[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]du.cn, [email protected]du.cn
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 dif-
fusion 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 time-
varying 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 Ctis said to be a Liu process if
(i) C0= 0,
(ii) Cthas stationary and independent increments,
1

(iii) every increment Ct+s−Csis a normally distributed fuzzy variable with expected value et and
variance σ2t2whose membership function is
µ(x) = 2 µ1 + exp µπ|x−et|
√6σt ¶¶−1
,−∞ < x < ∞.
Liu process is said to be standard if e= 0 and σ= 1. If Ctis 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 Xtand the stock price Ytfollow
(dXt=rXtdt
dYt=eYtdt+σYtdCt
(1)
where ris the riskless interest rate, eis the stock drift, σis the stock diffusion, and Ctis a
standard Liu process. It is just a fuzzy counterpart of Black-Scholes stock model [3].
3 Generalized Stock Model
Let Ctbe a standard Liu process, and let e(t) and σ(t) be functions. Then the fuzzy differential
equation
dYt=e(t)Ytdt+σ(t)YtdCt
has the solution
Yt=Y0exp µZt
0
e(s)ds+Zt
0
σ(s)dCs¶,
which is called the generalized geometric Liu process.
The stock price given by Ythas 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 eand σare 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 Xtand the stock price Ytfollow:
(dXt=r(t)Xtdt
dYt=e(t)Ytdt+σ(t)YtdCt
(2)
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 Kand expiration time T. Then the payoff from buying a European call option is (YT−K)+.
Considering the time value of money, the present value of this payoff is exp ³−RT
0r(t)dt´(YT−
K)+.
2

Definition 1 European call option price fcfor the generalized stock model is defined as
fc= exp Ã−ZT
0
r(t)dt!E
ÃY0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!−K!+
(3)
where Kis 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 fcfor the generalized stock model is defined as
fc=Y0exp ÃZT
0
(e(t)−r(t))dt!Z+∞
Kexp¡−RT
0e(t)dt¢/Y0
Cr (exp ÃZT
0
σ(t)dCt!≥u)du. (4)
Proof: By the definition of expected value of fuzzy variable, we have
fc= exp Ã−ZT
0
r(t)dt!E
ÃY0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!−K!+
= exp Ã−ZT
0
r(t)dt!Z+∞
0
Cr 
ÃY0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!−K!+ ≥r dr
= exp Ã−ZT
0
r(t)dt!Z+∞
0
Cr (Y0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!−K≥r)dr
=Y0exp ÃZT
0
(e(t)−r(t))dt!Z+∞
Kexp¡−RT
0e(t)dt¢/Y0
Cr (exp ÃZT
0
σ(t)dCt!≥u)du.
5 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 fpfor the generalized stock model is defined as
fp= exp Ã−ZT
0
r(t)dt!E
ÃK−Y0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!!+
(5)
where Kis the strike price at time T.
Theorem 2 European put option price fpfor the generalized stock model is defined as
fp=Y0exp ÃZT
0
(e(t)−r(t))dt!ZKexp¡−RT
0e(t)dt¢/Y0
−∞
Cr (exp ÃZT
0
σ(t)dCt!≤u)du. (6)
Proof: By the definition of expected value of fuzzy variable, we have
fp= exp Ã−ZT
0
r(t)dt!E
ÃK−Y0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!!+
= exp Ã−ZT
0
r(t)dt!Z+∞
0
Cr 
ÃK−Y0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!!+ ≥r dr
3

= exp Ã−ZT
0
r(t)dt!Z+∞
0
Cr (K−Y0exp ÃZT
0
e(t)dt+ZT
0
σ(t)dCt!≥r)dr
=Y0exp ÃZT
0
(e(t)−r(t))dt!ZKexp¡−RT
0e(t)dt¢/Y0
−∞
Cr (exp ÃZT
0
σ(t)dCt!≤u)du.
6 Conclusions
In this paper, we proposed a generalized stock model for financial market and investigated the op-
tion 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.
References
[1] Bachelier L, Th´eorie de la sp´eculation, Ann. Sci. ´ Ecole Norm. Sup., vol.17, pp.21-86, 1900.
[2] Baxter M, and Rennie A, Financial Calculus: An Introduction to Derivatives Pricing,
Cambridge University Press, 1996.
[3] Black F and Scholes M, The pricing of option and corporate liabilities, Journal of Political
Economy, vol.81, pp.637-654, 1973.
[4] Dai W, Reflection principle of Liu process, http://orsc.edu.cn/process/071110.pdf, 2007.
[5] Etheridge A, A Course in Financial Calculus, Cambridge University Press, 2002.
[6] Hull J, Options, Futures and Other Derivative Securities, 5th ed., Prentice-Hall, 2006.
[7] Li X, Expected value and variance of geometric Liu process, http://orsc.edu.cn/process
/071123.pdf, 2007.
[8] Li X, and Liu B, A sufficient and necessary condition for credibility measures, International
Journal of Uncertainty, Fuzziness &Knowledge-Based Systems, vol.14, no.5, pp.527-535,
2006.
[9] Liu B, Uncertainty Theory, Springer-Verlag, Berlin, 2004.
[10] Liu B, Uncertainty Theory, 2nd ed., Springer-Verlag, Berlin, 2007.
[11] Liu B, Fuzzy process, hybrid process and uncertain process, Journal of Uncertain Systems,
vol.2, no.1, pp.3-16, 2008.
[12] Liu B, and Liu YK, Expected value of fuzzy variable and fuzzy expected value models,
IEEE Transactions on Fuzzy Systems, vol.10, no.4, pp.445-450, 2002.
[13] Merton R, Theory of rational option pricing, Bell Journal Economics &Management Sci-
ence, vol.4, no.1 pp.141-183, 1973.
[14] Peng J, Credibilistic stopping problems for fuzzy stock market, http://orsc.edu.cn/process
/071125.pdf, 2007.
[15] Qin Z, On analytic functions of complex Liu process, http://orsc.edu.cn/process/071026.
pdf, 2007.
4

[16] Qin Z, and Li X, Option Pricing Formula for Fuzzy Financial Market, Journal of Uncertain
Systems, Vol.2, No.1, pp.17-21, 2008.
[17] Samuelson P A, Proof that properly anticipated prices fluctuate randomly, Ind. Manage.
Rev., Vol.6, pp.41-50, 1965.
[18] Samuelson P A, Mathematics of speculative prices, SIAM Rev., Vol.15, pp.1-42, 1973.
[19] You C, Multi-dimensional Liu process, differential and integral, http://orsc.edu.cn/process
/071015.pdf, 2007.
[20] Zadeh LA, Fuzzy sets, Information and Control, vol.8, pp.338-353, 1965.
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