Some Properties for the American Option-Pricing Model ()

Hong-Ming Yin

Department of Mathematics, Washington State University, Pullman, WA99164, USA.

**DOI: **10.4236/jmf.2012.23027
PDF
HTML XML
4,808
Downloads
8,762
Views
Citations

Department of Mathematics, Washington State University, Pullman, WA99164, USA.

In this paper we study global properties of the optimal excising boundary for the American option-pricing model. It is shown that a global comparison principle with respect to time-dependent volatility holds. Moreover, we proved a global regularity for the free boundary.

Share and Cite:

H. Yin, "Some Properties for the American Option-Pricing Model," *Journal of Mathematical Finance*, Vol. 2 No. 3, 2012, pp. 243-250. doi: 10.4236/jmf.2012.23027.

1. Introduction

It is well-known that, for the American option-pricing model, there is an optimal holding region for contracts holders (see [1-5]). The part of the boundary for the region is unknown (free boundary), which is often referred as the optimal excising boundary for option traders. This free boundary has to be calculated along with the option price of the security. The mathematical model for the problem is highly nonlinear and there is no explicit solution representation even when volatility and interest rate are assumed to be constants (see [4]). On the other hand, for the financial world as well as for the intrinsic interest itself, it is extremely important to find the location of the free boundary along with the option price of the security. Particularly, people would like to know how the price of a security changes near the option expiry time since it may change dramatically [6,7].

During the past few decades, there are many research papers concerning for various option-pricing models. There are several Monographs devoted to this topic (see, for examples, [1,3,4,8]). For the American option model as well as its generalization, the existence and uniqueness are studied by many researchers ( here just a few examples, [2,5,9-12]). A basic fact is that the American option-pricing model can be reformulated as a variational inequality of parabolic type. Hence, many known results about existence and uniqueness can be applied to the model. However, the disadvantage of the method is that there is no information about the free boundary. To overcome the shortcoming, several authors employed other methods to establish the existence and uniqueness for the problem (see [7,13-17]). Because of the practical importance, many researchers paid a special attention to the asymptotic behavior for the free boundary near the expiration time(see [6,18-25]). Moreover, various numerical computations for the location of free boundary are also carried out by many people (see, for examples, [14,25-28] and the references therein). More recently, some global property of the free boundary attracts some interest. The authors of [29,30] proved that the free boundary is convex if the volatility in the model is assumed to be a constant. However, this global property is not valid in the real financial market since the volatility depends on time and other economical factors. When the volatility depends on time and the security, the problem becomes much more challenging. In this paper we would like to study some global property of the free boundary. We want to find how the optimal exercising boundary changes when the volatility changes during the life-time of the option contract. This question is very important for structured products in the financial world.

We first recall the classical model for the American option-pricing model with one security or one type of asset. Let be the option price for a security such as a stock with price at time. Then it is wellknown that satisfies the Black-Scholes equation with no dividend [31,32]:

(1.1)

where is the interest rate and represents the market volatility of the stock, is the region defined below.

For the American put-option model (call-option is similar), in order to avoid loss for option holders, it is desirable to hold the option only when lies in the region (called optimal holding region):

where is the free boundary, which ensures, called the optimal exercising boundary.

On the free boundary, we know from the continuity of the option price that satisfies:

(1.2)

(1.3)

where is the striking price.

We also know the payoff value at the terminal time once the striking price is given:

(1.4)

(1.5)

For later use, we introduce :

where

In financial markets, the volatility plays a major role for the option pricing model. Option price often changes dramatically when the stock market is in a chaotic movement. This was the case when the flash-crash happened on May 6, 2010 as well as the case on Oct. 19, 1987. On the other hand, for a relatively stable market, the volatility mainly depends on time. This is particularly true for an index fund such as S&P500 index in the U.S. market. Hence, we assume that throughout this paper. Our question is how the free boundary changes when the volatility changes during the life-span of the option contract. We show that there is a global comparison principle for the free boundary with respect to the change of volatility. Moreover, a global existence result is also established as a by-product. Our proof is based on the line method (see [15]), which is different from existing literature (see [21,13] and the references therein). Although the existence of a solution for the problem is already known, our method does have several advantages. One of them is that the free boundary is determined along with the option price at each discrete time simultaneously. Moreover, a global regularity for the free boundary is also obtained. To author’s knowledge, this regularity result is new and optimal (see [19, 21,12]).

