233x Filetype PDF File size 0.11 MB Source: www.iam.uni-bonn.de
Option Volatility and Pricing
Mouna HADDADI (PhD student)
Faculty of Science and Technology of Marrakesh, Cadi Ayyad university, Morocco.
YOUNGWOMENINPROBABILITY2014
Abstract Part 1. Historical volatility Part 2 : Implied volatility
This poster discusses three types of volatility : the historical, implied Thehistorical volatility reflects the past price movements of the under- The implied volatility is often interpreted as estimation of the future
and stochastic volatility, and the concept of local volatility. Finally the lying asset, it is calculated as a standard deviation of a stock’s returns volatility. It means that this volatility is a volatility anticipated by the
pricing formula of Vanilla options with stochastic volatility model such over a fixed number of days. market maker. In other words it is the value of σ that equalizes the
as the model of Heston is presented. The estimate of historical volatility starting from data : price calculated by Black & Scholes model with the observed prices on
n+1:thenumberof observations; the market
S : the price at the time t; observed Black−Scholes impl
t C (S ;T;K) = C (S ;T;K;σ )
u : the return at time t; t t t t
Introduction t
τ : duration of the time intervals in year.
Then Estimation of implied volatility
S Wecan find the value of an European call, by using the Risk-Neutral
The study of the volatility of certain financial assets became very im- u =ln t
t S
portant subject in finance. This importance comes from the possibility t−1 valuation method i.e by considering that price of a call corresponds to
to measuretheuncertaintyofevolutionoftheyieldonanasset(shareor for t = 1;2;:::;n its expected value of future return discounted :
Theestimate s of the standard deviation of u is given by this formula :
index) and the fact that the fluctuations of prices can not be neglected. t −rT b −rT b +
C0 = e E[max(S −K;0)]=e E (S −K)
Nowadays, any investor is conscious of these fluctuations which intro- v T T
u n
duce an element of risk into its portfolio. That is why the investors wish u 1 X 2
s = t (u −u) b
to choose the degree ”of exposure” at the risk compatible with their n−1 t where E is the expectation operator under the probability risk–neutral.
level of tolerance to this risk. Thus the study of the volatility plays an t=1
essential role in evaluation and hedging of risk of an investment. where u is the average of u The value of call and put option a time 0 is given by :
t
The Black and Scholes model assumes the following dynamic of the C = S Φ(d )−KerTΦ(d )
0 0 1 2
stock price : P = KerTΦ(−d )−S Φ(−d )
dS =µSdt+σSdz 0 2 0 1
The definition of the volatility t t t t
where z is a Wiener process where
t √ S σ2
dS ln( 0) + (r + )T √
Since t behaves like a normal distribution N(µdt;σ dt), the stan- d = K √ 2 ,d =d −σ T
St √ 1 2 1
Thevolatilityisameasureforvariationofpriceofafinancialinstrument dard deviation of the return is equal to σ dt σ T
over time. Therefore s is an estimator of σ√τ. Thus we estimate σ by σb where : and Φ is a the normal probability distribution function.
The types of volatility : s It is not possible to reverse the preceding equation and to express σ
σb = √ according to S , K, r, T and C . However, it is possible to determine
–Historical volatility τ 0 0
–Implied volatility the value of this implied volatility by using methods of interpolation
–Stochastic volatility like the method of Newton & Raphson.
Part 3 : Smile volatility Part 4 : Local volatility Part 5 : Heston model
The implied volatility of an option evolves according to the strike and Dupire formula : Heston model (1993)
the maturity of the option, now when we draw the implied volatility The Heston stochastic volatility model is based on the following stock
according to strike for a given maturity, generally we do not obtain a Fokker-Planck equation : price and variance dynamics
horizontal line, which corresponds to the assumption of consistency of (∂f + r ∂ (xf) − 1 ∂2 (x2σ2(x;T)f) = 0 dS(t) = µ(t)S(t)dt+pv(t)S(t)dZ
implied volatility. ∂T ∂x 2∂x2 1
f(x;t) = δ(S −x) sur [0,+∞]x[t,+∞]
t p
where δ is the Dirac function dv(t) = κ(θ −v(t))dt +σ v(t)dZ
2
where hdZ ;dZ i = ρdt , θ : the long-run average of v(t),
Theorem : for every (t,s) fixed the function : 1 2
κ : controls the speed by which v(t) returns to its long-run mean
and σ : the volatility of volatility.
Thefundamental partial differential equation (PDE) verified by option
−r(T−t) Q +
C(T;K)=e E [(S −K) =S =s] price is :
T t
is a solution of Dupire equation : ∂C 1 ∂2C ∂2C 1 ∂2C ∂C
∂C ∂C 1 2 2∂2C + CS2 +ρσvS + σ2v +rS −rC
∂T −r(C −K∂K)−2σ (T;K)K ∂K2 =0 ∂t 2 ∂S2 ∂S∂v 2 ∂v2 ∂S
In particular : s ∂C
∂C+r(C−K∂C) −∂v[κ(θ−v)−λv]=0
σ(T;K) = 2∂T ∂K
K2∂2C We seek to solve the preceding PDE in the case of a European call
∂K2 option of strike K and maturity T, by analogy with the Black & Scholes
formula, the solution of this option is of the form :
C(S;v;t) = SP −Ke−r(T−t)P
1 2
Part 4 : The link between local volatility and implied
volatility By injecting it in the PDF, and From the Fourier inversion theorem,
we have : Z " #
P =1+1 +∞Re e−iφln(K)fj dφ
Implied volatility smile j 2 π iφ
Let us consider a model with non-deterministic volatility. That is the 0
risk-neutral dynamics of S is written as : For j = 1;2 , P are probabilities , and f are characteristics functions
j j
The Smile of volatility is a phenomenon observed on the markets of such as
dS
options vanillas which contradicts the assumption of Black and Scholes t = µdt +σ dW
S t t f (x;v;T;φ) = exp(C(τ;φ)+D(τ;φ)v +iφx)
according to which the volatility of an option is constant and is not t j
influenced by the value of other parameters. From a statistical point Instantaneous volatility σ is a process such as : h dri
and C(τ;φ) = rφiτ + a (b −ρσφi+d)τ −2ln 1−ge
of view such a form of curve of volatility according to the strike price Z σ2 j 1−g
corresponds to a value of Kurtosis higher than 3, therefore risk-neutral T
σ2ds < ∞;∀ T > 0 " #
dynamics of Black & Scholes and Merton are not compatible with the s bj −ρσφi+d 1−edr
0 D(τ;φ) =
phenomenon of smile which exists on all markets options. σ2 1−gedr
Thus we can define the local variance as conditional expectation of the
future instantaneous variance bj −ρσφi+d q
h i g = and d = ρσφi−b 2−σ2 2u φi−φ2
2 Q 2 b −ρσφi−d j j
σ (T;K) = E σ S =K j
L T T
u = 1 , u = −1 , a = κθ , b = κ+λ−ρσ , b = κ+λ
This definition and that based on Dupire’s formula are equivalent. 1 2 2 2 1 2
no reviews yet
Please Login to review.