For trading businesses
Explore client, product and desk performance using your trading business data. Work with dashboards and an AI analyst on reports matched to your markets, reporting periods and revenue definitions.
Trading-desk client flow example · illustrative
Choose the questions and measures that matter to your business. These examples show different reporting needs within the industry; the available analysis depends on the records you supply.
Review client flow, product mix and desk revenue. Add relationship or benchmark records when the question concerns coverage or the share of a client's activity.
Compare products, clients and periods using your own volume and revenue measures. Keep currencies, units and attribution definitions consistent.
Explore counterparty, product and location performance. Add the relevant costs and contract fields when investigating commercial margin.
Three steps, in this order.
Client or counterparty IDs, products, dates, volume and revenue, plus the attribution or benchmark records relevant to your report.
Start with standard dashboards. Agree on the measures, reporting periods and business structure your customized views need.
Work with an AI analyst to investigate the available data and prepare reports. Review the definitions and results in the context of your business.
Short answers. The Help center has the long ones.
Client or counterparty IDs, products, dates, volume and revenue, plus the attribution or benchmark records relevant to your report.
The example illustrates one part of the industry. Standard dashboards are a starting point; views can be customized to your business and data as part of your agreed setup.
The report depends on the fields, history and definitions in your sample. Start with one question, identify the records it needs and confirm any gaps before relying on a comparison.
Analytics software for trading, compared · Alternatives to named products
Written for this industry: the measures, the data you already hold, and the arithmetic.
An institutional trading business dashboard organizes client inquiries, executed flow, and relationship coverage for a desk review. Follow a worked example from inquiry, trade, revenue, and contact exports, with reconciliation checks and a coverage-only variation.
Oct 2, 20265 min readHow desks should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.
Sep 3, 20264 min readThe honest answer to what hit ratio a sales trading desk should run: the 20 to 40 percent figures quoted on credit and rates desks depend on the product, on whether the ratio is by inquiry count or by size, and on the client mix, because a desk that is in competition on every inquiry from a large client will run lower than one that sees only the inquiries it is likely to win. This page gives the ranges by product, the three measurable things that set the right figure for one desk, and the table to compute before anyone quotes a percentage.
Aug 26, 20263 min readThe complete hit ratio calculation on ten RFQs from two clients in one product, small enough to check by hand: each inquiry's notional and outcome, the count-weighted ratio, the size-weighted ratio, why the two diverge when a client trades the small tickets and leaves the large, the tier the two clients land in on flow and hit ratio, and the assertion that traded notional never exceeds inquired, so a reader can reproduce every figure and then run it on their own RFQ log.
Aug 13, 20262 min readThe ten client KPIs a sales and trading desk should run on, each with its formula, the export it comes from and what it tells you: hit ratio by client and product, size-weighted hit ratio, inquiry share, the quiet client list, client tiering by flow and profitability, axe hit rate, traded unsent, coverage recency by client value, revenue concentration, and response time on inquiries. Also the three measures most desks miss, the figures to drop, the identities, and who owns what.
Aug 10, 20264 min readThe complete axe distribution calculation on ten axes sent by one desk, small enough to check by hand: each axe's instrument, side and the clients it was sent to, the blotter's trades in those instruments within the window, the match rule, axes received and traded per client, the axe hit rate, the client on every list who traded none, the client who traded the desk's axed instrument without being sent the axe, the salesperson's list age, and the assertion that matched trades are a subset of the blotter, so a reader can reproduce every figure and then run it on their own axe log.
Aug 9, 20263 min read