Financial Mathematics

Revisiting risk-neutral pricing of options

June 18, 2015 Leave a comment

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

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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).

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

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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.

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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.

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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 $\alpha$ .

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

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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.

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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.

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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.

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

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

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

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

$\displaystyle \gamma=2 \ \text{ln}(1.176388903)=$ 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.

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

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

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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

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

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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.

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Practice problems

Practice problems to be added.

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

The binomial option pricing model – part 5

June 13, 2015 Leave a comment

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).

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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

Build a binomial tree.
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.
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.

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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.

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

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

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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.

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

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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.

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

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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.

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

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Practice problems

Practice problems can be found in the companion problem blog.

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

The binomial option pricing model – part 4

June 11, 2015 Leave a comment

This is post #4 on the binomial option pricing model. The purpose of post #4:

The work in this post is heavily relying on the work in the one-period binomial option pricing model discussed in the part 1 post and in the part 2 post.

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Multi-period binomial trees

We describe how to price an option based on a multi-period binomial tree. We use a 2-period tree to anchor the discussion. Assume that the length of one period is $h$ years. Then the following 2-period binomial tree is to price a $2h$ -year option (call or put). For example, if $h=$ 0.25 years, then the following binomial tree is a basis for pricing a 6-month option.

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Figure 1 – 2-period binomial tree

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The stock prices in the above binomial tree are constructed using forward prices. At the left, $S$ is the initial stock price. Then the stock prices at the end of period 1 are:

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$\displaystyle S_d=S \ e^{(r-\delta) h - \sigma \sqrt{h}} \ \ \ \ \ \ \ \ \ \displaystyle S_u=S \ e^{(r-\delta) h + \sigma \sqrt{h}} \ \ \ \ \ \ \ \ \ \ \ \ \ (1)$

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where $r$ is the annual risk-free interest rate, $\delta$ is the annual continuous dividend rate and $\sigma$ is the annualized standard deviation of the continuously compounded stock return. Multiplying $\sigma$ by $\sqrt{h}$ adjusts the standard deviation to make the stock return appropriate for a period of length $h$ .

The stock prices at the end of period 2 are also constructed based on the idea in (1). The formula (1) takes a starting price (e.g. $S_u$ ) and calculates the up move, e.g. $S_{uu}$ and the down move, e.g. $S_{dd}$ . The same idea in (1) can then be used to build additional periods beyond the period 2.

Because the stock prices in Figure 1 are calculated by formula (1), an up move followed by a down move leads to the same stock price as a down move followed by an up move. Thus $S_{ud}=S_{du}$ at the end of the second period. When this happens, the resulting binomial tree is called a recombining tree. When up-down move leads to a different price from a down-up move, the resulting tree is called a nonrecombining tree. When stock prices are calculated using the forward prices, the resulting binomial tree is a recombining tree.

Suppose that the binomial tree in Figure 1 models a $2h$ -year option. We can compute the value of the option at each node at the end of period 2.

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Figure 2 – 2-period binomial tree with option values

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The option value is $0 if it is not advantageous for the option buyer to exercise. If it is, the option value is the difference between the stock price at expiration and the strike price. For example, for a call option, if strike price is $50 and $S_{uu}=$ $75, then $C_{uu}=$ = $25. For a put option, if strike price is $50 and if $S_{dd}=$ $30, then $C_{dd}=$ $20.

Once the option values at the end of the last period are known, we can calculate the option values for the preceding periods and at time 0.

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Figure 3 – 2-period binomial tree with option values

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Risk-neutral pricing is an efficient algorithm for pricing an option using a binomial tree. The option value at a given node is simply the weighted average using risk-neutral probabilities of the two option values in the next period discounted at the risk-free interest rate. The following is the risk-neutral pricing formula:

$\displaystyle C^*=e^{-r h} \ [p^* \times (C^*)_u + (1-p^*) \times (C^*)_d] \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)$

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 for the up move is:

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

For example, in Figure 3, the option value $C_u$ at the node for stock price $S_u$ is:

$\displaystyle C_u=e^{-r h} \ [p^* \times C_{uu} + (1-p^*) \times C_{ud}]$

Once the option values at expiration (the end of the last period in the binomial tree) are known, we can use the risk-neutral pricing formula (2) to work backward to derive the option value $C$ at the first node in the tree, which is the price of the option in question.

