Modern Multi-Factor Analysis of Bond Portfolios: Critical Implications for Hedging and Investing
Editat de Giovanni Barone-Adesi, Nicola Carcanoen Limba Engleză Hardback – 3 dec 2015
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.
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Specificații
ISBN-13: 9781137564856
ISBN-10: 1137564857
Pagini: 112
Ilustrații: XII, 124 p.
Dimensiuni: 140 x 216 x 20 mm
Greutate: 0.33 kg
Ediția:1st ed. 2015
Editura: Palgrave Macmillan UK
Colecția Palgrave Macmillan
Locul publicării:London, United Kingdom
ISBN-10: 1137564857
Pagini: 112
Ilustrații: XII, 124 p.
Dimensiuni: 140 x 216 x 20 mm
Greutate: 0.33 kg
Ediția:1st ed. 2015
Editura: Palgrave Macmillan UK
Colecția Palgrave Macmillan
Locul publicării:London, United Kingdom
Cuprins
1.Introduction
2.Adjusting principal component analysis for model errors: Nicola Carcano
2.1.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
2.Adjusting principal component analysis for model errors: Nicola Carcano
2.1.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
Notă biografică
Giovanni Barone-Adesi is Professor in finance theory at the Swiss Finance Institute, University of Lugano, Switzerland. A graduate from the University of Chicago, US, he has taught at the University of Alberta, Canada, City University, UK, and the Universities of Texas and Pennsylvania, US. His main research interests are derivative securities and risk management. Especially well-known are his contributions to the pricing of American commodity options and the measurement of market risk.
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.
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.
Textul de pe ultima copertă
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.
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.