Where institutions and individuals averagely invest the majority of their assets in money-market and fixed-income instruments, interest rate risk management could be seen as the single most important global financial issue. However, the majority of the key techniques used by most investors were developed several decades ago, and the advantages of multi-factor models are not fully recognised by many researchers and practitioners.
This book provides clear and practical insight into bond portfolios and portfolio management through key empirical analysis. The authors use extensive sets of empirical data to describe the value potentially added by more recent techniques to manage interest rate risk relative to traditional techniques and to present empirical evidence of such an added value. Beginning with a description of the simplest models and moving on to the most complex, the authors offer key recommendations for the future of rate risk management.
|Publisher:||Palgrave Macmillan UK|
|Edition description:||1st ed. 2015|
|Product dimensions:||5.51(w) x 8.50(h) x (d)|
About the Author
Nicola Carcano holds a degree in Economics from The Libera Università Internazionale degli Studi Sociali "Guido Carli" (LUISS), Rome, Italy, an MBA degree from the New York University, and a PhD in Financial Markets Theory from the University of St Gallen, Switzerland. He teaches Structured Products at the University of Lugano, Switzerland. After working as a consultant and institutional portfolio manager, he is now the Chief Executive Officer of Heron Asset Management. His research focuses on fixed income finance.
Table of Contents
1. Introduction 2. Adjusting principal component analysis for model errors: Nicola Carcano2.1. The hedging models 2.2. The results 2.3. Conclusions 2.4. Appendix 3. Alternative models for hedging yield curve risk: an empirical comparison: Nicola Carcano and Hakim Dall'O 3.1. The hedging methodology 3.2. The dataset and the testing approach 3.3. The results 3.4. Conclusions 4. Applying error-adjusted hedging to corporate bond portfolios: Giovanni Barone-Adesi, Nicola Carcano and Hakim Dall'O 4.1. Dataset and calculation of unexpected returns 4.2. Methodology 4.3. Results 4.4. Conclusions 4.5. Appendix 1 4.6. Appendix 2 5. Credit risk premium: measurement, interpretation & portfolio allocation: Radu Gabudean, Wok Yuen Ng and Bruce D. Phelps 5.1. Measures of the credit risk premium 5.2. The long-term credit risk premium: Jan 1973-Nov 2012 5.3. Optimal combination of IG corporates and treasuries 5.4. Conclusion 6. Conclusion: Giovanni Barone-Adesi and Nicola Carcano