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The process of pricing an option using a multi-period binomial tree

The process just described can be used to price a European option based on a binomial tree of any number of periods. The process is summarized as follows:

Pricing an option using a multi-period binomial tree

Build a binomial tree as in Figure 1. The stock prices in this tree are relative to the forward prices as shown in formula (1).
Calculate the option values at the end of the last period in the tree as in Figure 2. This step is based on a comparison of the strike price and the stock prices at expiration of the option.
Starting from the option values at the end of the last period, work backward to calculate the option value at each node in each of the preceding periods. One way to calculate the option value at each node is to use the risk-neutral pricing formula in (2).

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Two-period examples

We demonstrate how to extend the one-period calculation to two-period through the following two examples.

Example 1
Price a one-year call option using a 2-period binomial tree. The specifics of the call option and its underlying stock are:

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%.

The one-year option period is divided into two periods, making one period being 6 months. Thus $h=$ 0.5. This example is based on Example 4 in this previous post, which is about a 6-month call option with the same specifics as given above. Thus Example 1 here is Example 4 in the previous post with an additional 6-month period in the binomial tree.

Usually, in working a binomial tree problem, one tree diagram suffices. In order to make the procedure clear, we use three tree diagrams to demonstrate the three steps involved. Step 1 is to build the binomial tree. The following diagram is the result.

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Step 1: build the binomial tree (Example 1)
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$\displaystyle \begin{array}{lllll} \displaystyle \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 95.45058 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_u=\$ 75.67718 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ S= \$ 60 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 62.44865 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_d=\$ 49.51187 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 40.85710 \end{array}$

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The stock prices in the above binomial tree are based on the following movement factors $u$ and $d$ .

$\displaystyle u=e^{(0.04-0) 0.5 + 0.3 \sqrt{0.5}}=$

$\displaystyle d=e^{(0.04-0) 0.5 - 0.3 \sqrt{0.5}}=$ 0.825197907

The following details the calculations for the stock prices:

$\displaystyle S_u=60u=$

$\displaystyle S_d=60d=$

$\displaystyle S_{uu}=u S_u$ 1.261286251 (75.67717506) = $95.45058041
$\displaystyle S_{du}=S_{ud}=d S_u$ 0.825197907 (75.67717506) = $62.44864645
$\displaystyle S_{dd}=d S_d$ 0.825197907 (49.51187441) = $40.85709513

Step 2 is to obtain the option values at expiration. For a European call option, the option value at expiration is the mximum of $0 or the stock price less the strike price. Simply compare the strike price of $55 with the stock prices at the end of the binomial tree. Any node with stock price above the strike price $55 has positive option value. The following tree shows the result.

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Step 2: add option values at expiration (Example 1)
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$\displaystyle \begin{array}{lllll} \displaystyle \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 95.45058 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{uu}=\$ 40.45058 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_u=\$ 75.67718 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ S= \$ 60 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 62.44865 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{ud}=\$ 7.44865 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_d=\$ 49.51187 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 40.85710 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{dd}=\$ 0 \end{array}$
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Step 3 is to work backward from the end of the tree to the front of the tree. For example, calculate the option value at each node in period 1 by using the option values of the associated up and down nodes in period 2. We take the approach of using risk-neutral pricing described in (2). The following diagram shows the results.

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Step 3: work backward to obtain option price (Example 1)
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$\displaystyle \begin{array}{lllll} \displaystyle \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 95.45058 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{uu}=\$ 40.45058 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_u=\$ 75.67718 & \text{ } & \text{ } \\ \text{ } & \text{ } & C_u=\$ 21.76625 & \text{ } & \text{ } \\ \text{ } & \text{ } & \Delta=1.0 & \text{ } & \text{ } \\ \text{ } & \text{ } & B=- \$ 53.91093 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ S= \$ 60 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 62.44865 \\ C=\$ 11.30954 & \text{ } & \text{ } & \text{ } & C_{ud}=\$ 7.44865 \\ \Delta=0.70710 & \text{ } & \text{ } & \text{ } & \text{ } \\ B=- \$ 31.11633 & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_d=\$ 49.51187 & \text{ } & \text{ } \\ \text{ } & \text{ } & C_d=\$ 3.26482 & \text{ } & \text{ } \\ \text{ } & \text{ } & \Delta=0.34498 & \text{ } & \text{ } \\ \text{ } & \text{ } & B=- \$ 13.81577 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 40.85710 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{dd}=\$ 0 \end{array}$
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As mentioned above, to calculate the option values, we use risk-neutral probabilities:

