Tag Archives: American Option

Revisiting risk-neutral pricing of options

This is post #6 on the binomial option pricing model. The purpose of post #6:

    Post #6: To revisit the notion of risk-neutral pricing. The idea of risk-neutral pricing is that the binomial option pricing formula can be interpreted as a discounted expected value. In risk-neutral pricing, the option value at a given node is a discounted expected payoff to the option calculated using risk-neutral probabilities and the discounting is done using the risk-free interest rate. Then the price of the option is calculated by working backward from the end of the binomial tree to the front. Even though the risk-neutral probabilities are not the true probabilities of the up and down moves of the stock, option pricing using risk-neutral probabilities is the simplest and easiest pricing procedure and more importantly produces the correct option price. In this post, we examine why this is the case.

___________________________________________________________________________________

The binomial option pricing formula

In the post #1 on the binomial option pricing model, the following option pricing formula is derived (formula (4) in that post).

    \text{ }
    \displaystyle C=\Delta S + B=e^{-r h} \biggl(C_u \ \frac{e^{(r-\delta) h}-d}{u-d} +C_d \ \frac{u-e^{(r-\delta) h}}{u-d}  \biggr) \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)
    \text{ }

The formula has the appearance of a discounted expected value. The expected value refers to the result inside the parentheses, which is the expected value of the option value C_u (when stock price goes up) and the option value C_d (when stock price goes down). The calculation uses the probabilities p^* and 1-p^*:

    \displaystyle p^*=\frac{e^{(r-\delta) h}-d}{u-d} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)

    \displaystyle 1-p^*=\frac{u-e^{(r-\delta) h}}{u-d}

The values of p^* and 1-p^* sum to 1 and are positive (discussed in the post #2 on the binomial option pricing model). Thus they can be interpreted as probabilities. The value inside the parentheses in (1) can thus be interpreted as the expected value of the option payoff in the next period that follows a given node. The formula (1) uses the risk-free rate to discount the expected value back to that given node. Using this formula, the price of the option is calculated by working backward from the end of the binomial tree to the front. Using formula (1) in this recursive fashion is called the risk-neutral pricing.

From a computational standpoint, formula (1) is clear. Something is peculiar about the expected value calculation and the discounting in formula (1). The expected value is calculated using p^* and 1-p^*. What is p^*? Is it really the probability that the stock will go up? There is no reason to believe that p^* is the true probability of an up move in the stock price in one period in the binomial tree. Why is the true probability of stock price movement not used?

On the other hand, the expected value is counted from one period to the previous period using the risk-free rate. In the earlier posts on the binomial pricing model, we see that an option is equivalent to a leverage investment in the stock (e.g. a call is equivalent to borrowing the amount B to partly finance the purchase of \Delta shares). Thus an option is riskier than the stock. It is natural to think that discounting the value of an option should be done using the risk-free rate and instead using a rate of return equivalent to the option.

Our goal in this post is to show that the risk-neutral pricing approach produces the same option price as from using the more standard approach of using a true probability of a stock price up move and using a realistic discount rate. Even though using the more standard approach is possible, it is more cumbersome. Thus the risk-neutral pricing approach is easy to implement and produces the correct price. There is no reason to not use risk-neutral pricing.

___________________________________________________________________________________

The risk-neutral world

Let’s look at the implication of investing in a risk-neutral world. Imagine a world where investors are indifferent between a sure thing and a risky investment as long as both investments have the same expected value. For example, one investment pays $25 with certainty. Another investment with equally likely payoff of $50 or $0. Both investments have the same expected value but the second one is much riskier. Normally a risk premium is needed in order to entice a risk-averse investor to hold the second investment. In a risk-neutral world, investors are indifferent between these two investment choices. We further assume that in a risk-neutral world investors are willing to hold risky assets without a risk premium, i.e. risky assets such as stock are expected to earn at the risk-free rate.

Let’s see what happens when stock are expected to earn at the risk-free rate. Thus the end-of-period value of the stock is e^{r h} S if S is the initial stock price. Here r is the annual risk-free rate and h is the length of a period in years. Solving for p^* in the following equation

    \displaystyle p^* \ uS e^{\delta h}+(1-p^*) \ dS e^{\delta h}=e^{r h} S \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)

produces the following answer:

    \displaystyle p^*=\frac{e^{(r-\delta) h}-d}{u-d} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (4)

which is exactly the risk-neutral probability of an up stock move in formula (2) above. Thus p^* is the probability of an increase in the stock price in the scenario that the stock is expected to earn the risk-free rate. This is the reason that p^* is called the risk-neutral probability of a up move in stock price. Thus the risk-neutral pricing procedure is the realistic method for pricing options in a risk-neutral world. But we do not live in a risk-neutral world. Most investors will demand a risk premium in order to bear risk. We show that risk-neutral pricing is also a realistic method of pricing in a world where investors are risk-averse.