The paper is organized as follows. In Section 2, we construct a sequence of approximation solutions by using the line method. After deriving some uniform estimates, a global existence is established. Moreover, an optimal global regularity for the free boundary is also obtained. In Section 3, we first derive some comparison properties for the approximation solution and then show that the limit solution preserves the same property. Some concluding remarks are given in Section 4.

Remark 1.1: After this paper is completed, the author learned that E. Ekströn proved a result in [33] (2004) about the monotonicity of option price with respect to volatility. However, there is no result about the comparison result for the free boundary. Moreover, the method in [33] is totally different from ours here. In addition, we also present a regularity result for the free boundary.

2. Existence and Uniqueness

Since our argument in Section 3 is based on the discrete problem, we give the complete details about the construction of the approximation solution sequence. We also show that the approximation sequence is convergent to the solution of the original problem (1.1)-(1.5). As a byproduct, an optimal regularity of the free boundary is obtained.

The following conditions are always assumed throughout this paper.

H(1): Let for some. There exist positive constants and such that

Now we construct an approximate solution sequence by using the line method.

Let be a positive integer. Divide into

subintervals with equal length:

Define

If we use difference quotient to approximate and replace and by and, we have

This leads us to define the approximate solution and as follows:

From the terminal condition, we know

and. So we define

Suppose we have obtained and, we can define and as follows:

(2.1)

(2.2)

(2.3)

where we have extended into the whole interval by

It is easy to see that the above free boundary problem (2.1)-(2.3) has a unique solution for each. Actually, since the problem is one-dimensional one can find the solution and explicitly (see [4] for detailed calculation).

Now we use the interpolation to define the free boundary as follows:

Also, we define

We also use the notation

Our goal is to show that the approximate solution sequence is convergent to the solution of the original free boundary problem (1.1)-(1.5).

To this end, we need to derive some uniform estimates.

Lemma 2.1: For all,

Proof: From the definition, we see

if. Suppose we have shown that , we claim that. Indeed, if attains a negative minimum at some point, then at this minimum point, we see

which contradicts the right-hand side of the Equation (2.1). It follows that on. By the definition of on, we see for. Consequently, on.

On the other hand, we claim that has an upper bound. Indeed, it is obviously true for, which implies that when. We assume that is the first interval in which. Then, suppose that attains a positive maximum at an interior point, then at,. Thus,

It follows from Equation (2.1) that

which is a contradiction. On the boundary,

Obviously, when. Consequently, in. Furthermore, from the boundary condition (2.2), we see for all.

Q.E.D.

Lemma 2.2: There exists a constant such that

where depends only on known data, but not on.

Proof: This estimate is similar to the energy estimate for a parabolic equation. Indeed, we introduce new variables:

Define

Then the original free boundary problem (1.1)-(1.5) is equivalent to the following one:

(2.4)

(2.5)

(2.6)

(2.7)

where

On the other hand, by the definition we know

It follows that

Thus,

Now we can extend into the region, we use the continuity of and in to see that is a weak solution of the following problem:

(2.8)

(2.9)

where if and if.

Now we can use the line method method to define and which are exactly the same as for a classical parabolic equation (see [34], estimate (5.15) on page 137) and obtain the desired energy estimate. By the definition, we see clearly that for.

Q.E.D.

Lemma 2.3: There exists a constant such that

where depends only on known data, but not on.

Proof: Note that is uniformly Lipschitz continuous on. We may assume that is differentiable with a bounded derivative on.

Define

It follows that satisfies the following equations:

(2.10)

(2.11)

(2.12)

The maximum principle yields that is uniformly bounded and the bound depends only on known data. By using the same argument, we can easily deduce the uniform bound for.

Q.E.D.

Let be a small number and define

Lemma 2.4: There exists a constant such that

where depends only on the known data and, but not on.

