ADVERTORIAL
Now contrast this to a ranking based methodology ( Figure 2 ). In this approach we score the broker ’ s ability to access liquidity by ranking the average trade value they achieve in each venue . For example , in Venue 1 , Broker E is ranked number 1 with a trade value of 410,000 per execution and Broker D is ranked 6 with an average value of 61,000 . We then take the weighted average of the rankings across all venues to determine the overall score for average trade value . Now not all brokers will access all venues , to ensure a reasonable sample dataset we restrict measurement to venues where the broker has executed a minimum of 1,000 trades .
In contrast to the first approach , when using the second methodology , Broker F ranks number 5 . Sourcing some large blocks on a single venue does not have the same weight to overcome their relatively weak performance across most venues . Broker E is still the top scoring broker because they rank either 1 , 2 , or 3 across most venues .
While all methodologies have their own advantages and disadvantages . The virtue of an approach that combines rankings with averages is that it rewards consistency of broker results when interacting with pools of liquidity .
Obviously average trade size is only one
Figure 3 : Broker Scorecard Based on Overall Rankings
Broker Avg . Trade Size
Price Impact
Adverse Selection
Broker Scorecard – Overall Ranking Pct . of Price Moves - 1 Second
Price Improvement
Spread Capture
% Trade Through
Eff . Spread
Avg . Rank - All Metrics
Broker A |
3 |
5 |
2 |
4 |
5 |
1 |
3 |
2 |
1 |
2.9 |
1 |
Broker B |
2 |
6 |
1 |
6 |
4 |
3 |
2 |
5 |
4 |
3.7 |
4 |
Broker C |
4 |
2 |
3 |
3 |
1 |
4 |
1 |
3 |
6 |
3.0 |
2 |
Broker D |
1 |
4 |
6 |
5 |
6 |
6 |
4 |
4 |
2 |
4.2 |
6 |
Broker E |
6 |
3 |
5 |
1 |
2 |
5 |
6 |
1 |
3 |
3.6 |
3 |
Broker F |
5 |
1 |
4 |
2 |
3 |
2 |
5 |
6 |
5 |
3.7 |
4 |
metric . Other metrics evaluate broker performance with respect to minimizing post trade price movements ( both price impact when removing liquidity and adverse selection when adding liquidity ), spread capture , price improvement versus the far touch , minimising the number of trade throughs and other factors in measuring overall broker performance . We include but downplay order level benchmarks such as Implementation Shortfall and Interval VWAP in the overall measurement as these results are so dependent on when the buy-side client gives the order to the broker . Instead we put more focus here on how brokers
Trade Benchmark Performance
Overall Broker Rank
interact with the market and specifically individual venues to measure how well they are managing the buy-side ’ s order flow .
An overall ranking scorecard might look something like Figure 3 above .
Creating a meaningful broker scorecard for trading performance is still in relatively early days compared to other aspects of measuring best execution . Still , it is an important tool for monitoring broker performance as part of the overall buy-side investment strategy . We encourage more dialogue in this area between the buy-side , sell-side and analytic vendors with the goal to develop common standards for scoring .
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For more information please contact Marc Carolissen marc . carolissen @ thetradenews . com + 44 ( 0 ) 207 397 3807