When we use risk-neutral pricing formula to price options, we are not saying that every investor is risk-neutral. Risk-neutral pricing is only an interpretation to formula (1). The best reason for using it is that it gives the correct result and is much easier to implement as compared to the more standard approach discussed below.

___________________________________________________________________________________

A more realistic investment world

Suppose that investors do care about risk. As a result, we want to calculate an expected value of payoff using true probability of stock price movements and using the expected rate of return of the option to discount the expected value of payoff.

To derive the true probability of an up stock move, suppose that the continuously compounded expected return on the stock is \alpha. Solve for p in the following equation

    \displaystyle p \ uS e^{\delta h}+(1-p) \ dS e^{\delta h}=e^{\alpha h} S \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (5)

yields the following answer:

    \displaystyle p=\frac{e^{(\alpha-\delta) h}-d}{u-d} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (6)

For p and 1-p to be between 0 and 1, the rate of return \alpha must be compatible with the stock price movement factors u and d. Specifically, we must have \displaystyle d < e^{(\alpha-\delta) h} < u. Given that we know \alpha, the expected return of the stock, we have just derived p, which is the probability of the stock going up. The following is then the expected payoff of the option in the next period:

    \displaystyle \begin{aligned} C&=p \ C_u + (1-p) \ C_d \\&=\frac{e^{(\alpha-\delta) h}-d}{u-d} \ C_u+\frac{u-e^{(\alpha-\delta) h}}{u-d} \ C_d \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (7) \end{aligned}

The value of C belongs to the next period. So we need to discount it back to the present period (or the present node in the tree). Let’s say the discount rate is \gamma. Then the following equation is satisfied:

    \displaystyle e^{\gamma h}=\frac{S \Delta}{S \Delta+B} \ e^{\alpha h}+\frac{B}{S \Delta+B} \ e^{r h} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (8)

Recall that an is equivalent to the portfolio of holding \Delta shares of stock and the amount B in lending (this is called the replicating portfolio). The make-up of the replicating portfolio is determined from the idea of replication: equating the option values and the values of the replicating portfolio, i.e. from solving the following equations. So the determination of \Delta and B has nothing to do with p or \alpha.

    \text{ }

    \displaystyle \text{ } \left\{\begin{matrix} \displaystyle \Delta \times (dS \ e^{\delta h})  + B \ e^{r h}=C_d&\ \ \ \ \ \ \text{ }& \\ \text{ }&\text{ } \\ \Delta \times (uS \ e^{\delta h})  + B \ e^{r h}=C_u&\ \ \ \ \ \ \text{ } \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (9)  \end{matrix}\right.

    \text{ }

The right hand side of (8) is the expected return of the replicating portfolio. The right hand side is simply the weighted average of the return of the \Delta shares of stock and the amount B in lending. Then \gamma can be determined from solving equation (8) for \gamma. Once \gamma is known, the option price C is:

    \displaystyle C=e^{-\gamma h} \ \biggl(\frac{e^{(\alpha-\delta) h}-d}{u-d} \ C_u + \frac{u-e^{(\alpha-\delta) h}}{u-d} \ C_d \biggr) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (10)

Let’s recap the journey it takes to get the option price in (10). We assume an expected rate of return \alpha for the stock in question, which leads to a probability p for an up movement in the stock. The actual probability p allows us to compute the expected option value in (7). To find the expected rate of return of the option, we take the weighted average of the returns of the stock and lending in the replcating portfolio. Then equation (1) gives the discounted value of the expected option value.

One peculiar thing happens in the process of obtaining the answer in (10). We can obtain \Delta and B by solving the equations in (9). Then we would have obtained the option price C=\Delta S+B. Doing so does not require knowing \alpha, the expected return of the stock, or p, the real probability of an up move in stock price. If the goal is to obtain the option price, the steps for obtaining p and \gamma are redundant! The ultimate reason that \alpha, p and \gamma are not necessary is that the option price in (10) is the same as the option price obtained from using risk-neutral pricing, i.e. equation (1). We verify this fact in the next section. Then we examine some examples.

