Abstract

The SABR stochastic volatility model with β-volatility β ? (0,1) and an absorbing barrier in zero imposed to the forward prices/rates stochastic process is studied. The presence of (possibly) nonzero correlation between the stochastic differentials that appear on the right hand side of the model equations is considered. A series expansion of the transition probability density function of the model in powers of the correlation coefficient of these stochastic differentials is presented. Explicit formulae for the first three terms of this expansion are derived. These formulae are integrals of known integrands. The zero-th order term of the expansion is a new integral formula containing only elementary functions of the transition probability density function of the SABR model when the correlation coefficient is zero. The expansion is deduced from the final value problem for the backward Kolmogorov equation satisfied by the transition probability density function. Each term of the expansion is defined as the solution of a final value problem for a partial differential equation. The integral formulae that give the solutions of these final value problems are based on the Hankel and on the Kontorovich-Lebedev transforms. From the series expansion of the probability density function we deduce the corresponding expansions of the European call and put option prices. Moreover we deduce closed form formulae for the moments of the forward prices/rates variable. The moment formulae obtained do not involve integrals or series expansions and are expressed using only elementary functions. The option pricing formulae are used to study synthetic and real data. In particular we study a time series (of real data) of futures prices of the EUR/USD currency's exchange rate and of the corresponding option prices. The website: http://www.econ.univpm.it/recchioni/finance/w18 contains material including animations, an interactive application and an app that helps the understanding of the paper. A more general reference to the work of the authors and of their coauthors in mathematical finance is the website: http://www.econ.univpm.it/recchioni/finance.

Highlights

  • Let us consider the SABR stochastic volatility model. This model has been introduced in mathematical finance in 2002 by Hagan, Kumar, Lesniewski, Woodward [1] to describe the time dynamics of forward prices/rates and is widely used in the financial markets

  • The SABR model describes the dynamics of two variables: the forward prices/rates variable xt, t > 0, and the stochastic volatility variable vt, t > 0

  • The normal and lognormal SABR models have been widely studied in the scientific literature

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Summary

Introduction

Let us consider the SABR stochastic volatility model. This model has been introduced in mathematical finance in 2002 by Hagan, Kumar, Lesniewski, Woodward [1] to describe the time dynamics of forward prices/rates and is widely used in the financial markets. In particular the “diagonalization” procedure shows that the zero-th order term of the expansion is a kind of convolution between two kernels, one depending from the transformed forward prices/rates variable and the other depending from the stochastic volatility variable This last kernel has already been used in [4] to express the transition probability density function of the SABR model when β = 0 or β = 1 and ρ ∈ (−1,1) , and in [9] [15] to study respectively a modified SABR model when β ∈[0,1] , ρ = 0 and when β = 1 and ρ ∈ (−1,1).

The Initial Value Problems Satisfied by the Expansion Terms
The Zero-th Order Term of the Expansion
The First and Second Order Terms of the Expansion
The Series Expansion of the Option Prices
Findings
Some Numerical Experiments
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