[ I N - D E P T H
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T C A ]
by considering certain factors such as the percent-
age of the average daily trading volume, spread size,
expected impact, and volatility when orders are
routed to them.
Comparing like-for-like performance is another
important part of the process, therefore all data
points are separated, and similar brokers and flow
are grouped together. When comparing similar
brokers, the analysis goes beyond which broker out-
or underperformed the benchmark the most. All
contextual metrics are measured, including spread
capture, fill size, momentum, impact, and reversion,
for example, in order to paint a fuller picture of
broker performance.
A weighted ranking score system is then pro-
duced to reveal the broker winners and losers in the
analysis, before trends or potential outliers that are
driving the ranking are identified. For the losers,
Hermes consults with the brokers to verify the
results of the analysis and work towards preventing
any continued poor performance. If this low scoring
occurs over a small sample size, the broker is placed
on a watchlist, which is closely monitored until the
results are either proved or discredited. A desk re-
view is also undertaken in circumstanc-
es where there are difficult market
conditions or flow.
The process for high-touch
and broker analysis is similar
to the analysis carried out for
algorithms, but Hermes com-
20 // TheTRADE // Spring 2020
pares algorithms side-by-side for
actionable insight not only for
selection, but for informing any
changes made to the algorithm
itself. If the algorithm is tweaked
in partnership with the broker,