Proof: From the theory of parabolic equations, we may assume that is differentiable up to. Set

From the boundary condition (2.5), we see

It follows by (2.6) that

From the Equation (2.4) and the boundary conditions (2.5) and (2.6), we see

which is uniformly bounded.

By differentiating Equation (2.4) with respect to x twice, we see satisfies

For any, the Schauder’s theory implies that is uniformly bounded and the bound depends on known data and. Now we can apply the maximum principle again on to conclude that is uniformly bounded. One can also use the same argument for to conclude the estimate for in. Similar estimates hold for the discretized solution and.

Q.E.D.

Lemma 2.5: There exists a constant such that

where depends only on known data and, but not on.

Proof: First of all, is continuous and is also differentiable on except. It follows that.

From the definition of and the boundary condition (2.2), we know that, for,

Note that, then

It follows that

where depends only on known data and.

Q.E.D.

With the results of Lemmas 2.1-2.5, we are ready to prove the following theorem.

Theorem 2.6: The free boundary problem (1.1)-(1.5) has a unique solution with

and.

Proof: First of all, the existence of a weak solution in follows the exactly same argument as that in [34] (Theorem 5.1, page 138). The uniqueness follows from the variational inequality. Moreover, regularity theory for parabolic equation implies that

Moreover, since the coefficients of the Equation (2.4) depends only on, we use the interior regularity of parabolic equations to conclude that

.

To see the regularity of the free boundary, we use Lemma 2.5 to see and

It follows that

Hence, by Ascoli-Arzela’s lemma, we can extract a subsequence, still denoted by, such that converges to a function, denoted by. Moreover,

. Since is arbitrarily, we have.

Furthermore, since, we use - estimate to obtain that for any,

where depends only on known data, and.

Now we convert back to the original variables to conclude that

By Sobolev’s embedding, we know that and are continuous over. On the other hand, since

we obtain

To see more regularity for, we use the boundary condition (2.5)-(2.6). Indeed, from the condition (2.5)- (2.6), we see

We differentiate (2.6) to find

From the Equation (2.4) we obtain

It follows that

Now we consider the free boundary problem for in:

It is easy to see that a unique solution exists with. It follows that

Q.E.D.

Remark 2.1: For the existence and uniqueness, we only need to assume that and are of class with a positive lower bound for.

3. Properties of Free Boundary

As we mentioned in the introduction, we are interested in how the free boundary changes when changes. It turns out that a comparison principle holds.

Theorem 3.1: Let and satisfy the assumption H(1). Let and

be the solutions of the problem (1.1)- (1.5) corresponding to and.

If on, then

To prove the theorem, we show that the comparison property holds for the discrete solution under certain condition.

Lemma 3.1: If, then

Proof: If necessary, we may use an approximation to replace by a smooth convex function on. Without loss of generality, we may simply assume. Then from the regularity theory, we know that is differentiable in. Let

Now for, we differentiate the Equation (2.1) twice with respect to to see that satisfies the following equation:

From the maximum principle, we see that can not attain a negative minimum if.

On the other hand, from the Equations (2.1) and (2.1) we see

It follows that, if,

Once we know, we can use the maximum principle to obtain the same conclusion for. After a finite number of steps, we obtain the desired result of Lemma 3.1.

Q.E.D.

Since we are interested in the relation between and, for convenience we use

and instead of and.

Lemma 3.2: For,

Proof: Let

We differentiate Equation (2.1) for with respect to to obtain:

From Lemma 3.1, we see that

The maximum principle implies that can not attain a negative minimum at an interior point in.

On:

We differentiate with respect to to obtain

It follows that for when. Now we can use the same argument to obtain the same conclusion for.

Moreover, from the second boundary condition, we have

.

Also, from Equation (2.1) we know

It follows that

Since attains its minimum 0 at the boundary, by Hopf’s lemma, we see. Thus,

Q.E.D.

Now we are ready to prove the main theorem in this section.