___________________________________________________________________________________

Option valuation using true probabilities

Recall that the risk-neutral pricing formula (1) is identical to C=\Delta S+B. With a little bit of algebraic manipulation, we show that the option price in (10) is identical to C=\Delta S+B. First equation (10) is identical to the following:

    \displaystyle e^{-\gamma h} \ \biggl(\frac{e^{(r-\delta) h}-d}{u-d} \ C_u + \frac{u-e^{(r-\delta) h}}{u-d} \ C_d + \frac{e^{(\alpha-\delta) h}-e^{(r-\delta) h}}{u-d} (C_u-C_d)\biggr) \ \ \ \ \ (11)

where \displaystyle e^{-\gamma h}=\frac{S \Delta+B}{S \Delta e^{\alpha h}+B e^{r h}}. We show that the content within the big parentheses in (11) is the same as S \Delta e^{\alpha h}+B e^{r h}. Then (11) is identical to C=\Delta S+B. Based on the risk-neutral pricing formula (1), the first two terms inside the parentheses in (11) can be rewritten as:

    \displaystyle e^{r h} (\Delta S+B)=\frac{e^{(r-\delta) h}-d}{u-d} \ C_u + \frac{u-e^{(r-\delta) h}}{u-d} \ C_d

Denote the content inside the parentheses in (11) by A, we have the following derivation:

    \displaystyle \begin{aligned} A &=\frac{e^{(r-\delta) h}-d}{u-d} \ C_u + \frac{u-e^{(r-\delta) h}}{u-d} \ C_d + \frac{e^{(\alpha-\delta) h}-e^{(r-\delta) h}}{u-d} (C_u-C_d) \\&=e^{r h} (\Delta S+B) + \frac{e^{(\alpha-\delta) h}-e^{(r-\delta) h}}{u-d} (C_u-C_d) \\&=e^{r h} (\Delta S+B) + (e^{\alpha h}-e^{r h}) \ e^{-\delta h} \frac{C_u-C_d}{u-d} \\&=e^{r h} (\Delta S+B) + (e^{\alpha h}-e^{r h}) \ \Delta S \\&=S \Delta e^{\alpha h}+B e^{r h} \end{aligned}

The above derivation shows that the content inside the big parentheses in (11) is identical to S \Delta e^{\alpha h}+B e^{r h}. This means that (10) is identical to C=\Delta S + B. Therefore it is not necessary to use real stock price probability and real discount rate to calculate the option price. When we do, we know that the result is the same as from using the risk-neutral pricing method.

___________________________________________________________________________________

Example

We now examine examples to illustrate the point that risk-neutral pricing and valuation approach using true probabilities and true discount rate produce the same option price. We take two examples from previous posts and compare the two valuation approaches.

Example 1
This is Example 1 in the post #4 on the binomial option pricing model. The example is to price a 1-year call stock option with strike price $55. For the other details of this example, see Example 1 in the other post. Price this call option assuming that the expected annual rate of return of the stock is \alpha= 12%. Compare this pricing with the risk-neutral pricing.

The following is the binomial tree obtained by using risk-neutral pricing.

    \text{ }

    Example 1: option valuation using risk-neutral pricing
    \text{ }
    \displaystyle \begin{array}{lllll} \displaystyle   \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 95.45058 \\   \text{ } & \text{ } & \text{ } & \text{ } & C_{uu}=\$ 40.45058 \\   \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & S_u=\$ 75.67718 & \text{ } & \text{ } \\  \text{ } & \text{ } & C_u=\$ 21.76625 & \text{ } & \text{ } \\  \text{ } & \text{ } & \Delta=1.0 & \text{ } & \text{ } \\  \text{ } & \text{ } & B=- \$ 53.91093 & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  S= \$ 60 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 62.44865 \\  C=\$ 11.30954 & \text{ } & \text{ } & \text{ } & C_{ud}=\$ 7.44865 \\  \Delta=0.70710 & \text{ } & \text{ } & \text{ } & \text{ } \\  B=- \$ 31.11633 & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\   \text{ } & \text{ } & S_d=\$ 49.51187 & \text{ } & \text{ } \\   \text{ } & \text{ } & C_d=\$ 3.26482 & \text{ } & \text{ } \\   \text{ } & \text{ } & \Delta=0.34498 & \text{ } & \text{ } \\   \text{ } & \text{ } & B=- \$ 13.81577 & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 40.85710  \\  \text{ } & \text{ } & \text{ } & \text{ } & C_{dd}=\$ 0 \end{array}
    \text{ }

