Vanna–Volga pricing
The Vanna–Volga method is a mathematical tool used in finance. It is a technique for pricing first-generation exotic options in foreign exchange market (FX) derivatives.
It consists of adjusting the Black–Scholes theoretical value (BSTV)
by the cost of a portfolio which hedges three main risks
associated to the volatility of the option: the Vega 
, the Vanna
and the Volga. 
The Vanna is the sensitivity of the Vega with respect to a change in the spot FX rate:
.
Similarly, the Volga is the sensitivity
of the Vega with respect to a change of the implied volatility
:
.
If we consider a smile volatility term structure 
 with ATM strike 
, ATM volatility 
, and where 
 are the 25-Delta
call/put strikes (obtained by solving the equations 
  and 
 where 
 denotes the
Black–Scholes Delta sensitivity) then the hedging portfolio
will be composed of the at-the-money (ATM), risk-reversal (RR) and butterfly (BF)
strategies:

with 
 the Black–Scholes price  of a call option (similarly for the put).
The simplest formulation of the Vanna–Volga method suggests that the
Vanna–Volga price 
 of an exotic instrument 
 is
given by

where by 
 denotes the Black–Scholes price of the
exotic and the Greeks are calculated with ATM volatility and
![\begin{align}
RR_{cost} &=\left[ \textrm{Call}(K_c,\sigma(K_c))-\textrm{Put}(K_p,\sigma(K_p)) \right] - \left[ \textrm{Call}(K_c,\sigma_0)-\textrm{Put}(K_p,\sigma_0) \right] 
\\
BF_{cost} &= \frac12 \left[ 
\textrm{Call}(K_c,\sigma(K_c))+\textrm{Put}(K_p,\sigma(K_p)) \right] - \frac12 \left[ \textrm{Call}(K_c,\sigma_0)+\textrm{Put}(K_p,\sigma_0) \right]
\end{align}](../I/m/1d3b5c9834c02daff4f887a3dcbdbdf0.png)
These quantities represent a smile cost, namely the difference between the price computed with/without including the smile effect.
The rationale behind the above formulation of the Vanna-Volga price is that one can extract
the smile cost of an exotic option by measuring the
smile cost of a portfolio designed to hedge its Vanna and
Volga risks. The reason why one chooses the strategies BF and RR
to do this is because they are liquid FX instruments and they
carry mainly Volga, and respectively Vanna risks. The weighting
factors 
 and 
 represent
respectively  the amount of RR needed to replicate the option's
Vanna, and the amount of BF needed to replicate the option's
Volga. The above approach ignores the small (but non-zero)
fraction of Volga carried by the RR and the small fraction of
Vanna carried by the BF. It further neglects the cost of hedging
the Vega risk. This has led to a more general formulation of the
Vanna-Volga method in which one considers that within the Black–Scholes
assumptions the exotic option's Vega, Vanna and Volga can be
replicated by the weighted sum of three instruments:

where the weightings are obtained by solving the system:

with
,
,

Given this replication, the Vanna–Volga method adjusts the BS price of an exotic option by the smile cost of the above weighted sum (note that the ATM smile cost is zero by construction):

where

and

The quantities 
 can be interpreted as the
market prices attached to a unit amount of Vega, Vanna and Volga,
respectively. The resulting correction, however, typically turns
out to be too large. Market practitioners thus modify
 to

The Vega contribution turns out to be several orders of magnitude smaller than the Vanna and Volga terms in all practical situations, hence one neglects it.
The terms 
 and 
 are put in by-hand and represent factors that ensure the correct behaviour of the price of an exotic option near a barrier:
as the knock-out barrier level 
 of an option
is gradually moved toward the spot level 
, the BSTV price of a
knock-out option must be a monotonically decreasing function, converging
to zero exactly at 
. Since the Vanna-Volga method is a
simple rule-of-thumb and not a rigorous model, there is no
guarantee that this will be a priori the case. The attenuation factors are of a different from for the Vanna or the Volga
of an instrument. This is because for barrier values close to the spot they behave differently: the Vanna becomes large while,
on the contrary, the Volga becomes small. Hence the
attenuation factors take the form:

where 
 represents some measure of the barrier(s)
vicinity to the spot with the features

The coefficients 
 are found through calibration of the model to ensure that it reproduces the vanilla smile. Good candidates for 
 that ensure the appropriate behaviour close to the barriers are the survival probability and the expected first exit time. Both of these quantities offer the desirable property that they vanish close to a barrier.
Survival probability
The survival probability  
 refers to the
probability that the spot does not touch one or more barrier
levels 
. For example, for a single barrier option we have
![p_{surv} = \mathbb{E}[ 1_{S_t<B, t_{\textrm{tod}}<t<t_{\textrm{mat}}}] = \mathrm{NT}(B) / \mathrm{DF}(t_{\textrm{tod}},t_{\textrm{mat}})](../I/m/c2f2798ed8d16a3838801144dd568e13.png)
where 
 is the value of a no-touch option and 
 the discount factor between today and maturity. Similarly, for options with two barriers
the survival probability is given through the undiscounted value
of a double-no-touch option.
First-exit time
The first exit time (FET) is the minimum between: (i) the time in
the future when the spot is expected to exit a barrier zone before
maturity, and (ii) maturity, if the spot has not hit any of the
barrier levels up to maturity. That is, if we denote the FET by
 then 
min
 where
 such that 
 or
 where 
 are the 'low' vs 'high' barrier levels and
 the spot of today.
The first-exit time is the solution of the following PDE

This equation is solved backwards
in time starting from the terminal condition 
 where 
 is the time to maturity and
boundary conditions 
. In case of a single
barrier option we use the same PDE with either 
 or 
. The parameter 
 represents the risk-neutral drift of the underlying stochastic process.
References
- Frédéric Bossens; Grégory Rayée; Nikos S. Skantzos; Griselda Deelstra (2009). "Vanna-Volga methods applied to FX derivatives : from theory to market practice". arXiv:0904.1074 [q-fin.PR].
 - Castagna, Antonio; Mercurio, Fabio (1 March 2007). "Vanna-Volga methods applied to FX derivatives : from theory to market practice" (PDF). Risk magazine.
 
- Shkolnikov, Yuriy (2009). "Generalized Vanna-Volga Method and its Applications".
 
- Wystup, Uwe (2006), FX Options and structured products, Wiley
 - US patent 7315838