizational side you
know you don't want to call someone we
hire like literally like head of hft
from firms like Citadel and you know get
Co back then and other firms and a kcg
back in the day as well
and they would come in and be like wait
a second you know why do I have the same
title as this kid who graduate 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
he or she called a partner we were like
oh gosh you're right you know we
realized that people actually felt less
equal because of that rather than more
equal which was pretty bad and then in
terms of perks as well just didn't work
out you know people abused the perks
like crazy and it was kind of unfair
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 you know
that it's okay to go for a smaller as a
small hedge fund that you know it's okay
your investors aren't gonna look down on
you for hiring a smaller lawyer you know
so long as they are still qualified to
do their job right so just things like
that we made a lot of mistakes on to
anything of what else we we did so much
wrong that it's just hard to even begin
to 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 we worked in
my apartment for some time until we were
kicked out we were evicted and the
reason why we were evicted was actually
kind of a random read all the cops
knocked on my door late at night but I'm
what happened was the we were we had
built our server cabinets literally in
the closet of one of the like the master
bedroom basically and we rigged our own
electric you know basically we rewired
the electric system and built our own
box and stuff and I think Jay weighing
one of my co-founders he actually
electrocuted himself in the process so
we were clearly not experienced at all
we should have hired a you know a
unionized I don't know person right to
do this and 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 we were literally using up all the
electricity in the building and you
could also you know people thought that
we were like we had a marijuana farm or
something they like literally people
we're running some kind of marijuana
farm and so that's why the cops knocked
on
or thinking like you're 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 they saw there's computers and
monitors everywhere and they're like
what are guys some genius hackers like
if you thought were hackers it's like no
no no this is you know this is a small
business here and you know I did live in
the other bedroom so technically it's my
whole my home business right and they're
like no this is not going to work you
gotta you gotta get out of there and get
a get a real office and then the next
day we literally packed up and moved to
we work back when we worked first open
in Boston at the time our rent shot up
we were used to pay 4000 per month for
rent and then we work it was 12,000 per
month and this is three times as much
and the room we were stuck in you know
we work they pack you like sardines in
these tiny little rooms and literally it
was the size of the server closet that
we were that we had at the apartment so
it was just what a crazy just a turn of
events like that that really changed
Jeannot 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
[Laughter]
if we look at Dome yard where it is
today
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 a bit just on
average yeah
recently 2500 ish a little under 2500
trades per day which recently has not
been a lot we've done more more in the
past you know depending on the market
environment and stuff like that but in
general it's in the up in the thousands
you know and completely automated and
people are you really high frequency
tray you know this is high frequency
trading you know they're all intraday
and holding periods anywhere between I
mean I know it sounds like I'm not
marketing and we're not fundraising just
gonna clarify that right now so that
people don't you know as CC doesn't come
after me
again as I'm just saying we're not
fundraising but uh you know we holding
period wise anywhere between you know
let's the split second you know like
less than a second microseconds all the
way up to hours these days and we
consider the hourly you know holding
period so we caught we call the 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 we live in kind of
different universes it feels like a
little bit but but yeah 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 we used
to do some overnight stuff but um you
know realize that our nation was too in
the the high frequency you know me I
guess intraday type of strategies and we
also figured that the additional edge we
would get from holding overnight
wouldn't 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 it's just
something that we haven't really 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 two and a half thousand
right she for some reason thought that
number would be a bit higher oh yeah it
could be up to I don't know how much ten
thousand
you know twenty five thousand it really
depends on what we're trading and how
the markets are reacting and how much
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 quite a lot
because there's you know lots of
speculators lots of day traders and and
a lot of institutions everyone's just
very active right now so it did shoot up
a little bit but for now you know it's
down to the 2000s the number of trades
America is that somewhat correlated to
the the volatility of the market
questioned us kind of yes to know
depends again on what kind of strategy
were implementing you know usually
during very high volatile you know
periods like like this basically we tend
to have a lot higher volume and the hope
is that we perform better and can
maintain some kind of neutrality to the
markets so that's a that's definitely
the case for I would say of actually
most high frequency trading firms as
well as just during periods of you know
higher volatility there tends to be just
more naturally more opportunities out
there for folks to to see and utilize
right and are you able to share you'll
win right oh man I actually did not
that's one thing I did not ask the
lawyers about but in general I will say
you know we were really happy with our
performance this year we did have like
two very particularly disappointing
months in general but um overall you
know we were definitely still by a huge
margin beating you know all of our
benchmarks so it's it's been a great
time for us too and also because it's oh
this is also a first recession we've
been through - because we didn't go
through oh wait I was still in school so
so the other thing is because of this we
were able to prove ourselves and be like
ha you see we can finally show we've
been through you know the wringer we've
been through this bad these crazy times
and that week you can show that we can
you know go through those and more so
you know we've had some disappointing
months but in general it's it's been