The following shows the calculation for the probability associated with the expected rate of stock return \alpha= 0.12.

    u=e^{(r-\delta) h+\sigma \sqrt{h}}=e^{(0.04-0) 0.5+0.3 \sqrt{0.5}}= 1.261286251

    d=e^{(r-\delta) h-\sigma \sqrt{h}}=e^{(0.04-0) 0.5-0.3 \sqrt{0.5}}= 0.825197907

    \displaystyle p=\frac{e^{(\alpha-\delta) h}-d}{u-d}=\frac{e^{(0.12-0) 0.5}-d}{u-d}= 0.542639222

    \displaystyle 1-p= 0.457360778

Next find the rate of return of option at each node. Because the compositions of the replicating portfolio are different across the nodes, the option rate of return \gamma is different.

    \displaystyle \begin{aligned}e^{\gamma (0.5)}&=\frac{75.67718 (1)}{75.67718 (1)-53.91093} \ e^{0.12 (0.5)}+\frac{-53.91093}{75.67718 (1)-53.91093} \ e^{0.04 (0.5)} \\&=1.164959169 \end{aligned}

    \displaystyle \gamma=2 \ \text{ln}(1.164959169)= 0.305372077 (at the node for stock price S_u)

    _______________

    \displaystyle \begin{aligned}e^{\gamma (0.5)}&=\frac{49.51187 (0.34498)}{49.51187 (0.34498)-13.81577} \ e^{0.12 (0.5)}+\frac{-13.81577}{49.51187 (0.34498)-13.81577} \ e^{0.04 (0.5)} \\&=1.238024651 \end{aligned}

    \displaystyle \gamma=2 \ \text{ln}(1.238024651)= 0.427034172 (at the node for stock price S_d)

    _______________

    \displaystyle \begin{aligned}e^{\gamma (0.5)}&=\frac{60 (0.70710)}{60 (0.70710)-31.11633} \ e^{0.12 (0.5)}+\frac{-31.11633}{60 (0.70710)-31.11633} \ e^{0.04 (0.5)} \\&=1.176388903 \end{aligned}

    \displaystyle \gamma=2 \ \text{ln}(1.176388903)= 0.324898989 (at the initial node)

We are now ready to calculate the option value at each node.

    \displaystyle \begin{aligned} C_u&=e^{-0.305372077 (0.5)} \ \biggl(0.542639222 \ (40.45058041) + 0.457360778 (7.448646452) \biggr) \\&=21.76624803 \end{aligned}

    \displaystyle \begin{aligned} C_d&=e^{-0.427034172 (0.5)} \ \biggl(0.542639222 \ (7.448646452) + 0.457360778 (0) \biggr) \\&=21.76624803 \end{aligned}

    \displaystyle \begin{aligned} C&=e^{-0.0.324898989 (0.5)} \ \biggl(0.542639222 \ (21.76624803) + 0.457360778 (3.264820059) \biggr) \\&=11.3095427 \end{aligned}

Note that the option price produced from the alternative approach is the same as from the risk-neutral approach. The following binomial tree shows all the results.

    \text{ }

    Example 1: option valuation using true probabilities
    \text{ }
    \displaystyle \begin{array}{lllll} \displaystyle   \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 95.45058 \\   \text{ } & \text{ } & \text{ } & \text{ } & C_{uu}=\$ 40.45058 \\   \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & S_u=\$ 75.67718 & \text{ } & \text{ } \\  \text{ } & \text{ } & C_u=\$ 21.76625 & \text{ } & \text{ } \\  \text{ } & \text{ } & \gamma=0.305372077 & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  S= \$ 60 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 62.44865 \\  C=\$ 11.30954 & \text{ } & \text{ } & \text{ } & C_{ud}=\$ 7.44865 \\  \gamma=0.324898989 & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\   \text{ } & \text{ } & S_d=\$ 49.51187 & \text{ } & \text{ } \\   \text{ } & \text{ } & C_d=\$ 3.26482 & \text{ } & \text{ } \\   \text{ } & \text{ } & \gamma=0.427034172 & \text{ } & \text{ } \\   \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\  \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 40.85710  \\  \text{ } & \text{ } & \text{ } & \text{ } & C_{dd}=\$ 0 \end{array}
    \text{ }

___________________________________________________________________________________

Example 2
This is Example 1 in the post #5 on the binomial option pricing model. Example 1 in that post is to price a 6-month American put option in a 3-period binomial tree. The strike price of the option is $45. The following shows the specifics of the binomial trees.

