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Synopsis
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 aligns with professional performance measurement standards, giving practitioners results that are analytically sound, auditable, and repeatable.
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Bond Return Attribution (Paperback)
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Paperback. Condition: new. Paperback. 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 aligns with professional performance measurement standards, giving practitioners results that are analytically sound, auditable, and repeatable. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798896655206
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Bond Return Attribution
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Bond Return Attribution: Yield Curve, Spread, and Selection Effects
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Bond Return Attribution
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Bond Return Attribution (Paperback)
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Paperback. Condition: new. Paperback. 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 aligns with professional performance measurement standards, giving practitioners results that are analytically sound, auditable, and repeatable. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798896655206
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Bond Return Attribution (Paperback)
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Paperback. Condition: new. Paperback. 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 aligns with professional performance measurement standards, giving practitioners results that are analytically sound, auditable, and repeatable. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798896655206
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Bond Return Attribution : Yield Curve, Spread, and Selection Effects
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 aligns with professional performance measurement standards, giving practitioners results that are analytically sound, auditable, and repeatable. Seller Inventory # 9798896655206
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Bond Return Attribution | Yield Curve, Spread, and Selection Effects
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Taschenbuch. Condition: Neu. Bond Return Attribution | Yield Curve, Spread, and Selection Effects | Marcus T. Whitfield | Taschenbuch | Englisch | 2026 | NobleTrex Press | EAN 9798896655206 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 138110608
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