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Glossary

Hit ratio

On a trading desk, requests for quote won divided by requests received, per client and product over a window. The desk's version of share of wallet, counted in requests.

DefinitionOn a trading desk, requests for quote won divided by requests received, per client and product over a window. The desk's version of share of wallet, counted in requests.

How it is computed

Hit ratio = RFQs won ÷ RFQs received

Declined requests count as received and not won. Otherwise the ratio measures only the requests the desk chose to compete on.

Read it with flow share

A high hit ratio on a small share of the client's flow means the client sends you the trades they intend to do with you. A low hit ratio on a large request count means you are the price check. Neither number alone says which.

The drifts

Hit ratio falling while requests hold: the client is testing another dealer. Requests falling while hit ratio holds: a product has moved. Hit ratio rising while volume falls: you are winning the small tickets.

How it is computed

Requests for quote traded divided by requests received, per client, product and channel, by count and by notional.

Example

A client sent forty inquiries and traded eighteen: 45 percent by count. By notional it traded $32 million of $400 million: 8 percent. It trades size elsewhere.

Where it goes wrong

Voice and electronic blended, and count used without size. The price-checker ranks as the best client.

Articles that use this term

Territory, capacity and quota planning · Trading

Client tiering by flow and hit ratio: where the desk should spend its axe

How a trading desk tiers its clients from the RFQ log and the blotter rather than from the coverage list: two axes, notional traded and hit ratio, four tiers that follow, the clients with high inquiry volume and low hit ratio who consume pricing effort for little, the clients with high hit ratio and modest flow who would trade more if shown more, and the quarterly re-tiering that moves clients on their own numbers.

16 Sept 20262 min readBoard and management reporting

Count-weighted and value-weighted: why every ratio on this site says which

The difference between a ratio weighted by count, accounts, deals, inquiries, and one weighted by value, revenue, notional, premium, why the two disagree whenever the large items behave differently from the small ones, the six measures where the difference is largest, hit ratio, coverage, win rate, share of wallet, renewal rate and retention, the rule that a report shows both and ranks by value, and the case where count is the honest one.

16 Sept 20263 min readWallet share and penetration · Trading

Hit ratio by client and product: a trading desk's guide to flow share

How a sell-side desk computes hit ratio and flow share per client and product from its own RFQ logs and blotter, why the two numbers must be read together, and the three drifts that predict a client is leaving before the revenue shows it.

16 Sept 20264 min readForecast and pipeline

Pipeline coverage by industry: what the pipeline is when there are no deals

Pipeline coverage is open pipeline over remaining target, and on many desks there is no CRM pipeline at all: the pipeline is renewals due, tenders in flight, RFQs open, applications pending, or the season's filings. This hub gives, for twelve industries, what stands in for the pipeline, where it lives, how it is weighted, and the multiple the desk actually needs, with the guide for each.

16 Sept 20263 min readWallet share and penetration · Trading

Size-weighted hit ratio: why the count-weighted number hides the losses

Why a trading desk's hit ratio should be weighted by ticket size as well as counted, how the two diverge when a competitor commits balance sheet, the computation from the RFQ log, and a worked example where a rising count-weighted ratio masks a falling share of volume.

16 Sept 20263 min readCoverage and territory · Trading

Ten questions a head of sales trading asks, and the table that answers each

The ten questions a head of sales trading puts to the salespeople and the traders, which clients have gone quiet in a product where the desk has not, what is the size-weighted hit ratio by client, which clients are tiered where by flow and hit ratio, which axes reached the clients who trade them, who is covered by one salesperson only, what does the coverage map look like by client and product, does the blotter reconcile to the benchmark submission, which clients receive many prices and trade none, which salespeople's distribution lists are stale, and what changed, each with the table from the RFQ log, the blotter and the coverage file, and the answer to send back.

16 Sept 20262 min read