  • The initial stock price is $40.
  • The annual risk-free interest rate is r= 0.05.
  • The stock pays no dividends.
  • The annual countinuously compounded standard deviation of stock return is \sigma= 0.3.

Price this 6-month put option assuming that the expected annual rate of return of the stock is \alpha= 15%. Compare with the results from Example 1 in the previous post.

The following is the binomial tree from the previous post showing option price based on risk-neutral pricing. Since this is for an American option, early exercise is permitted if it is optimal to do so. There are two nodes in the following tree where early exercise is optimal (the option value is in bold). For option valuation using true probabilities, the calculation at each node is also an either-or proposition, i.e. the option value is either the value from the discounted expected value using probabilities or the value from early exercise.

    \text{ }

    Example 2 – Option valuation using risk-neutral pricing (from a previous post)
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 59.22258163 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 0 \\        \text{ } & \text{ } & S_{uu}=\$ 51.96108614   & \text{ } \\   \text{ } & \text{ } & C_{uu}=\$ 0   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 46.3561487 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 0 \\     \text{ } & S_u=\$ 45.58994896  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 2.41285153  & \text{ }    & \text{ } \\     S=\$ 40 &  \text{ } & S_{ud}=S_{du}=\$ 40.67225322    & \text{ } \\   C=\$ 6.024433917 &  \text{ } & C_{ud}=\$ 4.585624746    & \text{ } \\    \text{ } & S_d=\$ 35.68528077 \text{ }   &  \text{ } \\   \text{ } & \mathbf{C_d=\$ 9.314719233} \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 36.28501939 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 8.714980615 \\      \text{ } & \text{ } & S_{dd}=\$ 31.83598158   & \text{ } \\     \text{ } & \text{ } & \mathbf{C_{dd}=\$ 13.16401842}   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 28.40189853 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 16.59810147 \\      \end{array}

    \text{ }

The pricing results from using true probabilities will be identical to the risk-neutral pricing results. We will not show a diagram for the binomial tree. Instead, we show the calculation on some nodes.

The following shows the calculation for the probability associated with the expected rate of stock return \alpha= 0.15.

    u=e^{(r-\delta) h+\sigma \sqrt{h}}=e^{(0.05-0) \frac{0.5}{3} +0.3 \sqrt{\frac{0.5}{3}}}= 1.139748724

    d=e^{(r-\delta) h-\sigma \sqrt{h}}=e^{(0.05-0) \frac{0.5}{3} -0.3 \sqrt{\frac{0.5}{3}}}= 0.892132019

    \displaystyle p=\frac{e^{(\alpha-\delta) h}-d}{u-d}=\frac{e^{(0.15-0) \frac{0.5}{3}}-d}{u-d}= 0.537859921

    \displaystyle 1-p= 0.462140079

The following is the calculation at the node where the stock price is S_{ud}= $40.67225.

    \displaystyle \begin{aligned}e^{\gamma \frac{0.5}{3}}&=\frac{40.67225 (-0.86534)}{40.67225 (-0.86534)+39.78107} \ e^{0.15 \frac{0.5}{3}}+\frac{39.78107}{40.67225 (-0.86534)+39.78107} \ e^{0.05 \frac{0.5}{3}} \\&=0.878297298 \end{aligned}

    \displaystyle \gamma=6 \ \text{ln}(0.878297298)= -0.778620804

    \displaystyle \begin{aligned} C_{ud}&=e^{0.778620804 \frac{0.5}{3}} \ \biggl(0.537859921 \ (0) + 0.462140079 \ (8.714980615) \biggr) \\&=4.585624753 \end{aligned}

At the node where the stock price is S_{dd} = 31.83598, early exercise is optimal. There is no need to calculate the option value here using true probabilities. However, it is possible to calculate \gamma if it is desirable to do so. This is done by solving for \gamma in equation (10).

    \displaystyle 13.16401842=e^{-\gamma \frac{0.5}{3}} \ \biggl(0.537859921 \ (8.714980615) + 0.462140079 \ (16.59810147) \biggr)

    \gamma= -0.379059524

At the node where stock price is S_d= $35.68528, early exercise is also optimal. So the option value is not obtained by a discounted expected value (risk-neutral probabilities or otherwise). We now look at the initial node.

