[orsc.edu.cn]

Option Pricing Formula for Generalized Stock Models
Xin Gao,
Xiaowei Chen
Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China
[email protected],
[email protected]
Abstract
The stock model and option pricing problem are central contents in modern finance. In
this paper, generalized stock model for financial market is proposed and the European option
pricing formula for the generalized stock model is computed.
Keywords: finance, fuzzy process, option pricing, Liu process
1
Introduction
Brownian motion was introduced to finance by Bachelier [1]. Samuelson [17] [18] proposed the
argument that geometric Brownian motion is a good model for stock prices. In the early 1970s,
Black and Scholes [3] and, independently, Metron [13] used the geometric Brownian motion to
determine the prices of stock options. Stochastic financial mathematics was founded based on
the assumption that stock price follows geometric Brownian motion. The Black-Scholes formula
has become an indispensable tool in today’s daily financial market practice.
Different from randomness, fuzziness is another type of uncertainty in real world. In order
to deal with the evolution of fuzzy phenomena with time, Liu [11] proposed a fuzzy process,
a differential formula and a fuzzy integral. Later, the community renamed them Liu process,
Liu formula and Liu integral due to their importance and usefulness, just like Brownian motion,
Ito formula and Ito integral. Some researches surrounding the subject have been made. You
[19] studied differential and integral of multi-dimensional Liu process. Qin [15] considered some
properties of analytic functions of complex Liu process. Dai [4] gave a reflection principle related
to Liu process.
As a different doctrine, Liu [11] presented an alternative assumption that stock price follows
geometric Liu process. Moreover, a basic stock model for fuzzy financial market was also proposed
by Liu [11]. We call it Liu’s stock model in order to differentiate it from Black-Scholes stock model.
Qin and Li [16] presented the European options pricing formula for Liu’s stock model.
However, the time-varying interest rate, time-varying stock drift and time-varying stock diffusion factors were not considered in Liu’s stock model. In real market, time-varying factors
are necessary to be considered. We build a generalized stock model in the presence of a timevarying interest rate, time-varying stock drift and time-varying stock diffusion according to the
reality. Considering the option pricing problem is a fundamental problem in financial market, we
investigate the European option pricing formulas for the generalized stock model.
The rest of this paper is organized as follows. Some basic concepts about Liu process are
recalled and Liu’s stock model is introduced in Section 2. The generalized stock model based on
the generalized geometric Liu process is proposed in Section 3. European call and put option
price formulas are derived in Sections 4 and 5. Finally, some conclusions are listed.
2
Liu’s Stock Model
Definition 1 (Liu [11]) A fuzzy process Ct is said to be a Liu process if
(i) C0 = 0,
(ii) Ct has stationary and independent increments,
1
(iii) every increment Ct+s − Cs is a normally distributed fuzzy variable with expected value et and
variance σ 2 t2 whose membership function is
µ
µ
µ(x) = 2 1 + exp
π|x − et|
√
6σt
¶¶−1
, −∞ < x < ∞.
Liu process is said to be standard if e = 0 and σ = 1. If Ct is a Liu process, then the fuzzy
process Xt = exp(Ct ) is called a geometric Liu process.
It was assumed that stock price follows geometric Brownian motion, and Black-Scholes stock
model was then founded based on this assumption. Liu [11] presented an alternative assumption
that stock price follows geometric Liu process. Liu [11] presented a basic stock model for fuzzy
financial market in which the bond price Xt and the stock price Yt follow
(
dXt = rXt dt
(1)
dYt = eYt dt + σYt dCt
where r is the riskless interest rate, e is the stock drift, σ is the stock diffusion, and Ct is a
standard Liu process. It is just a fuzzy counterpart of Black-Scholes stock model [3].
3
Generalized Stock Model
Let Ct be a standard Liu process, and let e(t) and σ(t) be functions. Then the fuzzy differential
equation
dYt = e(t)Yt dt + σ(t)Yt dCt
has the solution
µZ
Yt = Y0 exp
Z
t
e(s)ds +
0
t
¶
σ(s)dCs ,
0
which is called the generalized geometric Liu process.
The stock price given by Yt has instantaneous stock drift e(t) and stock diffusion σ(t). Both
the instantaneous stock drift and stock diffusion are allowed to be time-varying.
This process includes all possible models of a stock price process that is always positive, has
no jumps, and is driven by a single standard Liu process. If e and σ are constant, it degenerates
into Liu’s stock model. Qin and Li [16] presented the European options pricing formula for Liu’s
stock model.
When the interest rate is time-varying denoted by r(t), and the stock price is a generalized
geometric Liu process, we obtain a new stock model for fuzzy financial market in which the bond
price Xt and the stock price Yt follow:
(
dXt = r(t)Xt dt
(2)
dYt = e(t)Yt dt + σ(t)Yt dCt
which is called as the generalized stock model.
4
European Call Option Pricing Formula
A European call option gives the holder the right, but not the obligation, to buy a stock at a
specified time for a specified price. In this section, we consider European call option pricing
problem for the generalized stock model.
Considering the generalized stock model, we assume that a European call option has strike
price K and expiration time T . Then the payoff from buying a European call ³option is (YT´−K)+ .
RT
Considering the time value of money, the present value of this payoff is exp − 0 r(t)dt (YT −
K)+ .
2
Definition 1 European call option price f c for the generalized stock model is defined as
à Z
! Ã
ÃZ
!
!+ 
Z T
T
T