$\displaystyle u=e^{(0.04-0) 0.5 + 0.3 \sqrt{0.5}}=$

$\displaystyle d=e^{(0.04-0) 0.5 - 0.3 \sqrt{0.5}}=$ 0.825197907

$\displaystyle p^*=\frac{e^{(0.04-0)0.5}-0.825197907}{1.261286251-0.825197907}=$ 0.447164974

$\displaystyle 1-p^*=$ 0.552835026

The following computes the option values:

$C_u=e^{-0.04 (0.5)} [ p* (40.45058041)+(1-p^*)(7.44864645)]=$

$C_d=e^{-0.04 (0.5)} [ p* (7.44864645)+(1-p^*)(0)]=$ $3.264820056

$C=e^{-0.04 (0.5)} [ p* (21.76624801)+(1-p^*)(3.264820056)]=$ $11.30954269

The diagram in Step 3 also shows the replicating at each node. For example, the replicating portfolio at the node for $C_{u}$ is computed as follows:

$\displaystyle \Delta=e^{0(0.5)} \ \frac{C_{uu}-C_{ud}}{S_{uu}-S_{ud}}=\frac{40.45058041-7.44864645}{95.45058041-62.44864645}=$

$\displaystyle \begin{aligned} B&=e^{-0.04(0.5)} \ \frac{u C_{ud}-d C_{uu}}{u-d} \\&=e^{-0.02} \ \frac{1.261286251 (7.44864645)-0.825197907 (40.45058041)}{1.261286251-0.825197907} \\&=- \$ 53.91093 \end{aligned}$

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Example 2
This is Example 5 in this previous post. Example 5 in that post is a 3-month put option. We now price the same 3-month put option using a 2-period binomial tree. Thus the 3-month option period is divided into two periods. The following gives the specifics of this put option:

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%.

We carry out the same three steps as in Example 1. The following diagram captures the results of all three steps.

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Example 2: binomial tree for pricing put option
$\text{ }$
$\displaystyle \begin{array}{lllll} \displaystyle \text{Initial Price} & \text{ } & \text{Period 1} & \text{ } & \text{Period 2} \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{uu}=\$ 50.07448 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{uu}=\$ 0 \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_u=\$ 44.75466 & \text{ } & \text{ } \\ \text{ } & \text{ } & C_u=\$ 2.35281 & \text{ } & \text{ } \\ \text{ } & \text{ } & \Delta=-0.46983 & \text{ } & \text{ } \\ \text{ } & \text{ } & B=- \$ 23.37970 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ S= \$ 40 & \text{ } & \text{ } & \text{ } & S_{ud}=\$ 40.50314 \\ C=\$ 5.56462 & \text{ } & \text{ } & \text{ } & C_{ud}=\$ 4.49686 \\ \Delta=-0.72087 & \text{ } & \text{ } & \text{ } & \text{ } \\ B=\$ 34.39932 & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & S_d=\$ 36.20016 & \text{ } & \text{ } \\ \text{ } & \text{ } & C_d=\$ 8.51947 & \text{ } & \text{ } \\ \text{ } & \text{ } & \Delta=-1 & \text{ } & \text{ } \\ \text{ } & \text{ } & B=- \$ 44.71963 & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{ } & S_{dd}=\$ 32.76128 \\ \text{ } & \text{ } & \text{ } & \text{ } & C_{dd}=\$ 12.23872 \end{array}$
$\text{ }$

Note that the put option calculated in Example 5 in this previous post using one binomial period is
$5.3811 whereas the put option price from a 2-period binomial tree here is $5.56462. It is not uncommon for binomial option prices to fluctuate when the number of periods $n$ is small. When $n$ is large, the binomial price will stabilize.