    \displaystyle \begin{aligned}e^{\gamma \frac{0.5}{3}}&=\frac{40 (-0.69683)}{40 (-0.69683)+33.89762} \ e^{0.15 \frac{0.5}{3}}+\frac{33.89762}{40 (-0.69683)+33.89762} \ e^{0.05 \frac{0.5}{3}} \\&=0.929959775 \end{aligned}

    \displaystyle \gamma=6 \ \text{ln}(0.929959775)= -0.435683676

    \displaystyle \begin{aligned} C&=e^{0.435683676 \frac{0.5}{3}} \ \biggl(0.537859921 \ (2.41285153) + 0.462140079 \ (9.314719233) \biggr) \\&=6.024433917 \end{aligned}

___________________________________________________________________________________

Remarks

The proof shown above and the calculation in the two examples show that option valuation using true probabilities based on the expected rate of return of the stock is not necessary. Risk-neutral pricing will produce the same results with much simpler and easier calculation.

One peculair point about option valuation using true probability and true discount rate that should be mentioned again. To discount the expected value of the option, we need to find the rate of return \gamma of the option at each node. To find the rate of return \gamma for the option at each node, we make use of the replicating portfolio \Delta and B. By knowing \Delta and B, we can derive the option value directly by C=\Delta S + B. Then we are done. Unless the goal is to find the expected return \gamma of an option, the valuation approach of using real probability and actual rate of return of option is pointless.

___________________________________________________________________________________

Practice problems

Practice problems to be added.

___________________________________________________________________________________
\copyright \ \ 2015 \ \text{Dan Ma}

Advertisements

The binomial option pricing model – part 5

This is post #5 on the binomial option pricing model. The purpose of post #5:

    Post #5: Tweak the binomial European option pricing methodology to work for American options.

The work in this post is heavily relying on the work in the binomial option pricing model for European options (multiperiod, one-period and more on one-period).

___________________________________________________________________________________

Valuing American options

The binomial tree approach of pricing options can also be used to price American options. Recall that a European option can be exercised only at expiration. An American option is one that can be exercised at any time during the life of the option. This means that in a binomial tree, an European option can be exercised only at the final nodes while an American option can be exercised at any node if it is profitable to do so. For an American option, the option value at a given node is obtained by comparing the exercise value (i.e. the value of the option if it is exercised at that node) and the intrinsic value (the value of the option resulting from the binomial model calculation). Thus for an American option, the option value at each node is simply the greater of the exercise value and the intrinsic value. The following 3-step process summarizes the approach in pricing an American option.

    Pricing an American option using a multi-period binomial tree

  1. Build a binomial tree.
  2. Calculate the option values at the last nodes in the tree. For a call, the option value at the end of the tree is either the stock price less the strike price or $0, whichever is greater. For a put, the option value at the end of the tree is either the strike price less the stock price or $0, whichever is greater.
  3. Starting from the option values at the final nodes, work backward to calculate the option value at earlier nodes. The option value at the first node is the price of the option. Keep in mind at each node, the option value is either the intrinsic value (the value calculated using the binomial pricing method) or the exercise value, whichever is the greater.

The three-step process is almost identical to the process of European option valuation discussed in binomial model post #4. The tweak is in Step 3, allowing for early exercise at any node whenever it is advantageous to do so (for the option holder).

In Step 3, we use risk-neutral pricing. The idea is that the option value at each node is the weighted average of the option values in the later two nodes and then discounted at the risk-free interest. The two option values (at the up node and at the down node) are weigted by the risk-neutral probabilities as follows:

    \displaystyle C^*=e^{-r h} \ [p^* \times (C^*)_u + (1-p^*) \times (C^*)_d] \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)

where C^* is the option value at a given node, and (C^*)_u is the option value at the up move and (C^*)_d is the option value at the down move that follow the node at C^*. The risk-neutral probability p^* for the up move is:

    \displaystyle p^*=\frac{e^{(r-\delta) h}-d}{u-d}

    \displaystyle d=e^{(r-\delta) h - \sigma \sqrt{h}}

    \displaystyle u=e^{(r-\delta) h + \sigma \sqrt{h}}

where r is the annual risk-free interest rate, h is the length (in years) of a period in the binomial tree, u and d are the stock price movement factors and \sigma is the stock price volatility factor. The risk neutral pricing is discussed in binomial model post # 2.

