NAG Library Function Document

nag_heston_price (s30nac)


    1  Purpose
    7  Accuracy


nag_heston_price (s30nac) computes the European option price given by Heston's stochastic volatility model.


#include <nag.h>
#include <nags.h>
void  nag_heston_price (Nag_OrderType order, Nag_CallPut option, Integer m, Integer n, const double x[], double s, const double t[], double sigmav, double kappa, double corr, double var0, double eta, double grisk, double r, double q, double p[], NagError *fail)


nag_heston_price (s30nac) computes the price of a European option using Heston's stochastic volatility model. The return on the asset price, S, is
dS S = r-q dt + vt d W t 1  
and the instantaneous variance, vt, is defined by a mean-reverting square root stochastic process,
dvt = κ η-vt dt + σv vt d W t 2 ,  
where r is the risk free annual interest rate; q is the annual dividend rate; vt is the variance of the asset price; σv is the volatility of the volatility, vt; κ is the mean reversion rate; η is the long term variance. dWti, for i=1,2, denotes two correlated standard Brownian motions with
ℂov d W t 1 , d W t 2 = ρ d t .  
The option price is computed by evaluating the integral transform given by Lewis (2000) using the form of the characteristic function discussed by Albrecher et al. (2007), see also Kilin (2006).
Pcall = S e-qT - X e-rT 1π Re 0+i/2 +i/2 e-ikX- H^ k,v,T k2 - ik d k , (1)
where X- = lnS/X + r-q T  and
H^ k,v,T = exp 2κη σv2 tg - ln 1-he-ξt 1-h + vt g 1-e-ξt 1-he-ξt ,  
g = 12 b-ξ ,   h = b-ξ b+ξ ,   t = σv2 T/2 ,  
ξ = b2 + 4 k2-ik σv2 12 ,  
b = 2 σv2 1-γ+ik ρσv + κ2 - γ1-γ σv2  
with t = σv2 T/2 . Here γ is the risk aversion parameter of the representative agent with 0γ1 and γ1-γ σv2 κ2 . The value γ=1  corresponds to λ=0, where λ is the market price of risk in Heston (1993) (see Lewis (2000) and Rouah and Vainberg (2007)).
The price of a put option is obtained by put-call parity.
The option price Pij=PX=Xi,T=Tj is computed for each strike price in a set Xi, i=1,2,,m, and for each expiry time in a set Tj, j=1,2,,n.


Albrecher H, Mayer P, Schoutens W and Tistaert J (2007) The little Heston trap Wilmott Magazine January 2007 83–92
Heston S (1993) A closed-form solution for options with stochastic volatility with applications to bond and currency options Review of Financial Studies 6 327–343
Kilin F (2006) Accelerating the calibration of stochastic volatility models MPRA Paper No. 2975
Lewis A L (2000) Option valuation under stochastic volatility Finance Press, USA
Rouah F D and Vainberg G (2007) Option Pricing Models and Volatility using Excel-VBA John Wiley and Sons, Inc