Note that the option period is 3-month long (a quarter of a year). Thus one period is $h=$ 0.25/2 = 0.125 of a year. To build the binomial tree, the following shows the calculation for the stock prices $S_d$ and $S_{du}$ .

$\displaystyle u=e^{(0.05-0) 0.125 + 0.3 \sqrt{0.125}}=e^{0.1625}=$

$\displaystyle d=e^{(0.05-0) 0.125 - 0.3 \sqrt{0.125}}=e^{-0.1375}=$ 0.905003908

$\displaystyle S_d=40d=$ 40 (0.905003908) = $36.20015632

$\displaystyle S_{ud}=S_{du}=S_d \ d=$ 36.20015632 (1.118866386) = $40.50313807

As in Example 1, we perform risk-neutral pricing. The following shows the calculation of the option values.

$\displaystyle p^*=\frac{e^{(0.05-0)0.25}-0.87153435}{1.176448318-0.87153435}=$ 0.462570155

$\displaystyle 1-p^*=$ 0.537429845

$C_u=e^{-0.05 (0.125)} [ p* (0)+(1-p^*)(4.496861938)]=$ $2.352809258

$C_d=e^{-0.05 (0.125)} [ p* (4.496861938)+(1-p^*)(12.23871707)]=$ $8.519470762

$C=e^{-0.05 (0.125)} [ p* (2.352809258)+(1-p^*)(8.519470762)]=$ $5.564617421

The diagram in Example 2 also shows the replicating at each node. For example, the replicating portfolio at the node for $C_{d}$ is computed as follows:

$\displaystyle \Delta=e^{0(0.125)} \ \frac{C_{du}-C_{dd}}{S_{du}-S_{dd}}=\frac{4.496861938-12.23871707}{40.50313806-32.76128293}=$

$\displaystyle \begin{aligned} B&=e^{-0.05(0.125)} \ \frac{u C_{dd}-d C_{du}}{u-d} \\&=e^{-0.00625} \ \frac{1.118866386 (12.23871707)-0.905003908 (4.496861938)}{1.118866386-0.905003908} \\&=- \$ 44.71962708 \end{aligned}$

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Binomial trees with more than two periods

Since one or two-period binomial trees are unlikely to be accurate model of stock price movements, option prices based on the binomial model with one or two periods are unlikely to be accurate. It is then necessary to use more periods in the binomial tree, i.e. divide the time to expiration into more periods to create more realistic model of stock price movements. Therefore realistic applications of the binomial option pricing model require the use of software.

Another point we would like to make is that using more periods in the binomial tree requires no new concepts or new methods. The same three steps described above are used – build the binomial tree, calculate the option values at expiration and work backward to derive the option price. The calculation at each node still uses the same one-period binomial option formulas. It is just that there are more periods to calculate. Hence realistic binomial option pricing is a job that should be done by software. To conclude this post, we present an example using a three-period binomial tree.

Example 3
Like Example 1 above, this example is based on Example 4 in this previous post. Example 4 in that post is to price a 6-month call option. In this example, we price the same call options using a 3-period binomial tree. All other specifics of the call option and the underlying stock remain the same. They are repeated here:

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%.

Now one period is 2-month long. Hence in the calculation $h=$ 2/12 = 0.16667. The results of the 3-period binomial calculation are show in the following two trees. The first one displays the stock prices and the option values. The second one displays the replicating portfolios (the hedge ratio $\Delta$ and the amount of borrowing $B$ ) at each node.

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

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Example 3 – Replicating portfolios
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$\displaystyle \begin{array}{llll} \displaystyle \text{Initial Price} & \text{Period 1} & \text{Period 2} & \text{Period 3} \\ \text{ } & \text{ } & \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \Delta=1 & \text{ } \\ \text{ } & \text{ } & B=-\$ 54.63456 & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \Delta=0.97364 & \text{ } & \text{ } \\ \text{ } & B=-\$ 52.23779 & \text{ } & \text{ } \\ \Delta=0.75168 & \text{ } & \Delta=0.94386 & \text{ } \\ B=-\$ 36.83749 & \text{ } & B=-\$ 50.77586 & \text{ } \\ \text{ } & \Delta=0.50079 \text{ } & \text{ } \\ \text{ } & B=-\$ 23.67681 \text{ } & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \Delta=0 & \text{ } \\ \text{ } & \text{ } & B=\$ 0 & \text{ } \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \text{ } & \text{ } & \text{ } & \text{N/A} \\ \end{array}$

$\text{ }$

The call option price using one-period tree in Example 4 in the previous post is $9.06302. The 3-period option price using a 3-period tree is $8.26318. Once again, there is no need to be alarmed. Binomial option prices can wildly fluctuate when the number of periods is small. The example here is only meant to illustrate the calculation in binomial option model.