___________________________________________________________________________________

Examples

The binomial tree pricing process produces more accurate results when the option period is broken up into many binomial periods. Thus the binomial pricing model is best implemented in computer. In order to make a binomial tree a more realistic model for early exercise, it is critical for a binomial tree to have many periods when pricing American options. Thus the examples given here are only for illustration purpose.

Example 1
A 6-month American put option has the following characteristics:

  • Initial stock price is $40.
  • Strike price of the put option is $45.
  • The stock is non-dividend paying.
  • The annual standard deviation of the stock return is \sigma= 0.3.
  • The annual risk-free interest rate is r= 5%.

Price this put option with a 3-period binomial tree. Compare the American option with the European but otherwise identical put option.

Compare the following two binomial trees. The first one is for the American put option. The second one is for the otherwise identical European put option.

    \text{ }

    Example 1 – the binomial tree and option values – American put
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 59.22258163 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 0 \\        \text{ } & \text{ } & S_{uu}=\$ 51.96108614   & \text{ } \\   \text{ } & \text{ } & C_{uu}=\$ 0   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 46.3561487 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 0 \\     \text{ } & S_u=\$ 45.58994896  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 2.41285153  & \text{ }    & \text{ } \\     S=\$ 40 &  \text{ } & S_{ud}=S_{du}=\$ 40.67225322    & \text{ } \\   C=\$ 6.024433917 &  \text{ } & C_{ud}=\$ 4.585624746    & \text{ } \\    \text{ } & S_d=\$ 35.68528077 \text{ }   &  \text{ } \\   \text{ } & \mathbf{C_d=\$ 9.314719233} \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 36.28501939 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 8.714980615 \\      \text{ } & \text{ } & S_{dd}=\$ 31.83598158   & \text{ } \\     \text{ } & \text{ } & \mathbf{C_{dd}=\$ 13.16401842}   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 28.40189853 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 16.59810147 \\      \end{array}

    \text{ }

    \text{ }

    Example 1 – the binomial tree and option values – European put
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 59.22258163 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 0 \\        \text{ } & \text{ } & S_{uu}=\$ 51.96108614   & \text{ } \\   \text{ } & \text{ } & C_{uu}=\$ 0   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 46.3561487 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 0 \\     \text{ } & S_u=\$ 45.58994896  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 2.41285153  & \text{ }    & \text{ } \\     S=\$ 40 &  \text{ } & S_{ud}=S_{du}=\$ 40.67225322    & \text{ } \\   C=\$ 5.787711996 &  \text{ } & C_{ud}=\$ 4.585624746    & \text{ } \\    \text{ } & S_d=\$ 35.68528077 \text{ }   &  \text{ } \\   \text{ } & C_d=\$ 8.864829182 \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 36.28501939 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 8.714980615 \\      \text{ } & \text{ } & S_{dd}=\$ 31.83598158   & \text{ } \\     \text{ } & \text{ } & C_{dd}=\$ 12.79057658   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 28.40189853 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 16.59810147 \\      \end{array}

    \text{ }

At the node where the stock price is S_{dd}= 31.83598158, the option value for the American option is in bold and is greater than the option value in the tree for the European option. This is due to the fact that early exercise is possible in the tree for the American option. When early exercise is possible, the put option value at that node is $45 – $31.83598158 = $13.16401842. As a result of the early exercise in one node, the price of the American put option is $6.0044 whereas the price of the option if early exercise is not permitted is $5.7877.

Example 2
Consider Example 3 in the binomial model post #4. That example is to price a 6-month European call option in a 3-period binomial tree. The following shows the specifics of this call option.

  • Initial stock price is $60.
  • Strike price of the call option is $55.
  • The stock is non-dividend paying.
  • The annual standard deviation of the stock return is \sigma= 0.3.
  • The annual risk-free interest rate is r= 4%.

What is the price if early exercise is possible? The following is the binomial tree for the European call option from Example 3 in the previous post.

    \text{ }

    Example 2 – the binomial tree and option values – European call
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 88.39081 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 33.39081 \\        \text{ } & \text{ } & S_{uu}=\$ 77.68226   & \text{ } \\   \text{ } & \text{ } & C_{uu}=\$ 23.04770   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 69.18742 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 14.19742 \\     \text{ } & S_u=\$ 68.27104  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 14.23394  & \text{ }    & \text{ } \\     S=\$ 60 &  \text{ } & S_{ud}=S_{du}=\$ 60.80536    & \text{ } \\   C=\$ 8.26318 &  \text{ } & C_{ud}=\$ 6.61560    & \text{ } \\    \text{ } & S_d=\$ 53.43878 \text{ }   &  \text{ } \\   \text{ } & C_d=\$ 3.08486 \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 54.15607 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 0 \\      \text{ } & \text{ } & S_{dd}=\$ 47.59506   & \text{ } \\     \text{ } & \text{ } & C_{dd}=\$ 0   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 42.39037 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 0 \\      \end{array}

    \text{ }

Observe that early exercise is optimal at none of the nodes in this binomial tree. In this example, the American call option and the European call option have the same price (when suing a 3-period binomial tree).

