You are given an Excel file containing a few months of trading RFQ (request-for-quote) data for a sales & trading desk. The data includes RFQs from 3 clients on 3 different assets.
Each row in the dataset corresponds to a single RFQ and has (at least) the following columns:
timestamp
– time of the RFQ
client_id
– which of the 3 clients sent the RFQ
asset_id
– which of the 3 assets the RFQ is for
rfq_side
– buy or sell
rfq_size
– requested notional/quantity
our_quote
– the price (or spread) your firm quoted
market_reference_price
– the mid‑market or reference price at RFQ time
is_competitive
– Boolean flag: whether our quote was considered competitive (e.g., inside some benchmark or relative to competitors)
won_trade
– Boolean flag: whether your firm ultimately won the RFQ (the client traded with you) or not
You are told only to “analyze the data”; there is no further guidance. You can use only Excel (including functions, pivot tables, charts, etc.).
Task:
Describe, in detail, how you would approach this analysis to help the trading desk understand and potentially improve its quoting and bidding strategy. In particular:
Login required