How might predictive analytics help to support the bond trading process?
This case describes the process and the salient factors traders must consider in pricing and selling products in the secondary market for previously issued bonds. Since there is typically no readily available, agreed-upon price for a bond, a bank will quote its own price of a specific bond to buyers or sellers, with the set price dependent on many factors, including the face value of the bond, the remaining time to maturity, the prevailing interest rate environment, the health of the company in question, and the supply/demand imbalance for the bond. Buyers typically send out inquiries (requests for quotes, or RFQs) to many banks in search of the best price—and sellers typically spend a great deal of time with RFQ-management to track these RFQs in order to determine which ones are worth pricing. This case outlines the myriad of challenges facing both sell-side and buy-side traders and asks students to suggest how predictive analytics might streamline the bond trading process—and what data would be required to implement their suggestions.
Case ID: 210212
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