Just to be clear on the process, the stock prices in the upper two nodes in the third period are calculated as follows:

$\displaystyle u=e^{(0.04-0) \frac{1}{6} + 0.3 \sqrt{\frac{1}{6}}}=$

$\displaystyle d=e^{(0.04-0) \frac{1}{6} - 0.3 \sqrt{\frac{1}{6}}}=$ 0.890646371

$\displaystyle S_{uuu}=S_{uu} \ u=$ 77.68225631 (1.137850725) = $88.39081165

$\displaystyle S_{uud}=S_{uu} \ d=$ 77.68225631 (0.890646371) = $69.18741967

The option value at the node $S_{uu}$ is calculated as follows using risk-neutral probabilities:

$\displaystyle p^*=\frac{e^{(0.05-0)0.25}-0.87153435}{1.176448318-0.87153435}=$ 0.462570155

$\displaystyle 1-p^*=$ 0.537429845

$C_u=e^{-0.05 (0.125)} [ p* (0)+(1-p^*)(4.496861938)]=$ $2.352809258

$C_d=e^{-0.05 (0.125)} [ p* (4.496861938)+(1-p^*)(12.23871707)]=$ $8.519470762

$C=e^{-0.05 (0.125)} [ p* (2.352809258)+(1-p^*)(8.519470762)]=$ $5.564617421

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Practice problems

For practice problems on how to calculate price of European option using multiperiod binomial tree, go here in the practice problem companion blog.

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

The binomial option pricing model – part 3

June 7, 2015 Leave a comment

This is post #3 on the binomial option pricing model. The previous two posts (post #1 and post #2) discuss the calculation and issues for the one-period binomial option pricing model. The purpose of post #3:

$\Delta$

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Hedging a short option position – two examples

Suppose that a market maker sells an option (on a stock). He is on the hook to sell (or buy) shares of the stock if the call (or put) buyer decides to exercise (i.e. when the share price of the underlying stock is above (or below) the strike price). He can hedge the risk of a short option position by creating a long synthetic option, i.e. creating a portfolio that replicates the same payoff of the option he sold. This replicating portfolio consists of $\Delta$ shares of the stock and an appropriate amount of lending or borrowing. The $\Delta$ is also called the hedge ratio and is the number of shares in the replicating portfolio to hedge away the risk from selling an option. Let’s discuss through two examples.

Example 1
Suppose that the future prices for a stock are modeled with a one-period binomial tree with $u=$ 1.3 and $d=$ 0.8 and having a period of 6 months. The current price of the stock is $50. The following is the binomial tree shows the future state of the stock prices.

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Figure 1 – Stock Price

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The stock pays no dividends. The annual risk-free interest rate is $r=$ 4%. Determine the price of a European 55-strike call option on this stock that will expire in 6 months. What is the replicating portfolio for this call option.

This is Example 1 in the post #1 on binomial model. At the end of 6 months, the stock price is either $65 or $40 and the value of the option is either $10 (if stock price goes up) or $0 (if price goes down). According to the calculation in the previous post, the replicating portfolio consists of holding $\Delta=$ 0.4 shares of the stock and $15.6832 in borrowing. The price of the call option is $C=50 \Delta+B=$ 50(0.4) – 15.6832 = $4.3168.

The market maker makes $4.3168 per call option sold. But the market maker is also at risk of losing $10 (selling a share at $55 for a share that is worth $65) when the call buyer decides to exercise. To hedge this risk, the market maker can buy a synthetic call option that replicates exactly the call option he sold.

