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Quantitative Finance · Glosario

¿Qué es Dissemination fairness?

Definition 12.3 Networks, Hardware and Trading Infrastructure · Capítulo 12 — The Asia-Pacific Map

Dissemination fairness is the property of a market-data distribution that recipients in the same service receive each message at the same time, up to a spread that does not depend on who they are: measured by the spread of receive times for one message and by whether the order of recipients persists from one message to the next.

Simulation, not a measurement of any venue: mean receive delay of a tick by the member’s login rank on its port, for the four busy servers of the model (three ports of ten members each; 5\, µ s per copy at the centre, 10\, µ s per copy at a port, exponential jitter of mean 1\, µ s; 200 ticks). Each member’s delay is fixed by two login orders. Data: fig_asia.py, nw_asia.rank_curve().
Figure 12.3. Simulation, not a measurement of any venue: mean receive delay of a tick by the member’s login rank on its port, for the four busy servers of the model (three ports of ten members each; 5 µs5\,\text{µ}\mathrm{s} per copy at the centre, 10 µs10\,\text{µ}\mathrm{s} per copy at a port, exponential jitter of mean 1 µs1\,\text{µ}\mathrm{s}; 200 ticks). Each member’s delay is fixed by two login orders. Data: fig_asia.py, nw_asia.rank_curve().
DesignFirstMedianSpreadRankFirst beats
(µs\text{µ}\mathrm{s})(µs\text{µ}\mathrm{s})(µs\text{µ}\mathrm{s})correlationmedian
Unicast, fixed login order16.065.6107.71.00100%
Unicast, randomised15.170.7110.20.0788%
Unicast, randomised, no secondary15.269.0106.90.0151%
Multicast10.010.78.4–50%
Table 12.2. Simulation of four dissemination designs (the parameters of Figure 12.3; 126 members, of whom six on the secondary server, which the fourth design closes): one tick’s first, median and spread of receive times, the rank correlation between consecutive ticks, and how often the member first on one tick beats the median member of that tick over the next 200 ticks, both reacting in 20 µs20\,\text{µ}\mathrm{s} with a standard deviation of 5 µs5\,\text{µ}\mathrm{s}. Data: nw_asia.scenarios().
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