Example 3
A 2-year American call option has the following characteristics:

  • Initial stock price is $75.
  • Strike price of the call option is $72.
  • The stock pays continuous dividends at the annual rate of \delta= 0.06.
  • The annual standard deviation of the stock return is \sigma= 0.3.
  • The annual risk-free interest rate is r= 3%.

Price this call option in a 3-period binomial tree. Also compute the price for the European call with the same characteristics.

    \text{ }

    Example 3 – the binomial tree and option values – American call
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 147.2799263 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 75.27992628 \\        \text{ } & \text{ } & S_{uu}=\$ 117.6114109   & \text{ } \\   \text{ } & \text{ } & \mathbf{C_{uu}=\$ 45.61141089}   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 90.2367785 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 18.2367785 \\     \text{ } & S_u=\$ 93.91941129  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 23.94529115  & \text{ }    & \text{ } \\     S=\$ 60 &  \text{ } & S_{ud}=S_{du}=\$ 72.05920794    & \text{ } \\   C=\$ 12.16262618 &  \text{ } & C_{ud}=\$ 7.848617166    & \text{ } \\    \text{ } & S_d=\$ 57.54338237 \text{ }   &  \text{ } \\   \text{ } & C_d=\$ 3.377832957 \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 55.28707407 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 0 \\      \text{ } & \text{ } & S_{dd}=\$ 44.14987805   & \text{ } \\     \text{ } & \text{ } & C_{dd}=\$ 0   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 33.87377752 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 0 \\      \end{array}

    \text{ }

Observe that early exercise is optimal at the node where the stock price is S_{uu}= $117.6114109. If early exercise is not allowed, the following is the binomial tree.

    \text{ }

    Example 3 – the binomial tree and option values – European call
    \text{ }
    \displaystyle \begin{array}{llll} \displaystyle   \text{Initial Price} & \text{Period 1} & \text{Period 2}   & \text{Period 3} \\  \text{ } & \text{ } & \text{ }   &  \text{ } \\  \text{ } & \text{ } & \text{ }   & S_{uuu}=\$ 147.2799263 \\   \text{ } & \text{ } & \text{ }   & C_{uuu}=\$ 75.27992628 \\        \text{ } & \text{ } & S_{uu}=\$ 117.6114109   & \text{ } \\   \text{ } & \text{ } & C_{uu}=\$ 42.42549702   & \text{ } \\      \text{ } & \text{ } & \text{ }   &  S_{uud}=\$ 90.2367785 \\  \text{ } & \text{ } & \text{ }   &  C_{uud}=\$ 18.2367785 \\     \text{ } & S_u=\$ 93.91941129  & \text{ }    & \text{ } \\   \text{ } & C_u=\$ 22.57415983  & \text{ }    & \text{ } \\     S=\$ 60 &  \text{ } & S_{ud}=S_{du}=\$ 72.05920794    & \text{ } \\   C=\$ 11.57252827 &  \text{ } & C_{ud}=\$ 7.848617166    & \text{ } \\    \text{ } & S_d=\$ 57.54338237 \text{ }   &  \text{ } \\   \text{ } & C_d=\$ 3.377832957 \text{ }   &  \text{ } \\       \text{ } & \text{ } & \text{ }   &  S_{udd}=\$ 55.28707407 \\   \text{ } & \text{ } & \text{ }   &  C_{udd}=\$ 0 \\      \text{ } & \text{ } & S_{dd}=\$ 44.14987805   & \text{ } \\     \text{ } & \text{ } & C_{dd}=\$ 0   & \text{ } \\       \text{ } & \text{ } & \text{ } & S_{ddd}=\$ 33.87377752 \\  \text{ } & \text{ } & \text{ } & C_{ddd}=\$ 0 \\      \end{array}

    \text{ }

___________________________________________________________________________________

Practice problems

Practice problems can be found in the companion problem blog.

___________________________________________________________________________________
\copyright \ \ 2015 \ \text{Dan Ma}