# Binomial option price formula

The factor by which the price falls assuming it falls. Note that the model assumes that the price of the equity underlying the option follows a random walk. One Step Binomial Model. The essence of the model is this: The underlying price is assumed to follow a random walk and a probablity p is assigned to the likelihood that the price will rise.

Hence the probability of a fall in the stock price is 1-p. Conceptually any values for the three parameters, p , u and d may be used. However some values are more optimal than others. So the question is how can the best values be calculated? There is no simple answer to that question. In fact there are many different approaches to calculating values for p , u and d. These include methods developed by,.

Of the above approaches the Cox-Ross-Rubinstein method is perhaps the best known, with the Jarrow-Rudd method close behind. The remaining methods have been developed to address perceived and perhaps real deficiencies in those two methods. Three equations are required to be able to uniquely specify values for the three parameters of the binomial model. Two of these equations arise from the expectation that over a small period of time the binomial model should behave in the same way as an asset in a risk neutral world.

This leads to the equation Equation 1: Matching Variance which ensures that the variance matches. Cox, Ross and Rubinstein proposed the third equation Equation 3: Rearranging the above three equations to solve for parameters p , u and d leads to, Equation 4: The unique solution for parameters p , u and d given in Equation 4 ensures that over a short period of time the binomial model matches the mean and variance of an asset in a risk free world, and as will be seen shortly, ensures that for a multi-step model the price of the underlying asset is symmetric around the starting price S 0.

Before considering the more general case of a many-step model, consider the two-step model shown in Figure 2 Figure 2: A Two-Step Binomial Model. As with the one-step model of Figure 1 , over the first period of time in the two-step model the asset price may move either up to S u or down to S d. Over the second period, if the price moved up to S u in the first period then the price may move to either S uu or S ud.

However if the price moved down in the first period to S d then in the second period it may move to either S du or S dd. However if they are not equal then the price tree is said to be non-recombining or bushy. Since there are typically tens if not hundred or thousands of time steps taken when pricing an option the amount of data and hence computer memory, and computation time required to calculate a non-bushy tree is typically prohibitively and hence they are rarely used.

The third equation of the CRR model ensures that it generates a recombining tree that is centred around the original stock price S 0. Taking multiple time steps leads to the tree shown in Figure 3. A Multi-Step Binomial Model. In general the time period between today and expiry of the option is sliced into many small time periods. A tree of potential future asset prices is then calculated.

Each point in the tree is refered to as a node. The tree contains potential future asset prices for each time period from today through to expiry. The second step in pricing options using a binomial model is to calculate the payoffs at each node corresponding to the time of expiry.

This corresponds to all of the nodes at the right hand edge of the price tree. In general the payoff may depend on many different factors. As an example, the payoffs of simple put and call options will use the standard formulae. The third step in pricing options using a binomial model is to discount the payoffs of the option at expiry nodes back to today. This is achieved by a process called backwards induction , and involves stepping backwards through time calculating the option value at each node of the lattice in a sequential manner.

This is achieved using the appropriate following formulae. It is critical to notice that with backwards inducton the counter n starts at N i. Following the three step procedure described above the value of the option V 0 may be calculated.

This property also allows that the value of the underlying asset at each node can be calculated directly via formula, and does not require that the tree be built first. The node-value will be:. At each final node of the tree—i. Once the above step is complete, the option value is then found for each node, starting at the penultimate time step, and working back to the first node of the tree the valuation date where the calculated result is the value of the option.

If exercise is permitted at the node, then the model takes the greater of binomial and exercise value at the node. The expected value is then discounted at r , the risk free rate corresponding to the life of the option.

It represents the fair price of the derivative at a particular point in time i. It is the value of the option if it were to be held—as opposed to exercised at that point.

In calculating the value at the next time step calculated—i. The following algorithm demonstrates the approach computing the price of an American put option, although is easily generalized for calls and for European and Bermudan options:.

Similar assumptions underpin both the binomial model and the Black—Scholes model , and the binomial model thus provides a discrete time approximation to the continuous process underlying the Black—Scholes model.

In fact, for European options without dividends, the binomial model value converges on the Black—Scholes formula value as the number of time steps increases. The binomial model assumes that movements in the price follow a binomial distribution ; for many trials, this binomial distribution approaches the lognormal distribution assumed by Black—Scholes.

In addition, when analyzed as a numerical procedure, the CRR binomial method can be viewed as a special case of the explicit finite difference method for the Black—Scholes PDE; see Finite difference methods for option pricing.

In , Georgiadis shows that the binomial options pricing model has a lower bound on complexity that rules out a closed-form solution. From Wikipedia, the free encyclopedia. Journal of Financial Economics. Energy derivative Freight derivative Inflation derivative Property derivative Weather derivative. Retrieved from " https: Financial models Options finance. All articles with unsourced statements Articles with unsourced statements from May Articles with unsourced statements from January Views Read Edit View history.

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