alright okay and how about average daily
turnover of course that would vary with
the number of trades but just broadly
speaking oh man just turning over so
much it can really add up to quite a lot
I mean you know we would trade like
recently again like the most was 7.1
billion
I think per day this year so we've
gotten quite high and substantial in
terms of the volume and turnover rates
and it'll probably continue like that
for hopefully for sometime right and
given that you're trading so much and I
don't know you win right but
I presume it's it's you know above 50%
are you profitable at the end of each
day like I presumed losing day would be
pretty rare so we are not necessarily
profitable at the end of each day and I
think that's something you know
unfortunately for us and maybe even for
other firms as well it's 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 I'll say probably not most
hft firms you know we can end the day
losing you know having a negative you
know much less money than like the day
before that does happen as well so you
know the goal is though that we do aim
for a hundred percent winning days
nonetheless and 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 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
you know does happen to all companies
all firms but um it's its life right and
we've learned to how to deal with those
types of days how to mitigate those
risks and learn from those 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 were not as active in at
this point in time we've we've traded
before in the past but I'm at this point
in time it's just not the market for her
for us
most of our strategies are concentrated
in in futures and we have a lot of FX at
this point in time as well we do have
some option strategies that we're
utilizing at this point too so yeah a
lot of I guess you know
delta-1 strategies and 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 it
really just depends on the conditions
and you know what what we're testing
we're constantly testing things behind
the scenes and figuring out whether or
not it's the right time to pursue
something
and is that all future's in the US or
not all of them but is it or are you
more more focused on like indices
futures or commodity futures or pretty
much the the whole mix it's the whole
mix yeah we're pretty agnostic within
the future space at this point in time
they do have to be products that are you
know relatively frequently traded or
else it would you know not be worth it
for us to deploy strategy within so
they're they're heavily traded products
that we can hopefully take up you know
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 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 broad
question but just on your strategies in
such a highly competitive area of the
market that you compete in how do you
seek to generate alpha in terms of
generating alpha there's 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 what are some products that
you know we we can kind of be able to
map out and be able to make predictions
on so a lot of its based on you know
small predictions maybe a few seconds
ahead of time on where different trades
and products will go so so that's a big
portion of it but then also looking at
other I think of other things we we do
on this side let's see just mapping out
in general you know hundreds of
different signals and you're 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 a signal
selection throughout the day as well so
figuring out you know what those signals
are and what's gonna make the most money
during this certain environment and then
when the vibrant changes you know what
what kind strategies we want to pull
back and would want to deploy so that's
always a really tough question but it's
surprising because that 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
a bit to do some you know basic strategy
selection type processing is on our end
what data drives the majority of your
trading signals is it audible cologne
like looking at the market depth or is
there additional input from other data
sources - it's mainly market depth yeah
so just order book data is extremely
helpful for us we do have a little bit
of what we call metadata you know you
might call alternative data in different
types of areas - whether that's usually
it's like you know things like calendar
data right like every high-frequency
trading firm needs to know when bank
holidays are and things like that or
maybe things like SCC filings or big
economic you know announcements or you
know Fed meetings things like that you
know that kind of stuff does need to be
factored into you know the strategy as
well so we can't just be completely
focused on the market data but just also
keeping in mind all the other components
of data as well so yeah in general
though I think the biggest source is
still you know just market data that's
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
other sources of alternative data that
could help us out here and there as well
okay can you speak to almost like this
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 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 one
and a half months you know and then
within three months the strategy is you
know pretty much almost worthless at
that point in time and so it's a process
of constantly revising the strategy use
the process of constantly finding new
strategies as well and modeling those
strategies and different environments to
see you know how they would do
and and then also figuring out why do
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 maybe because the environments
changed in 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 just
important to be able to figure out when
it happens and why and be able to move
on quickly and not get too attached to
one or two you know strategies but you
know we have like hundreds and hundreds
of different types of signals to
potentially deploy and take a look at so
so I'm just making sure we're careful
there I know there's stories about like
I don't know if you've heard those
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 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 and you know when you
steal a strategy by the time you get to
launch three months later that strategy
is already dead and it's just no longer
effective so that's definitely something
that we do as well on our end is just
you know it's not on purpose but just
the nature of high frequency trading
it's just that the opportunities you
find may not necessarily last for a very
long period of time and they might be
really niche so once we find it and once
that niche kind of goes away then we're
on to you know hopefully the next thing
during the trading day what level of
human import or decision making is there
obviously the trades are all automated
but is there any human intervention
