[ D ATA ]
traded by combing active, passive and
dark fraction of volume as an RGB
triplet, while the brightness represents
the fraction of the overall order done
at the given time on the given venue.
We can see that Broker A mixes
both aggressive and passive execu-
Figure 3: Broker B – Low Volatility
tions across multiple venues while
Broker B largely executes on a single
venue throughout most of the
trading day.
This technique can easily be used
across an aggregate of thousands of
orders to identify the broker’s order
Figure 4: Broker B High Volatility
routing tendencies.
In Figure 3 (low volatility), Broker B
relies heavily on a single trading ven-
ue and is largely passive in execution
style. However, in a high volatility
environment, order routing switches
to using many venues and becomes
somewhat more aggressive.
The use of color allows us to clearly
see differences in venue selection,
timing and the degree of active versus
passive trading. More importantly,
the colors, brightness and size of each
box can be converted into numerical
equivalents which allow us to quan-
tify the differences for best execution
and specific applications such as Algo
Wheel selection.
LiquidMetrix analyses consolidated performance
figures for stocks on major European indices and the
changes from the previous quarter. The charts and
figures above are based upon LiquidMetrix’s unique
benchmarking methodology that provides accurate
measurements of trends in market movements.
Trading Volumes on lit markets including auctions
are taken into account, as well as dark trading on
the major MTFs.
98 // TheTRADE // Spring 2020