Comparing Heston and Black–Scholes European Call Prices
Summary
The document explains why Heston and Black–Scholes need not produce the same European call price. Black–Scholes assumes constant volatility, while Heston models variance as a mean-reverting stochastic process correlated with the underlying. Prices depend on model parameters; when Heston volatility of variance is zero, variance follows a deterministic path, and matching its initial and long-run levels to Black–Scholes volatility squared recovers the constant-volatility case. The answer also warns that the usual Heston characteristic-function formulas contain terms that cannot be evaluated by directly setting volatility of variance to zero; the limiting differential equations must be solved instead.
A second response notes that Heston's return distribution can have heavier tails than the lognormal Black–Scholes distribution, which can affect out-of-the-money option prices. It suggests Heston may price such options higher under compatible calibration, but stresses that the comparison depends on parameter settings. The material provides model reasoning rather than numerical results or a general price ordering; model calibration and risk-neutral distributions remain essential to a fair comparison.
Key ideas
- Heston and Black–Scholes option prices generally differ when their volatility assumptions and parameters differ.
- With zero volatility of variance, Heston variance evolves deterministically and can match the constant-volatility case under suitable settings.
- Closed-form Heston expressions may be singular in the zero-volatility-of-variance limit, so the limiting equations need separate treatment.
- Heston's heavier-tailed return distribution can affect out-of-the-money option prices.
- There is no universal rule that Heston calls must be more or less expensive than Black–Scholes calls.
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Full text
# How should option prices differ when using the Heston versus the Black-Scholes model?
# How should option prices differ when using the Heston versus the Black-Scholes model?
I am running Monte Carlo simulations for a European Call using Heston Model and I am trying to compare them with prices calculated using Black-Scholes formula. I am not quite sure if the prices I get from the Heston model are correct.
- Is there any regularity here?
- What should be the relation between the prices? (should a price of a European call from Heston be greater or smaller than from Black-Scholes?)
Can anyone explain what the relation should be?
## Answer by user16651 (score 3, accepted)
https://quant.stackexchange.com/a/31224
If $\sigma_{H}\ne 0$ and $v_0\ne \theta\ne \sigma^2_{BC}$ then prices are different in BC and Heston model.
Especial case
In the Black-Scholes model the dynamics of $S_t$ under risk neutral measure follow the stochastic process $$dS_t=(r-q)S_tdt+\sigma_{\color{red}{BC}}S_tdW^{\mathbb{Q}}(t)\tag 1$$ on the other hand $$dS_t=(r-q)S_t+\sqrt{v_t}S_tdW^{\mathbb{Q}}_1(t)\\ \quad dv_t=\kappa(\theta-v_t)dt+\sigma_{\color{red}{H}}\sqrt{v_t}dW^{\mathbb{Q}}_2(t)\tag 2$$ where $d[W^{\mathbb{Q}}_1(t)\,,\,W^{\mathbb{Q}}_2(t)]=\rho dt$. In CRR model we have $$\text{Var}[v_t\big{|}v_0]=\frac{v_0\sigma_{\color{red}{H}}^2e^{-\kappa t}}{\kappa}\left(1-e^{-\kappa t}\right)+\frac{\theta\sigma_{\color{red}{H}}^2}{2\kappa}\left(1-e^{-\kappa t}\right)^2\tag 3$$
Now if we set $\sigma_\color{red}{H}=0$ ,then $$\text{Var}[v_t|v_0] = 0\tag 4$$ This will produce volatility that is time-varying, but $\color{red}{\text{deterministic}}$. Indeed $$dv_t=\kappa(\theta-v_t)dt\tag 5$$ or $$v'_t+\kappa v_t=\kappa\theta\tag 6$$ Equation $(6)$ is a linear ordinary differential equation. We can show easily $$v_t=\theta+c\,e^{-\kappa t}\quad ,\quad c\in\mathbb{R}\tag 7$$ Set $v_0=\theta=\sigma_{\color{red}{BC}}^2$. Therefore $c=0$ and $v=\sigma_{\color{red}{BC}}^2\,.$
$\color{red}{\text{Warning}\,!}$