Proof of Theorem 3.1: Let and satisfy the assumption H(1). Let and be the solutions of (1.1)-(1.5) corresponding and. If on. We define

Let be the solution of the problem (2.1)- (2.3) corresponding to the volatility. It is clear that for if on

. By Lemma 3.1 and Lemma 3.2, if we have

From the definition of, we know that

provided that.

Since and are uniformly convergent to and, respectively, as. It follows that

It is also clear that on.

Q.E.D.

Remark 3.1: It is clear that the comparison result in Theorem 3.1 still holds if with a positive lower and upper bounds.

4. Conclusion

When the volatility is a constant, it has been known for a long time that the option price is bigger when the volatility is bigger. However, when the volatility is a function of time, , it is not clear how the option price nor the optimal excise boundary change when the volatility changes for the whole time period. In this paper we answered such a question. We show that a comparison property for option price and the optimal excising boundary hold (Theorem 3.1) when the volatility. This result is important for option traders. Moreover, we proved a global regularity result for the free boundary by using a very different method from the existing literature.

5. Acknowledgements

Some results in this paper were reported at the international conference “Problems and Challenges in Financial Engineering and Risk Management” held in Tongji University from June 23-24, 2011. The author would like to thank Professor Baojun Bian, Professor Xinfu Chen, Professor Min Dai, Professor Weian Zheng and other participants for their comments, which improves the original version of the paper.

Conflicts of Interest

The authors declare no conflicts of interest.

[1] | J. Hull, “Options, Futures and Other Derivative Securities,” 7th Edition, Prentice-Hall, New York, 2008. |

[2] | P. Jaillet, D. Lamberton and B. Lapeyre, “Variational Inequalities and the Pricing of American Options,” Acta Applied Mathematics, Vol. 21, No. 3, 1990, pp. 263-289. |

[3] | Y. K. Kwok, “Mathematical Models of Financial Derivatives,” Springer, Berlin, 2008. |

[4] | L. S. Jiang, “Mathematical Modelling and Methods of Option Pricing,” World Scientific Publishing Ltd., Singapore City, 2005. |

[5] | P. Van Moerbeke, “On Optimal Stopping and Free Boundary Problems,” Archive for Rational Mechanics and Analysis, Vol. 60, 1976, pp. 101-148. |

[6] | G. Barles, J. Burdeau, M. Romano and N. Sansoen, “Critical Stock Price near Expiration,” Mathematical Finance, Vol. 5, No. 2, 1995, pp. 77-95. |

[7] | P. Carr, R. Jarrow and R. Myneni, “Alternative Characterization of American Put Option,” Mathematical Finance, Vol. 2, 1992, pp. 87-105. |

[8] | P. Wilmott, “Derivatives: The Theory and Practice of Financial Engineering,” John Wiley and Sons, Inc., New York, 1998. |

[9] | A. Bensoussan, “On the Theory of Option Pricing,” Acta Applied Mathematics, Vol. 2, 1984, pp. 139-158. |

[10] | M. Broadie and J. Detemple, “The Valuation of American Options on Multiple Assets,” Mathematical Finance, Vol. 7, No. 3, 1996, pp. 241-286. |

[11] | S. Villaneuve, “Exercise Regions of American Option on Several Assets,” Finance and Stochastics, Vol. 3, No. 3, 1999, 295-322. |

[12] | C. R. Yang, L. S. Jiang and B. J. Bian, “Free Boundary and American Options in a Jump-Diffusion Model,” European Journal of Applied Mathematics, Vol. 17, No. 1, 2006, pp. 95-127. |

[13] | L. S. Jiang and M. Dai, “Convergence of the Explicit Difference Scheme and the Binomial Tree Method for American Options,” Journal of Computational Mathematics, Vol. 22, No. 3, 2004, pp. 371-380. |

[14] | I. J. Kim, “The Analytic Valuation of American Options,” Review of Financial Studies, Vol. 3, No. 4, 1990, pp. 547- 572. |

[15] | G. H. Meyer, “On Pricing American and Asian Options with PDE Methods,” Acta Mathematica of Univisitatis Comeniane, Vol. 70, No. 1, 2000, pp. 153-165. |

