[ A D V E R T O R I A L ]
they have the appropriate controls
and governance framework around
their venue on-boarding process
for you to be comfortable with
trusting that counterparty.
At Liquidnet we analyse a range
of different metrics, both at a par-
ent and child order level to evalu-
ate the execution quality a liquidity
source is providing. We call this
with SI liquidity is by reacting to
streaming quotes being consumed
by the counterparty. However, in
many cases these quote streams are
not available and the only option is
to send a firm order to the SI opera-
tor’s SOR and to allow them to react
to a quote on your behalf.
If this is the workflow a counter-
party is using, then what informa-
“It is incumbent on the execution counterparty to
have a very clear rationale for all the execution
venues they interact with on your behalf, and
as a result, they should be able to evidence this
rationale when asked.”
our Venue Ranking Model and it
can be tailored for different trading
objectives by adjusting the weight-
ing given to each metric. The
output of the model is reviewed as
part of our Best Execution Gover-
nance framework and Smart Order
Routing (SOR) decisions are taken
as part of that process.
Analysing mechanics
Understanding where your order is
being taken by a counterparty gives
you a degree of clarity, however the
next aspect to understand is how
these liquidity sources are being in-
teracted with on your behalf. This
is most often associated with Smart
Order Router mechanics.
Firm, conditional, RFQ, streaming
quotes; all different methods for
executing on different venues and
many of the venues offer multiple
interaction options. Which of these
methods is a counterparty using
when transmitting your order and
interacting with the different liquid-
ity sources? What is the rationale
for using one method vs. another?
For example, it is common thinking
that the optimal way to interact
26 // TheTrade // Winter 2018
tion is being passed on to the SI?
Is there any form of flow profiling
occurring? There are many differ-
ent questions that can be asked in
this area and there is an appropri-
ate situation for every method, so
no one answer is correct. However,
the ultimate goal is to gain an
understanding of how an order
is being handled so the process is
transparent and understood.
Analysing protections
Finally, there are many different
ways a counterparty can protect
your order when interacting with
the market, therefore which of
these, if any, are your counterparties
using and in what circumstances.
For example, does your counter-
party’s algorithm utilise a Min-
imum Execution Size (MES) or
a Minimum Average Size (MAS)
to protect against small fills? Are
these nuanced for different venue
types or even individual venues?
For instance, is the same MES used
for periodic auctions vs. condition-
al orders on dark MTFs? Intuition
would say this doesn’t make sense
given the very different average
execution sizes on each.
Are limit prices placed on child
orders sent to the market and
how are these set in relation to
any parent limit provided? Limit
prices offer one of the simplest
ways to protect against sudden
price movements or changes in
the primary order book spread and
liquidity. Some counterparties offer
the ability to adjust the sensitivity
of any child limit price model, so is
this set up appropriately for your
flow?
A participation rate constraint
can also help to protect against
sudden surges in volume at a par-
ticular price point; is this some-
thing utilised by your counterparty
and, again, is it set up appropri-
ately?
Conclusion
It has long been accepted that
analysing execution performance is
more of an art than a science, how-
ever, with the increased scrutiny
and monitoring requirements being
imposed on the industry, execution
evaluation is a process here to stay.
Focusing on key areas to analyse
and gaining a real understanding of
the details can help you recognise
what is important to your order
and workflow and to help you to
evaluate your counterparties, and,
ultimately, helping you to see the
wood for the trees.
1
See, www.fca.org.uk/publication/
multi-firm-reviews/algorith-
mic-trading-compliance-whole-
sale-markets.pdf
2
Liquidity Market Structure
Research: Q3 Liquidity Landscape
https://www.liquidnet.com/ex-
pert-insights/the-mifid-ii-liquidi-
ty-landscape-q3-2018