Matthew Trudeau is chief strategy officer at crypto asset exchange ErisX. The opinions expressed in this article are the author’s own.
The following article originally appeared in Institutional Crypto by CoinDesk, a free newsletter for institutional investors interested in crypto assets. Sign up here.
Recently CoinDesk published an article titled, ‘High Frequency Trading is Newest Battle Ground in Crypto Exchange Race’ that discusses trading venues offering direct connectivity to their matching engines.
While ErisX has only recently launched its spot market, other crypto exchanges announced
their intention to and/or began to enable trading firms to
cross-connect (a direct network connection within the data center as
opposed to a connection routed over the internet) to their matching
engines at least a year ago, so this is not a new development.
Cross-connects are a standard service in global capital markets,
utilized across asset classes and market participant types, so the
characterization of such connectivity options as “rolling out the red
carpet for high frequency traders” is peculiar. Based on the article,
none of the exchanges that responded, including ErisX, actually directly
offer colocation services (colocation is provided by the datacenter owners/operators).
One of our core views at ErisX is that precision in discussing any important topic is critical, be it institutional interest, custody,
etc. so in this piece we are applying the same rigor when discussing
“high frequency trading,” “colocation” and “data center-hosted”
exchanges vs. “cloud-based” exchanges.
Because ErisX is one of the exchanges mentioned in the article as
trying to attract large algorithmic traders with “colocation” offers, we
want to more precisely define “algorithmic trading” and “HFT.”
We also want to explain why automated trading can be beneficial to
the market and address the distinction, missing in the CoinDesk article,
between “cloud” versus “data center-hosted” exchanges and why exchanges
hosted in data centers present superior performance and benefits to
market participants.
Defining HFT
High frequency trading (HFT) has been a topic of debate in large part
because of a lack of precision and/or understanding by commentators
even in traditional markets. There are different kinds of “HFT” but for
this post we will define it as automation of trading strategies enabled
by computers to transact a large number of orders in fractions of a
second.
Leveraging algorithms, high frequency traders analyze market
conditions to manage risk and execute orders based on predefined trading
strategies. Blackrock, a global investment management company, did an
excellent job of further distinguishing a taxonomy of HFT strategies
along with their relative impact on market quality in a 2014 whitepaper US Equity Market Structure: An Investor Perspective.
We would add to the taxonomy in the graphic below a fifth category of fraudulent or manipulative strategies
that are prohibited in other markets, are not limited to HFT, and have
been shown to exist, although not exclusively, on many crypto exchanges
as we discussed in a previous post.
In general, automated market making and arbitrage strategies create
greater efficiency in the market as depicted in the above graphic by
integrating information into prices more quickly and efficiently
resulting in narrower bid/offer spreads, improved price discovery,
and fewer and more-fleeting instances of price discrepancies across
markets when an asset type, such as bitcoin, trades on multiple venues.
There is evidence that the cryptocurrency markets are experiencing
these benefits on the more reputable exchanges as a result of increasing
HFT participation.
In the past 2.5 years spreads have generally narrowed and become more
stable, and price discrepancies across trading venues have become less
dramatic and less frequent. The below graphic from a 2019 white paper Buying Bitcoin, published by the New York Digital Investment Group, demonstrates this effect from December 2016 through October 2018.
So, while there are a variety of trading strategies that can be
automated and labeled “HFT,” some contribute to market quality while
some detract from it.
It is important to note our definition of market quality includes
deep liquidity and tight bid/offer spreads, supported by fair access,
elimination or appropriate management of potential conflicts of
interest, and technology that benefits participants.
Cloud vs Data Center Matching Engine
The CoinDesk article mistakenly states that ErisX has a “hardware matching engine.”
In fact, ErisX has located the hardware (servers etc.) upon which its matching engine software runs
in a Tier 1 datacenter facility in New Jersey that services a high
density of major financial firms including traditional exchanges,
brokers and trading firms as well as communications firms, enabling all
new and traditional participants to quickly and efficiently gain access
to our markets.
Participants that already have a presence in this datacenter can
connect to ErisX’s matching engine via a cross-connect and our FIX API.
Additionally, ErisX offers connectivity to its matching engine over the
internet via Websocket API.
There is nothing extraordinary about this model. In fact, deploying
an exchange in a data center gives exchange operators the greatest
control of their entire infrastructure from network firewalls and
switches to servers.
This control enables exchange infrastructure to be
precision-calibrated to create the most reliable, consistent and
performant (lowest absolute latency and variability in latency)
experience, promoting fairness amongst market participants. Participants
can, in turn, precision-tune their trading systems and automated
trading strategies; market participants that host their trading
infrastructure in a datacenter (vs. the cloud) benefit from the same
level of control and precision tuning. This is a good thing.
In contrast, cloud-based exchanges have less control over their
infrastructure managed by the cloud operator in a shared general-purpose
environment, and as a result cannot yet achieve the same level of
reliability and performance offered by data center hosted exchanges.
To illustrate, at the risk of getting into the technical weeds, a
world-class data center-hosted exchange may offer round-trip latency in
the sub-100 microseconds (millionths of a second) range with 99th
percentile consistency and the capability to process millions of orders
per second, all with 99.99 percent uptime.
Cloud-based exchanges, on the other hand, may offer latency in the tens or hundreds of milliseconds (a
thousand times slower) with less reliability, consistency and
throughput due to the vagaries of internet routing algorithms. Further,
cloud-based exchanges may rotate the location of the system running
their matching engine periodically from one cloud datacenter to another,
introducing even greater latency and inconsistency.
Low and predictable latency enables market participants to better
manage their risk and pricing algorithms to ensure their best possible
quotes are posted to exchanges creating high quality liquidity. In
contrast, long round-trip order/quote/trade times resulting from high,
unpredictable latency do not allow participants to react as fast to
rapidly evolving market conditions. To compensate, participants may
quote wider markets and thinner liquidity.
The CoinDesk article implies that by hosting in the cloud, exchanges
create a fairer access model and/or protect retail investors. In fact,
wider spreads and thinner liquidity are a detriment to all investors.
The article also overlooks the reality that clouds run in data centers,
and latency-sensitive market participants can locate their automated
trading systems within, or close to the cloud data centers with or
without explicit approval from exchanges – essentially unsanctioned
“colocation.”
These firms access cloud exchanges faster than other participants,
just with less reliability and determinism than with a data
center-hosted exchange.
Conclusion
Automated market making and arbitrage, both forms of “high frequency
trading” strategies, contribute to higher quality liquidity and markets,
and the performance offered by data center-hosted exchanges enables
these strategies to better manage risk and react to fast-moving markets.
In conclusion, we believe that constructive automated strategies and
data center-colocated exchanges provide fair and consistent market
performance with benefits for all participants.
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