f c = exp −
r(t)dt E  Y0 exp
e(t)dt +
σ(t)dCt − K
0
0
(3)
0
where K is the strike price at time T .
In order to calculate the option price, we solve Equation (3) and give an integral form as
follows:
Theorem 1 European call option price f c for the generalized stock model is defined as
ÃZ
!Z
(
ÃZ
!
)
T
+∞
T
f c = Y0 exp
(e(t) − r(t))dt
Cr exp
σ(t)dCt ≥ u du.
¡ RT
¢
0
K exp −
0
e(t)dt /Y0
(4)
0
Proof: By the definition of expected value of fuzzy variable, we have
à Z
! Ã
ÃZ
!
!+ 
Z T
T
T

f c = exp −
r(t)dt E  Y0 exp
e(t)dt +
σ(t)dCt − K
0
=
à Z
exp −
0
T
0
à Z
= exp −
T
0
0
ÃZ
T
= Y0 exp
!Z
(e(t) − r(t))dt
0
0
(
+∞
¡ RT
0
5
0
Ã

!Z
ÃZ
!
!+
Z T


+∞
T
r(t)dt
Cr
Y0 exp
e(t)dt +
σ(t)dCt − K
≥ r dr


0
0
0
!Z
(
ÃZ
!
)
Z T
+∞
T
r(t)dt
Cr Y0 exp
e(t)dt +
σ(t)dCt − K ≥ r dr
K exp −
0
¢
ÃZ
Cr exp
!
T
σ(t)dCt
e(t)dt /Y0
)
≥ u du.
0
European Put Option Pricing Formula
A European put option gives the holder the right, but not the obligation, to sell a stock at a
specified time for a specified price. In this section, we consider European put option pricing
problem for the generalized stock model.
Definition 2 European put option price f p for the generalized stock model is defined as
à Z
! Ã
ÃZ
!!+ 
Z T
T
T

f p = exp −
r(t)dt E  K − Y0 exp
e(t)dt +
σ(t)dCt
0
0
(5)
0
where K is the strike price at time T .
Theorem 2 European put option price f p for the generalized stock model is defined as
¡ RT
¢
ÃZ
!Z
(
ÃZ
!
)
T
K exp −
e(t)dt /Y0
T
0
(e(t) − r(t))dt
Cr exp
σ(t)dCt ≤ u du. (6)
f p = Y0 exp
0
−∞
0
Proof: By the definition of expected value of fuzzy variable, we have
à Z
! Ã
ÃZ
!!+ 
Z T
T
T

f p = exp −
e(t)dt +
σ(t)dCt
r(t)dt E  K − Y0 exp
0
0
à Z
= exp −
0
T
0
Ã

!Z
ÃZ
!!+
Z T


+∞
T
Cr
e(t)dt +
σ(t)dCt
≥ r dr
r(t)dt
K − Y0 exp


0
0
0
3
à Z
= exp −
!Z
T
r(t)dt
0
ÃZ
= Y0 exp
ÃZ
T
!Z
¡ RT
K exp −
(e(t) − r(t))dt
0
Z
T
Cr K − Y0 exp
0
0
6
(
+∞
e(t)dt +
0
¢
(
e(t)dt /Y0
!
T
σ(t)dCt
0
ÃZ
Cr exp
−∞
)
≥r
dr
!
T
σ(t)dCt
)
≤ u du.
0
Conclusions
In this paper, we proposed a generalized stock model for financial market and investigated the option pricing problems based on it. European call and put option price formulas for the generalized
stock model were defined and computed.
Acknowledgments
This work was supported by National Natural Science Foundation of China Grant No.60425309.
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