[16] | D. M. Salopek, “American Put Options, Pitman Monographs and Surveys in Pure and Applied Mathematics,” Vol. 84, Addison-Wesley Longman, London, 1997. |

[17] | D. Sevcovic, “Analysis of the Free Boundary for the Pricing of an American Call Option,” European Journal of Applied Mathematics, Vol. 10, 2001, pp. 1-13. |

[18] | D. A. Bunch and H. Johnson, “The American Put Option and Its Critical Stock Price,” Journal of Finance, Vol. 55, No. 5, 2000, pp. 2333-2356. |

[19] | E. Bayraktar and Hao Xing, “Analysis of the Optimal Exercise Boundary of American Options for Jump Diffusions,” SIAM Journal of Mathematical Analysis, Vol. 41, No. 2, 2009, pp. 825-860. |

[20] | X. F. Chen and J. Chadam, “Analytic and Numerical Approximations for the Early Exercise Boundary for the American Put Options,” Dynamical Continuous and Discrete Impulse Systems, Vol. 10, 2003, pp. 649-657. |

[21] | X. F. Chen and J. Chadam, “A Mathematical Analysis of the Optimal Exercise Boundary for American Put Options,” SIAM Journal of Mathematical Analysis, Vol. 38, 2007, pp. 1613-1641. |

[22] | S. D. Jacka, “Optimal Stopping and the American Put,” Mathematical Finance, Vol. 1, No. 1, 1991, pp. 1-14. |

[23] | C. Knessl, “Asymptotic Analysis of the American Call Option with Dividends,” European Journal of Applied Mathematics, Vol. 13, 2002, pp. 587-616. |

[24] | R. A. Kushe and J. B. Keller, “Optimal Exercise Boundary for an American Put Option,” Applied Mathematical Finance, Vol. 5, No. 2, 1998, pp. 107-116. |

[25] | R. Stamicar, D. Sevcovic and J. Chadam, “The Early Exercise Boundary for the American Put Near Expiry: Numerical Approximation,” Canadian Appl. Math. Quartely, Vol. 7, No. 4, 1999, pp. 427-444. |

[26] | F. Aitsahlia and T. Lai, “Exercise Boundaries and Efficient Approximations to American Option Prices,” Journal of Computational Finance, Vol. 4, 2001, pp. 85-103. |

[27] | G. Barone-Adesi and R. E. Whaley, “Efficient Analytic Approximation of American Option Values,” Journal of Finance, Vol. 42, No. 2, 1987, pp. 301-320. |

[28] | G. Barone-Adesi and R. Elliott, “Approximations for the Values of American Options,” Stochastic Analysis and Applications, Vol. 9, No. 2, 1991, pp. 115-131. |

[29] | X. F. Chen, J. Chadam, L. S. Jiang and W. A. Zheng, “Convexity of the Exercise Boundary of the American Put Option on a Zero Dividend Asset,” Mathematical Finance, Vol. 18, No. 1, 2008, pp. 185-197. doi:10.1111/j.1467-9965.2007.00328.x |

[30] | E. Ekstrom, “Convexity of the Optimal Stopping Boundary for the American Put Option,” Journal of Mathematical Analysis and Applications, Vol. 299, No. 1, 2004, pp. 147-156. |

[31] | F. Black and M. Scholes, “The Pricing of Options and Corporate Liabilities,” Journal of Politics and Economics, Vol. 81, No. 3, 1973, pp. 637-654. |

[32] | R. C. Merton, “Theory of Rational Option Pricing,” Bell Journal of Economics and Management Science, Vol. 4, No. 1, 1973, pp. 141-183. |

[33] | E. Ekstrom, “Properties of American Option Prices,” Stochastic Processes and Their Applications, Vol. 114, 2004, pp. 265-278. |

[34] | O. A. Ladyzhenskaya, “The Boundary Value Problems of Mathematical Physics,” Springer-Verlag, New York, 1985. |

Journals Menu

Contact us

+1 323-425-8868 | |

customer@scirp.org | |

+86 18163351462(WhatsApp) | |

1655362766 | |

Paper Publishing WeChat |

Copyright © 2024 by authors and Scientific Research Publishing Inc.

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.