In the Heston Model we have \begin{align} C(t\,,{{S}_{t}},{{v}_{t}},K,T)={{S}_{t}}{{P}_{1}}-K\,{{e}^{-r\tau }}{{P}_{2}}\tag 8 \end{align} where,for $j=1,2$
\begin{align} & \mathbb{P}_j({{x}_{t}}\,,\,{{v}_{t}}\,;\,\,{{x}_{T}},\ln K)=\frac{1}{2}+\frac{1}{\pi }\int\limits_{0}^{\infty }{\operatorname{Re}\left( \frac{{{e}^{-i\phi \ln K}}{{f}_{j}}(\phi ;t,x,v)}{i\phi } \right)}\,d\phi \tag 9 \\ & {{f}_{j}}(\phi \,;{{v}_{t}},{{x}_{t}})=\exp [{{C}_{j}}(\tau ,\phi )+{{D}_{j}}(\tau ,\phi ){{v}_{t}}+i\phi {{x}_{t}}]\tag {10} \\ \end{align}
and
\begin{align} & {{C}_{j}}(\tau ,\phi )=(r-q)i\phi \,\tau +\frac{a}{{{\sigma_{\color{red}{H}} }^{2}}}{{\left( ({{b}_{j}}-\rho \sigma_{\color{red}{H}} i\phi +{{d}_{j}})\,\tau -2\ln \left(\frac{1-{{g}_{j}}{{e}^{{{d}_{j}}\tau }}}{1-{{g}_{j}}}\right) \right)}} \tag{11}\\ & {{D}_{j}}(\tau ,\phi )=\frac{{{b}_{j}}-\rho \sigma_{\color{red}{H}} i\phi +{{d}_{j}}}{{{\sigma_{\color{red}{H}} }^{2}}}\left( \frac{1-{{e}^{{{d}_{j}}\tau }}}{1-{{g}_{j}}{{e}^{{{d}_{j}}\tau }}} \right) \tag{12}\\ \end{align} such that \begin{align} & {{g}_{j}}=\frac{{{b}_{j}}-\rho \sigma_{\color{red}{H}} i\phi +{{d}_{j}}}{{{b}_{j}}-\rho \sigma_{\color{red}{H}} i\phi +{{d}_{j}}} \\ & {{d}_{j}}=\sqrt{{{({{b}_{j}}-\rho \sigma_{\color{red}{H}} i\phi )}^{2}}-{{\sigma_{\color{red}{H}} }^{2}}(2i{{u}_{j}}\phi -{{\phi }^{2}})} \\ & {{u}_{1}}=\frac{1}{2}\,,\,{{u}_{2}}=-\frac{1}{2}\,,\,a=\kappa \theta \,,\,{{b}_{1}}=\kappa +\lambda -\rho \sigma_{\color{red}{H}} \,,\,{{b}_{2}}=\kappa +\lambda \,,\ {{i}^{2}}=-1 \\ \end{align}
> We can not simply substitute $\sigma_{\color{red}{H}} = 0$ into the pricing functions, because that will lead to division by zero in the expressions for $C_j(\tau,\phi)$ and $D_j(\tau,\phi)$.
With $\sigma_{\color{red}{H}}=0$, the Riccati equation reduces to the ordinary first-order differential equation in the Heston's article (1993) $$\frac{\partial {{D}_{j}}}{\partial \tau }={{p}_{j}}-{{b}_{j}}{{D}_{j}}\tag {13}$$
where $p_j=u_j i\phi-\frac 12 \phi^2$.The solution of this ODE is $$D_j(\tau ,\phi )=\frac{(i{{u}_{j}}\phi -\frac{1}{2}{{\phi }^{2}})(1-{{e}^{-{{b}_{j}}\tau }})}{{{b}_{j}}}\tag {14}$$ on other hand , Heston showed $$\frac{\partial {{C}_{j}}}{\partial \tau }=ri\phi +a{{D}_{j}}\tag{15}$$ substitute $(14)$ in $(15)$ and integrate to obtain $${{C}_{j}}(\tau ,\phi )\ =ri\phi \tau +\frac{a(i{{u}_{j}}\phi -\frac{1}{2}{{\phi }^{2}})}{{{b}_{j}}}\left( \tau -\frac{1-{{e}^{-{{b}_{j}}\tau }}}{{{b}_{j}}} \right)\tag{16}$$ In the case $j=2$ and $\lambda=0$, we have $$\begin{align} & {{D}_{2}}(\tau ,\phi )=-\frac{(i\phi +{{\phi }^{2}})(1-{{e}^{-\kappa \tau }})}{2\kappa } \\ & {{C}_{2}}(\tau ,\phi )\ =ri\phi \tau -\frac{\theta (i\phi +{{\phi }^{2}})}{2}\left( \tau -\frac{1-{{e}^{-\kappa \tau }}}{\kappa } \right) \\ \end{align} \tag {17}$$ We know $${{f}_{2}}(\phi ;{{\ln S}_{t}},{{v}_{t}})=\exp\left[i\phi\,{\ln S_t}+{{C}_{2}}(\tau \,,\,\phi )+{{D}_{2}}(\tau \,,\,\phi ){{v}_{t}}\right]$$
let $v_0=\theta=\sigma_{\color{red}{BC}}^2$, thus $$\color{red}{{{f}_{2}}=\exp\left( i\phi \left[\ln {{S}_{t}}+(r-\frac{1}{2}{{\sigma }_{BC}}^{2})\tau \right]-\frac{1}{2}{{\phi }^{2}}{{\sigma }_{BC}}^{2}\tau \right)=\mathbb{E}\left[\exp\left(i\,\phi\,\ln S_t\right)\right]\tag {18}}$$
## Answer by berkorbay (score 2)
https://quant.stackexchange.com/a/31709
The answer depends on the parameter settings, but you should always check the risk neutral densities. One of the several complaints against BS is the underlying GBM has lower tails so it underprices OTM (out-of-the-money) options as the market is more heavy tailed.
Heston log-return density is leptokurtic (higher tails and kurtosis). See http://fedc.wiwi.hu-berlin.de/xplore/tutorials/stfhtmlnode46.html
It depends on the setting of your parameters but usually Heston should give higher prices for OTM options for compatible parameter optimizations (i.e. both models' parameters are estimated using the same data).Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.