1:     order Nag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by order=Nag_RowMajor. See Section in How to Use the NAG Library and its Documentation for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     option Nag_CallPutInput
On entry: determines whether the option is a call or a put.
A call; the holder has a right to buy.
A put; the holder has a right to sell.
Constraint: option=Nag_Call or Nag_Put.
3:     m IntegerInput
On entry: the number of strike prices to be used.
Constraint: m1.
4:     n IntegerInput
On entry: the number of times to expiry to be used.
Constraint: n1.
5:     x[m] const doubleInput
On entry: x[i-1] must contain Xi, the ith strike price, for i=1,2,,m.
Constraint: x[i-1]z ​ and ​ x[i-1] 1 / z , where z = nag_real_safe_small_number , the safe range parameter, for i=1,2,,m.
6:     s doubleInput
On entry: S, the price of the underlying asset.
Constraint: sz ​ and ​s1.0/z, where z=nag_real_safe_small_number, the safe range parameter.
7:     t[n] const doubleInput
On entry: t[i-1] must contain Ti, the ith time, in years, to expiry, for i=1,2,,n.
Constraint: t[i-1]z, where z = nag_real_safe_small_number , the safe range parameter, for i=1,2,,n.
8:     sigmav doubleInput
On entry: the volatility, σv, of the volatility process, vt. Note that a rate of 20% should be entered as 0.2.
Constraint: sigmav>0.0.
9:     kappa doubleInput
On entry: κ, the long term mean reversion rate of the volatility.
Constraint: kappa>0.0.
10:   corr doubleInput
On entry: the correlation between the two standard Brownian motions for the asset price and the volatility.
Constraint: -1.0corr1.0.
11:   var0 doubleInput
On entry: the initial value of the variance, vt, of the asset price.
Constraint: var00.0.
12:   eta doubleInput
On entry: η, the long term mean of the variance of the asset price.
Constraint: eta>0.0.
13:   grisk doubleInput
On entry: the risk aversion parameter, γ, of the representative agent.
Constraint: 0.0grisk1.0 and grisk×1.0-grisk×sigmav×sigmavkappa×kappa.
14:   r doubleInput
On entry: r, the annual risk-free interest rate, continuously compounded. Note that a rate of 5% should be entered as 0.05.
Constraint: r0.0.
15:   q doubleInput
On entry: q, the annual continuous yield rate. Note that a rate of 8% should be entered as 0.08.
Constraint: q0.0.
16:   p[m×n] doubleOutput
Note: where Pi,j appears in this document, it refers to the array element
  • p[j-1×m+i-1] when order=Nag_ColMajor;
  • p[i-1×n+j-1] when order=Nag_RowMajor.
On exit: Pi,j contains Pij, the option price evaluated for the strike price xi at expiry tj for i=1,2,,m and j=1,2,,n.
17:   fail NagError *Input/Output
The NAG error argument (see Section 3.7 in How to Use the NAG Library and its Documentation).

Error Indicators and Warnings

Solution cannot be computed accurately. Check values of input arguments.
Dynamic memory allocation failed.
See Section in How to Use the NAG Library and its Documentation for further information.
On entry, argument value had an illegal value.
Quadrature has not converged to the specified accuracy. However, the result should be a reasonable approximation.
On entry, m=value.
Constraint: m1.
On entry, n=value.
Constraint: n1.
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.
On entry, corr=value.
Constraint: corr1.0.
On entry, eta=value.
Constraint: eta>0.0.
On entry, grisk=value, sigmav=value and kappa=value.
Constraint: 0.0grisk1.0 and grisk×1.0-grisk×sigmav2kappa2.
On entry, kappa=value.
Constraint: kappa>0.0.
On entry, q=value.
Constraint: q0.0.
On entry, r=value.
Constraint: r0.0.
On entry, s=value.
Constraint: svalue and svalue.
On entry, sigmav=value.
Constraint: sigmav>0.0.
On entry, var0=value.
Constraint: var00.0.
On entry, t[value]=value.
Constraint: t[i-1]value.
On entry, x[value]=value.
Constraint: x[i-1]value and x[i-1]value.


The accuracy of the output is determined by the accuracy of the numerical quadrature used to evaluate the integral in (1). An adaptive method is used which evaluates the integral to within a tolerance of max 10 -8 , 10 -10 × I , where I is the absolute value of the integral.

Parallelism and Performance

nag_heston_price (s30nac) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the x06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

Further Comments



This example computes the price of a European call using Heston's stochastic volatility model. The time to expiry is 6 months, the stock price is 100 and the strike price is 100. The risk-free interest rate is 5% per year, the volatility of the variance, σv, is 22.5% per year, the mean reversion parameter, κ, is 2.0, the long term mean of the variance, η, is 0.01 and the correlation between the volatility process and the stock price process, ρ, is 0.0. The risk aversion parameter, γ, is 1.0 and the initial value of the variance, var0, is 0.01.

Program Text

Program Text (s30nace.c)

Program Data

Program Data (s30nace.d)

Program Results

Program Results (s30nace.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017