The site also contains presentations given by Riccardo Rebonato at conferences, symposia, courses, etc.
Finally, work in progress (eg, chapters of forthcoming books, computer code, etc) are also posted on this site. Visitors to this page are welcome to make use of the code (at their own risk!). If they find bugs or more efficient ways to perform computations Riccardo Rebonato would be grateful if he were informed.
The site is organized in four sections:
1) The first chapter and the index of my latest book, Plight of the Fortune Tellers, Princeton University Press
2) Papers in risk management
3) Papers that deal with the statistical properties of rates and prices in the real-world (objective) measure
4) Papers in derivatives pricing
WARNING: I have no connection with the site Rebonato.com. I have been cyber-squatted. Papers, further links to other pages, ads, etc, that you may find there have nothing to do with me.
1) The proofs of the preface and the first chapter of my latest book, Plight of the Fortune Tellers, PUP.
The book is about my views on the management of financial risk,
why I believe we are trying to measure and control it a non-productive way, what are the dangers in doing so and what we can do instead.
It us aimed at a non-technical readership ("the boss of the boss of the quant who read my previous books").
Preface
Chapter 1
2) The following are papers in risk management:
In this paper I look at model risk, and show that it can have very different meanings in different contexts.
Rebonato R, (2003), Theory and Practice of Model Risk Management
The following paper shows how to appriximate a candidate correlation matrix that is exogenously specified a priori (perhaps on the basis of the
formulation of a Bayesian prior) but which may not be 'valid' (ie, positive definite) with the closest positive definite valid correlation matrix.
This can be useful for scenarios analysis, when the risk manager would like to assign an exogenous correlation matrix.
Rebonato R, Jaeckel, P, (1999), The most general methodology to create a valid correlation matrix
Kwiatkowski J, Rebonato R, Liesch L, (2007), A Flexible Analytical Metohd to Calcualte the Specific Risk Surcharge - Text
These are its figures:
Kwiatkowski J, Rebonato R, Liesch L, (2007), A Flexible Analytical Metohd to Calcualte the Specific Risk Surcharge - Figs
This paper shows how to use non-constant weights if one wants to calculate risk statistics such as VaR, Conditional Expected Shortfall, etc using
historical simulation. The method can be of particular use to deal with seasonality (as found, eg, in some commodities):
Rebonato R, Shanbhoguue V, (2007), Combining Non-Constant Weights with Historical Simulation VaR - Text
These are the Figures that go with it:
Rebonato R, Shanbhoguue V, (2007), Combining Non-Constant Weihgts with Historical Simulation VaR - Figs
3) These papers deal with properties of interest rates in the real-world (objective) measure:
Rebonato R, Gaspari V, (2006), Analysis of Drawdowns and Drawups in the US$ Interest-Rate Market
The following two papers deal with the evolution of the yield curve over long time horizons in the real-world measure:
Rebonato R, et al, (2005), Evolving Yield Curves in the Real-World Measure
Nyholm K and Rebonato R, (2007), Long-Horizon Yield Curve Forecasts
4) These are papers in derivatives pricing:
This is a general review of interest-rate pricing models:
Rebonato R (2003), Interest-Rate Term-Structure Pricing Models: A Review
This paper presents a time-homogeneous version of the LIBOR Market Model which is compatible with SABR prices and is very easy to calibrate.
Personally I find it very useful.
Rebonato R (2007), A Time-Homogeneous, SABR-Consistent Extension of the LMM - Text
These are its figures:
Rebonato R (2007), A Time-Homogeneous, SABR-Consistent Extension of the LMM - Figs
This is an extension to include calibration to swaptions (plus a small improvement on the previous paper):
Rebonato R, White R, (2007), Linking Caplet and Swaption Prices in the LMM-SABR Model
This paper deals with the same problem in a simpler (LMM no-smile) setting:
Jaeckel, P, Rebonato R, (2002), The Link Between Caplet and Swaption Volatilities in a BGM Setting
This paper shows how to fit a market smile surface (for equites, interest rates or FX) in a robust and efficient way:
Rebonato R, Cardoso T, (2004), Unconstrained Fitting of Implied Volatility Surfaces Using a Mixture of Normals - Text
These are its figures:
Rebonato R, Cardoso T, (2004), Unconstrained Fitting of Implied Volatility Surfaces Using a Mixture of Normals - Figs
This paper links forward-rate volatilities to the ATM swaption mtarix in a LMM setting and looks at the historical performamce of the fits:
Rebonato R, (2005), Forward Rate Volatilities and the Swaption Matrix: Why Neither Time-Homogeneity nor Time-Dependence Will Do
This paper is an extension of the one above using a Markov approach: better fit, but also better 'physics' (also, some semi-analytic results):
Rebonato R, White R, (2007), A Swaption Volatility Model Using Markov Regime Switching