Discrete Dynamics in Nature and Society
Volume 2015 (2015), Article ID 579213, 10 pages
http://dx.doi.org/10.1155/2015/579213

Research Article

The Pricing of Vulnerable Options in a Fractional Brownian Motion Environment

Chao Wang, Shengwu Zhou, and Jingyuan Yang

China University of Mining and Technology, Xuzhou 221116, China

Received 6 January 2015; Revised 16 June 2015; Accepted 22 June 2015

Academic Editor: Juan R. Torregrosa

Copyright © 2015 Chao Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Under the assumption of the stock price, interest rate, and default intensity obeying the stochastic differential equation driven by fractional Brownian motion, the jump-diffusion model is established for the financial market in fractional Brownian motion setting. With the changes of measures, the traditional pricing method is simplified and the general pricing formula is obtained for the European vulnerable option with stochastic interest rate. At the same time, the explicit expression for it comes into being.

1. Introduction

Vulnerable option is a kind of option with credit risk that refers to a risk, a borrower that will default on any type of debt by failing to make required payments. Johnson and Stulz [1] firstly substituted default risk into option pricing and advanced a new definition called vulnerable option. Klein [2] obtained the pricing formula for vulnerable option with martingale method. Ammann [3] developed Klein’s model on the basis of structural approach. He finally obtained the explicit expression for vulnerable option under the assuming of interest rate and default intensity obeying the stochastic differential equation. What is more, other academics such as Chang and Hung [4] also discussed this problem, while all the discussions stated above are in the environment of geometric Brownian motion. Because of the inadequacies of geometric Brownian motion in describing the self-similarity and long-term dependence of stock prices, fractional Brownian motion is widely used into asset pricing. Hu and Øksendal [5] developed the structural approach in the condition that the stock prices followed a fractional Brownian motion and they proved that the correspondence to fractional Black-Scholes market had no arbitrage. For more literature on fractional Brownian motion, we can refer to Øksendal [6]. But there is another problem that fractional Black-Scholes market does not have equivalent martingale measure according to Sottinen and Valkeila [7]. Necula [8] applied quasi-martingale method to the risk neutral measure. Huang et al. [9] obtained the explicit expression for the European option price under the assuming of fractional Black-Scholes market. Su and Wang [10] and Li and Ma [11] derived the closed form formula for the price of the vulnerable European option by the method of changing measures.

In this paper, we will use quasi-martingale method to change measures, so we can derive the general pricing formula for the European vulnerable option under the assuming of the stock price obeying the jump-diffusion model, the interest rate and default intensity obeying Vasicek model which are driven by fractional Brownian motion.

2. Market Environment

Let the uncertainty in the economy be described by the filtered probability space . is the short-term interest rate which is consistently positive and -measurable in this space. Assume that is a risk neutral martingale measure under which the discounted asset price processes are martingales.

Suppose the stock price is given by

where is positive constant and is a fractional Brownian motion whose parameter is in the space . is a composite Poisson process, , and represents the th jump range of (using a convention that if there are no jumps). Consider . is a sequence of independent identically distributed random variables with the finite expected value. and are mutually independent and and are mutually independent. is a Poisson process whose intensity is . is a nonnegative adapted stochastic process which is integrable on any finite time interval. , , and are mutually independent.

Suppose that follows log-normal distribution so that ; then we have

Suppose that the interest rate and default intensity follow Vasicek model under the risk neutral measure

where , and are all positive constants. The covariance matrix of is

In order to prove the theorem, we introduce two lemmas firstly.

Lemma 1 (see [8]). We denote by the quasi-conditional expectation with respect to the risk neutral measure. Then the price at every of a bounded -measurable claim is given by

Lemma 2 (see [12]). If , where , , then

where is a standard normal distribution.

3. Pricing Options

In this section, we intend to discuss pricing vulnerable options in a Fractional Brownian Motion Environment.

We define that the default time is and represents the recovery rate due to the bankruptcy or reorganization, where is a constant. When the writer of the option defaults, the payoff is given by times the payoff of the default-free option at maturity. The price at every of an European vulnerable call option with strike price and maturity is given by

Note that ; we have

Since is a filtration, then . Suppose there is no default at present time, by the law of iterated conditional expectations; therefore,

Obviously is bonded and absolutely integrable, so we can interchange the two expectations by Fubini’s theorem

Since the full path of is known at time , we have [13]

Then (9) can be written as

For convenience, let , where and ; and are given as follows.

Theorem 3. Consider

where

Proof. By means of Lemma 1 we can see that the discounted asset price process whose numeraire is is a quasi-martingale. So we can define different equivalent quasi-martingale measures for different numeraires.
Suppose there is a bank account and a coupon with maturity . The price at every of the coupon is . Then the forward quasi-martingale measure equivalent to by the Radon-Nikodym derivative is given as

Since

hence

Using (3) we can have the expression for [14]

We integrate two sides from exclusively:

Using Fubini’s theorem [15], we exchange the last item’s integral sequence and obtain

Let , using multidimensional fractional Itô’s lemma [16]

So the Radon-Nikodym derivative is

Using fractional Girsanov’s theorem [14]

and are fractional Brownian motions under measure .
So, we can calculate under measure .
Since

we define and for convenience. We will calculate firstly.
Using (1) we have the expression for

We substitute into it; then

Using fractional Girsanov’s theorem, we have the expression for under measure

where

Since , we substitute into ; then

since

When ,

According to the nature of normal distribution, when , we have

where

So

Then we will calculate .
Since , we substitute into ; then

Using Lemma 2, when ,

where

so

Hence, when ,

Theorem 4. Consider

where

Proof. Using Lemma 1, the quasi-martingale measure equivalent to by the Radon-Nikodym derivative is given as

Using (4) we can have the expression for

Then we have

Let ; then

Using multidimensional fractional Itô lemma, let ; then

So

Using fractional Girsanov’s theorem

where

Under the probability measure , the processes , and are fractional Brownian motions. The covariance matrix of is the same as .
Then we can calculate under .
Since

we define and for convenience. We will calculate firstly.
Using fractional Girsanov’s theorem, we have the expression for under measure

where

We substitute into ; when , then

where

So

Then we will calculate .
Since , we substitute into

Using Lemma 2, when , we have

Let

and then

where

So

Hence

Theorem 5. The price at time of the European vulnerable call option is

Note 1. When there is no jump process, , and recovery rate is 1, (65) can be simplified as

4. Numerical Experiments

In this section, we mainly discuss the influence of different parameters on option prices. Figures are about the relationship between option prices and strike prices with different parameters.

The values of different parameters are as follows:

For all figures, the horizontal axis shows strike price and the vertical axis shows option value.

Figure 1 is about the influence of parameter on option value. As we can see from the figure, the influence will become larger with the increasing of strike prices within limits.

Figure 1: The influence of parameter .

Figure 2 is about the influence of recovery rate on option value. The default risk will decline with the increasing of recovery rate. So the option prices will fall down.

Figure 2: The influence of recovery rate .

Figures 3, 4, and 5 are about the influences of different covariance. According to these figures, we can see that different covariance has different influences on option value.

Figure 3: The influence of default covariance .

Figure 4: The influence of covariance .

Figure 5: The influence of covariance .

5. Conclusion

The method of changing measures is widely used for pricing options. In this paper, we develop this method and prove its feasibility in pricing options under the assumption of fractional Brownian motion. What is more, we also take jump process into consideration and obtain the general pricing formula for the European vulnerable option. Finally, we verify its accuracy through the numerical experiments.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgment

This work is supported by the Fundamental Research Funds for the Central Universities (2013XK03).

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