during the trading session oh it's a
really interesting question well first I
will say like a lot of people have this
vision of - to trading being you know a
bunch of robots taking over the world or
you know machines and 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 that's
really not the reality at all you know
the these trades are being heavily
monitored and you know by humans
throughout the day when we're trading
and you know really just gathering all
kinds of data about what we're doing and
stuff like that there's a huge human you
know obviously we're not having
human sit there and click to make those
trades you know there's no it's just
being placed automatically but there's
always a human behind the scenes to
tweak the strategies or to tweak some
parameters or you know change some of
the risk parameters things like that and
a lot of it's in code but just kind of
changing that coding of what the
strategy might look like so so yeah
there's a surprisingly large human
element in terms of what we do and you
know the strategies also there are only
as dumb as the humans who are you know
creating them hopefully as smart but you
know I would say that you're they're as
dumb as the person who created it so
absolutely you know we need that human
intervention constantly to make sure
that nothing goes rogue or you know
crazy the other thing is like I'm trying
to think of you know the markets as well
right because 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 you know the financial markets
things are constantly changing to the
point where even today right you know
you see a lot of things like oil going
negative you know things that
economically it's like in your textbook
you know you would never it just makes
no sense you know and that happens all
the time and a lot of that might be just
it's just driven by human very human
behaviors and so you need to have a
human behind the scenes to understand
those behaviors in order for your
strategy to do well you can't just have
a strategy that you know you can't you
know even if it's a cut 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 something's just
not the best start to the ETF ai driven
you know stuff yeah absolutely my my
personal opinion as a high-frequency you
know ironically has a high affinity
trader is that there is an important
human element that um you know we can't
forget and behind the scenes now as you
are high-frequency trading fund
obviously Spade and reducing agency as a
big factor in what you do what measures
do you take to reduce latency but
internally and externally you know the
biggest thing people always imagine is
like oh you're doing you know what they
didn't flash boys but we don't do any of
that you know biggest thing is on our
end it's purely pretty much you know
just internally making sure
okay let's you know gather data the fast
as we can let's make sure that once the
data is in place you know between
getting raw data and processing that and
turning it into an actionable strategy
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 on live data and be able to you
know place those traits as fast as you
can and and you know for latency it's
basically you know as soon as we
discover a decision we want to make the
time between that decision and actually
implementing it you know that kind of
that time we do try and reduce as much
as we can you know whether that's just
through direct market access you know
with the exchange or making sure that
you know our order management system is
structured in a way that is as fast and
efficient and can process you know a
bunch of orders at the same time without
having you know too much lag
I know we've had I'm trying to give
we've had some I know on the development
side like we'll maybe consider like you
know even just things like shortening
names of stuff might help a little bit
too so I'm just making sure that our
names are a little bit shorter so that
computer wise you know it takes a little
less time to process so stuff like that
might might work as well and then making
sure that we optimize for different
strategies on the latency side you know
the strategies themselves so making sure
that we're optimizing on that front so
that they can be you know code wise
right to be a little bit faster and take
a little less processing time in order
to complete so so that's definitely
important as well I will say one other
thing those you know I know everyone
obviously talks about speed and thinks
about speed when it comes to high
frequency trading but um
on our end I think we found our niche in
terms of you know where we're not trying
to aim for being like the top fastest
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 we used to we
used to like you know assemble our own
Hardware buy the best thing out there
and then we realized
year they're gonna release a better I
don't know FPGA a better you know piece
of hardware somewhere out there and do
we really want to pay an extra million
dollars is it really worth it you just
realized it just wasn't at some point
and they were lower hanging fruit in
different areas a big reason by the way
it's also because at the exchange level
if their lien C's are slow and there's a
lot of jitter happening at the exchange
level then even if we did place an order
really fast 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 we call lowering fruit in
terms of maybe better signals or looking
at better products out there that you
know we could take more advantage of
without having to compete at the you
know microsecond level all the time so
that's you know going for strategies
that are have longer holding periods as
well and 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
capacity constraints and that's what's
kind of interesting about what you guys
do is you are fund where most traders
who are running hft strategies mostly
prop model whereas your fund and I guess
that's one of the reasons is because hft
strategies typically have constraint
capacities how do you deal with that
aspect of it now it's a great question
it's one of the biggest things that
keeps me up at night actually is some
you know hft is although people always
assume it's this menacing thing you know
we're not a scalable business the
industry is just not scalable given the
nature of what hft is you know and and
that's that's fine I think 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 weren't debt so we
didn't have any money at the time to
trade and we supposed well you know even
if we could start a small fund in the
mean time it would be better than
nothing and at least give us enough
abus'd in our early-stage careers to you
know how have a
to know the industry better and also to
hopefully you know learn a thing or two
so so that was the big thing there but
um you know if we could like let's see
if we could start today yeah we would
