[ D ATA ]
Figure 1: Broker A , Symbol = AMD, Date = 2019-05-03
Figure 2: Broker B , Symbol = AMD, Date = 2019-05-03
time. The second dimension we care
about is the trading venue – we want
to answer the question ‘where did we
trade?’ The third dimension we care
about is the way we interacted with
the market – did we cross the spread
and remove liquidity? did we post our
order passively in the book provid-
ing liquidity? or did we execute in a
dark pool? – we want to answer the
question ‘how did we trade?’
Unfortunately, pictures are two
dimensional, so how can we show
these three dimensions in a single
picture? Well, fortunately, there are
colour pictures! So maybe we can
answer all three questions by devel-
oping a colour image. We can show
a time dimension along the horizon-
tal dimension of our picture, and a
venue dimension along the vertical
dimension of our picture and then the
colour can indicate how we traded.
We use the property that any colour
is a mixture of red, green and blue. So,
if we use red to represent the ‘active’
volume from crossing the spread,
blue to represent the ‘passive’ volume
and green to represent dark volume,
then we can combine three ways of
interacting with a venue into a colour
which is itself a mixture of active, pas-
sive and dark volume. The intensity
of the colour is proportional to the
amount of volume while the actual
colour is determined by the distribu-
tion of active/passive/dark. When the
pixel is red, it means the volume in
that bucket was all active. If the pixel
is blue, the volume was all passive,
while if green, then the volume was
all dark. Other colours are mixtures of
these three ‘primary’ colours.
This has real-life applications in
evaluating the order routing of differ-
ent brokers and can be used as an in-
put into making algo wheel strategies.
Analysing execution data in this way
allows us to clearly see the differences
in order routing between brokers
both under similar and different trad-
ing conditions. How differently do
different algos trade? How similar are
different brokers’ algos? How does my
trading strategy influence my realised
market impact?
Consider the differences between
the routing in Figures 1 and 2 above.
These two images both show a
single order in AMD done withing
six weeks of each other. The x-axis
represents the time of day, and in
this example shows 30-minute time
buckets between the open and close
of the market (9:30 – 16:00). Each row
shows a different trading venue. The
colour shows the way the order was
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