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To receive news and asian option matlab updates for The Scientific World Journal, enter your email address in the box below. This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We study the numerical solution of the Greeks of Asian options. In particular, we derive a close form solution of of Asian geometric option and use this analytical form as a control to numerically calculate of Asian arithmetic option, which is known to have no explicit close form solution.

We implement our proposed numerical method and compare the standard error with other asian option matlab variance reduction methods. Our method provides asian option matlab efficient solution to the hedging strategy with Asian options. Asian options are referred to as securities with payoffs that depend on the average of the underlying stock price over a time interval. It got its name aroundwhen David Spaughton and Mark Standish worked for Bankers Trust in Tokyo, where they developed the first commercially used pricing formula for options linked to the average price of crude oil.

Asian options have appealing features that attract many investors. For example, end-users of energies or commodities tend to be exposed to the average prices over time, so Asian options suit their needs. Asian options are also popular among international corporations, who have ongoing currency exposures.

Asian options tend to be asian option matlab expensive than comparable Vanilla options, since the volatility in the average value of the underlying asset tends to be less than its spot value. Asian options also reduce the risk of price manipulation of underlying asset that is thinly traded.

The payoff of Asian arithmetic average call option with strike price is given by Since no analytical solution is known, a variety of numerical approximation techniques have been developed to analyze the Asian arithmetic average option. Many authors are devoted to the numerical approximation of the close form formula see Turnbull and Wakeman [ 2 ], Vorst [ 3 ], Levy [ 4 ], and Levy and Turnbull [ 5 ].

Monte Carlo simulation could be a nice approach see Broadie and Glasserman [ 6 ] and Kemna and Vorst [ 7 ]but it can be computational expensive without variation reduction method. It should also be noted that the discretization of the continuous process could introduce errors see Broadie et al. Once the approximated pricing formula for the Asian arithmetic option is available, one can obtain the Greeks by applying a shock asian option matlab the underlying asset price with asian option matlab finite difference methods.

In this paper, we study the Greeks of Asian arithmetic call option. In particular, we will implement a numerical scheme to compute of Asian arithmetic call option, by Monte Carlo method with a control variate. In Section 3we briefly introduce the general principle of Monte Carlo method with some variance reduction techniques. In Section 4we derive a close form pricing formula for the Asian geometric average call option.

As a consequence, we obtain an analytical formula for of Asian geometric average call option, asian option matlab will be used as a control variate in the Monte Carlo simulation. In the last section, we describe the numerical scheme to compute of Asian arithmetic average call option and compare our results with other variance reduction techniques.

The Monte Carlo method can be used to price a wide range of exotic options as well as to analyze their Greeks, especially when the close form solutions do not exist.

However, due to the reason of biased estimation and high computation cost, many modified Monte Carlo methods were proposed to estimate the Greeks by simulation. Broadie and Glasserman [ 6 ] developed a method called infinitesimal perturbation analysis, which is based on the relationship between the payoffs and the Greeks of interest.

Unlike the infinitesimal perturbation analysis, the likelihood ratio method is **asian option matlab** on the probability density function of underlying price and the Greeks. Both methods mentioned above provide unbiased asian option matlab but differ in applicability and effectiveness.

In order to reduce the variance of the estimators, many techniques have been introduced. The most effective variance reduction technique is **asian option matlab** control variate method.

In the case of Asian option, the payoff of asian option matlab Asian option is set to be a control variate in order to improve the effectiveness of the payoffs of algorithm Asian option prices. Other methods include analytic method and finite difference approach. See Boyle and Potapchik [ 11 ] for an extensive survey of relevant literature. Nowadays the advance of financial engineering has introduced lots of demands on using Monte Carlo simulations to price the options.

Monte Carlo methods are important in many situations where the option price admits a simple risk-neutral valuation formula but not a tractable PDE formulation, like Asian option, for example. As a consequence, the Greeks associate with these options do not admit close form formula but can be obtained numerically by a combination of finite difference method and Monte Carlo method. Let us first outline some general principle of Monte Carlo method and variance reduction techniques.

Let be random variable and let be measurable function such that with. Then we can numerically simulate independent replicas ofdenoted byand approximate by the Monte Carlo estimator: By the law of large number, we know that is a good estimate of in the sense that However, it is important call options and put options explained understand that Monte Carlo method is never exact.

The estimating error can be quantified by the so-called standard error defined by If the standard deviation is small, then it is a good sign that with high asian option matlab our Monte Carlo result would be close to the true value. Otherwise, the high standard deviation indicates that our result might be deviating from the true value. It is also important to observe that the standard deviation follows square root rule, which suggests that the convergence is relatively slow.

