Download this Paper Open PDF in Browser

What Interest Rate Models to Use? Buy Side Versus Sell Side

23 Pages Posted: 12 Dec 2010 Last revised: 18 Jun 2011

Sanjay K. Nawalkha

University of Massachusetts Amherst - Isenberg School of Management

Riccardo Rebonato

Royal Bank of Scotland

Multiple version iconThere are 2 versions of this paper

Date Written: January 1, 2011

Abstract

Does the selection of a specific interest rate model to use for pricing, hedging, and risk-return analysis depend upon whether the user is a buy-side institution or a sell-side dealer bank? Sanjay Nawalkha and Riccardo Rebonato debate this question in this paper and provide some insightful conclusions. Responding to Nawalkha’s [2010] critique of the LMM-SABR model, Rebonato argues that the LMM-SABR model is currently the best available model for the sell-side dealer banks for pricing and hedging large portfolios of complex interest rate derivatives within tight time constraints. Nawalkha in his rejoinder argues that the LMM-SABR model is useless at best and dangerous at worst for the buy-side institutions, and these institutions must use time-homogeneous fundamental and single-plus interest rate models (e.g., such as affine and quadratic term structure models) for risk-return analysis under the physical measure, as this cannot be done using the time-inhomogeneous double-plus and triple-plus versions of the LMM-SABR model.

Keywords: Interest rate models, affine, quadratic, LMM, SABR, caps, swaptions

JEL Classification: G10, G11, G12, G13

Suggested Citation

Nawalkha, Sanjay K. and Rebonato, Riccardo, What Interest Rate Models to Use? Buy Side Versus Sell Side (January 1, 2011). Available at SSRN: https://ssrn.com/abstract=1723924 or http://dx.doi.org/10.2139/ssrn.1723924

Sanjay K. Nawalkha (Contact Author)

University of Massachusetts Amherst - Isenberg School of Management ( email )

Amherst, MA 01003-4910
United States
413-687-2561 (Phone)

Riccardo Rebonato

Royal Bank of Scotland ( email )

No Address Available

Paper statistics

Downloads
896
Rank
20,690
Abstract Views
2,791