probably be a prop shop 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 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 you know to have to do the weekly
you know sending newsletters out or
sending emails and you know answering
questions and stuff but also a
regulatory wise to you know registering
with all the different uh you know SEC
NFA whatever other countries and
jurisdictions that we want to be
involved with so that is you know just a
lot of administrative work cost you time
and money
having a director and the fund you know
thinking about the legal setup of the
fund structure all those other kind of
stuff like that costs surprisingly a lot
of money even before getting to launch
and so so yeah that was kind of a
trade-off that we had to make I guess in
order to start the hedge fund structure
right now Christina just one last
question before we 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 you know never loses and
stuff like that and that's definitely
not the case at all it's a very you know
it's fallible it has issues and 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 still died for one reason
or another or they got acquired or they
just were no longer 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 know back
in 2012 or 13 yeah
you were great you know you you're good
Congrats on being one of the you know
earlier funds right in that space but if
you started to crypt of fun today you
know most of the Alpha is gonna be
pretty much gone you know so it's kind
of a similar thing where it gets harder
and harder to compete as more people
flood the industry like that but I will
say like it was really surprising for me
because 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 you know
almost like heartbreaking to see and
then the day that we started launching
strategies and stuff you know we were
super nervous I remember turning it on
and literally was nothing like we
weren't trading at all and just nothing
was happening and we're just waiting
around the table you know our in our
office just huddled there being like
what's going on you know why isn't
anything happening and then we just kind
of gave up might in a day just went to
go grab I think I went to go you know
eat some ramen or something and then
someone called me over they like
Christina no comeback is finding the
starting to train I was like oh my gosh
you know the markets right about to
close and we literally started trading
at the clothes and we checked our
balance and we had made $70,000 you know
in like a minute
and we were like oh my gosh that's
that's more money than my parents make
combined in a year you know and that
feeling of like oh my gosh the half 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
you know we we felt very 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
unfortunately I can't cuz we've gotten
in trouble for sharing it in the past
for like it's considered marketing and
it just does not go well with we were
audited quite extensively in the past
couple of years or so 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 marketing in
one way or another so unfortunately
we're not allowed to mark I would love
too 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 fun
that can market that kind of information
understood that makes sense I mean the
last thing you want is is legal hassles
so totally understand 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 if somebody wants
to find out more about you I know you've
given a few talks and that type of thing
which are available on YouTube you're
also on Twitter can you please share
your Twitter handle sure it's just my
name it's at Cristina Qi which is
spelled Qi yeah please feel free to
check it out I'm a little crazy on
Twitter which a lot of people don't like
but I think there needs to be more loud
vocal voices in this industry so and
hopefully hopefully I have some reason
in terms of mostly stuff I say and I'm
not just completely crazy like some
other folks in this industry which is
fine but you know everyone has a
different personality so feel free to
you know check that out and then also
recently I've been working on a data
venture as well so if you guys are
interested in market data and
infrastructure colocation that kind of
stuff you know definitely feel free to
reach out as well because we do some
really cool stuff on that front too 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
basically you know one of the biggest
challenges we faced when we were
launching the hedge fund was we had
spent over a million full amount of
money over a million dollars on data and
infrastructure and and we feel like that
barrier to entry is way too high we want
to lower that barrier for other folks
out there and just so you know this has
nothing to do with Dome yard we're
completely unaffiliated you know that
we're not front running in a dome here
it's not taking that data at all from
anybody's that's a completely different
venture
but basically just offering you know
data that's a lot it's the quality that
we expect from you know institution
quality data but we sell it all apart so
it's broken down you can buy literally
just one security if you wanted to or
you know the entire thing if you want to
do 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 and the goal is like you
know people can purchase data from
various different sources and it's we do
live in historical so you can have live
data feeds from various different
sources but in smaller chunks than what
we typically see in the market so yeah
that's a it's been fun to work on that
it for me it's meaningful because that
you know I've been spending people
always ask me questions about morality
like you know you're an hft right like
how a moral can you be and I've always
wanted to do something that hopefully
would bring some value to the industry
and have some meaning and so 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 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 kind of
take over a lot of the day-to-day you
know operations and things that I didn't
want to do as much so so that that's
been very lucky and then you know to be
able to start this data venture and
hopefully help people out that's been a
dream come true for me yeah that's cool
that's really cool I'll make sure to
include a link to that in the show notes
and if someone wants to find out more
about dome yard what's the website it's
just do me a comm if people know we were
named after the MIT dome in Harvard Yard
back then we didn't want to name the
fund after ourselves and then by
coincidence the comm was you know pretty
much free so we were able to snag that
and quit pretty quickly and got pretty
lucky with the name nice nice well
Christina very grateful for your time
really appreciate your doing this thank
you very much and we'll talk again soon
Thank You Aaron it's been an honor
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