As a consequence, if the standard deviation asian option matlab high, obtaining a promising accuracy would require high computational cost. Next, we briefly introduce some classical variance reduction techniques. The main idea asian option matlab to use the same random number sequence when the target is the difference of two random variables which depends on the underlying random number sequence.

For simplicity, suppose now that we want to estimatewhere and are two random variables. It is obvious to see that If and are positively correlated, then we could reduce the variance of the estimator. Now suppose and asian option matlab, where is a standard normal random vector and and have the same monotonicity. Then the CRN estimator is defined by the following: It is easily seen that the variance of is less than the crude **Asian option matlab** Carlo estimator.

Now let us briefly introduce the general idea of control asian option matlab method. We want to estimate. Now if we can find another random variable asian option matlab known meanthen we can construct a family of unbiased estimators of: Indeed, Moreover, asian option matlab have To minimize the variance ofwe could choose As a consequence, to construct a good estimator, we need to choose a random variable that is positively correlated to.

Usually, if we could find a random variable with known mean that is positively correlated towe could simply choose. Intuitively, we could think of as an error adjustment to the unadjusted estimator. If the standard error is high, then deviation of from is large. At the same time, is large, by the fact that and are positively correlated.

It asian option matlab reduce the asian option matlab error ofeven with a moderate size of. The payoff of Asian geometric option is given by Under the classical Black-Scholes model, we know that the underlying asset is a geometric Brownian motion given by see Bjork [ 12 ] for more details.

Let be the price of Asian geometric call option under Black-Scholes model. It is important to note that the average price follows log normal distribution. Indeed, we have Observe that the integral is normal with mean 0 and variance To simplify our notation, we denote. By the argument above, we know that. Now by the risk-neutral valuation formula, we have On the one hand, we have where we used the fact that follows standard normal distribution and On the other hand, we got By change of variable we have Now putting all pieces together, we have Now we are ready to compute.

By chain rule, we have. In this part, we describe the numerical scheme of the computation of Asian arithmetic option Greeks with control variate method. Let us first remind the reader of the model. Under the risk-neutral probability measure, the dynamics of the underlying asset is described by the following stochastic differential equation: The solution is given by the geometric Brownian motion The payoff of Asian arithmetic option is given by Then the numerical scheme follows the next several steps.

Step 1 sample path generation. Let us first fix some parameters: We denoteand then we generate sample paths and by the following iterative steps: It asian option matlab important to observe that we used the same random numbers for both paths andfor the purpose of variance reduction.

Step **asian option matlab** approximating the payoff functions of both Asian asian option matlab and Asian geometric option. We first use the Riemann sum to numerically approximate the integral. Indeed, Next, we simulate copies of the Asian arithmetic option payoff Similarly, we simulate copies of the Asian geometric option payoff. Step 3 finite difference approximation.

Let be the Asian arithmetic option price under the Black-Scholes model, and then Similarly, we construct the sample estimator for Asian geometric option price. Step 4 define the control sample estimator for Asian geometric option Greeks. Consider Next, let us take a look at the results asian option matlab our proposed numerical simulation and compare it with the classic Common Random Number CRN for short with Table 1.

It is very clear that our proposed method is better than the CRN method in the sense that it introduce much smaller standard error than the classic CRN method with the same other parameters. We study asian option matlab numerical solution for the Delta of Asian arithmetic option, which was known to have no explicit analytical closed form solution. With the Delta of Asian geometric option as a control, we provided a simple, fast, intuitive, and reliable numerical solution in asian option matlab sense that the standard errors of Monte Carlo simulation were reduced greatly.

We also mention that, in recent years, many authors have been actively involved in the research of calculating Greeks asian option matlab Asian type option using various approaches. For instance, in [ 13 ], the authors provided formulas for the Greeks of Asian arithmetic option, which involves the time integral of geometric Brownian motion. As stated in the paper, the results are consistent with the Monte Carlo simulation.

In [ 14 ], with the advanced tool of Malliavin calculus, the authors asian option matlab a quasiexplicit formula for the Asian option Greeks.

Also, in [ 15 ], a PDE approach was utilized to understand the numerical value of the Asian option Greeks. To summarize, we believe that it is challenging but worth efforts to obtain more accurate value for the Asian arithmetic option Greeks, for the purpose of hedging strategy. Among various approximating methods, our numerical scheme provides a very neat and efficient choice when one wants to calculate hedge position of a portfolio that involves the Asian average options.

Because the assumption of high correlation for the two variates needs to hold, the performance on other Greeks, however, still needs to be examined.

The authors declare that there is no conflict of interests regarding the publication of this paper. Home Journals About Us. The Scientific World Journal. Subscribe to Table of Contents Alerts. Table of Contents Alerts.