Fixed-income portfolios rarely move for just one reason. A bond’s return can reflect shifts in the government curve, credit spread repricing, currency translation, carry, rolldown, hedging, and issuer-specific selection effects—all interacting across instruments, sectors, and markets. This book is written for portfolio managers, performance analysts, risk professionals, and advanced allocators who need a clear, defensible way to explain bond results with the rigor expected in institutional investment settings.
The book develops a practical attribution framework from the ground up, beginning with bond cashflows, pricing conventions, discounting, and return definitions, then moving into valuation, duration, convexity, and key rate durations. It shows how to decompose returns into parallel, twist, and curvature effects, isolate systematic credit spread movements from security selection, and incorporate FX translation and hedging into base-currency performance. Readers will also learn how to aggregate security-level effects to portfolios and benchmarks, govern residuals, and interpret outputs in a way that supports investment decisions.
A distinguishing feature of the guide is its implementation focus. Alongside the methodology, it outlines how to engineer an attribution system in Python, including data models, pricing functions, scenario engines, and reconciliation controls. The approach is aligned with professional performance measurement standards, making the book especially useful for practitioners who need results that are not only analytically sound, but also auditable