In this example, the hedge ratio is $\Delta=$ 0.4, which is the ratio of the range of the values of the call to that of the stock across two possible outcomes. In this example, the calculation of $\Delta$ is:

$\displaystyle \Delta=\frac{10-0}{65-40}=$

For every call option written by the market maker, 0.4 shares of stock must be held to hedge away risk. The reason is that the strategy of holding 0.4 shares and the borrowing of $15.6832 has the same payoff as the call option as indicated by the following two equations. Note that $16.00 is the end of period value of $15.6832.

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$\displaystyle \text{ } \left\{\begin{matrix} \displaystyle 0.4 \times 40 - 16=0&\ \ \ \ \ \ \text{ }& \\ \text{ }&\text{ } \\ 0.4 \times 65 - 16=10&\ \ \ \ \ \ \text{ } \end{matrix}\right.$

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The above two equations show the payoff of the replicating portfolio of holding 0.4 shares and the borrowing of $15.6832, which is exactly the same as the payoff of the call option in the example. By selling a call option in this example, the market maker is at risk of losing $10 when the stock price goes up. He can offset the loss by creating a replicating portfolio that gains $10. So a market maker can hedge away the risk from selling a call by buying a synthetic call (the replicating portfolio).

Example 2
In Example 1, we see that the hedge ratio $\Delta$ is positive and is the number of stocks to hold to hedge away the risk of selling a call option. Now we consider $\Delta$ for put options. We analyze the put option in the Example 1 of the post #1 on binomial model. The characteristics of the stock are as in Example 1. The stock prices are modeled with the same 6-month binomial tree as in Example 1, which is repeated here:

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Figure 1 – Stock Price

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The stock pays no dividends. The annual risk-free interest rate is $r=$ 4%. Consider a European 45-strike put option on this stock that will expire in 6 months.

At the end of 6 months, the value of the option is either $0 (if stock price goes up) or $5 (if price goes down). According to the calculation in the previous post, the replicating portfolio consists of holding $\Delta=$ -0.2 shares of the stock and $12.74258275 in lending. The price of the call option is $C=50 \Delta+B=$ 50(-0.2) – 12.74258275 = $2.742582753.

The market maker makes $2.74258 per put option sold. But the market maker is also at risk of losing $5 (buying a share at $45 for a share that is worth only $40) when the put buyer decides to exercise. To hedge this risk, the market maker can buy a synthetic put option that replicates exactly the put option he sold.

In this example, the hedge ratio is $\Delta=$ -0.2, which is the ratio of the range of the values of the put to that of the stock across two possible outcomes. In this example, the calculation of $\Delta$ is:

$\displaystyle \Delta=\frac{0-5}{65-40}=$

The hedge ratio $\Delta$ is negative. So instead of buying stock, like in Example 1, the market maker holds a short position in the stock, i.e. enter into a short sale for the stock. This means that the market maker borrows the shares and sell the borrowed shares for cash. A short position is a bearish position, i.e. investor enters into a short position in the hope that the price of the asset will fall. In this example, the market maker uses a short stock position because the payoff of a short stock position is exactly opposite of the payoff of a short put, i.e. the loss experienced by the market maker in the short put position is exactly offset by the gain in the short stock position.

Back to the example. For every put option written by the market maker, 0.2 shares of stock must be sold short to hedge away risk. The reason is that the strategy of shorting 0.2 shares and the lending of $12.74258 has the same payoff as the put option as indicated by the following two equations. Note that $13.00 is the end of period value of $12.74258.

$\text{ }$

$\displaystyle \text{ } \left\{\begin{matrix} \displaystyle -0.2 \times 40 + 13=5&\ \ \ \ \ \ \text{ }& \\ \text{ }&\text{ } \\ -0.2 \times 65 + 13=0&\ \ \ \ \ \ \text{ } \end{matrix}\right.$

$\text{ }$

The above two equations show the payoff of the replicating portfolio of shorting 0.2 shares and the lending of $12.74258, which is exactly the same as the payoff of the put option in the example. By selling a put option in this example, the market maker is at risk of losing $5 when the stock price goes down. He can offset the loss by creating a replicating portfolio that gains $5. So a market maker can hedge away the risk from selling a put by buying a synthetic put (the replicating portfolio).

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To further examine $\Delta$

Here’s the observation from the above two examples. From the perspective of a market maker, the hedge ration $\Delta$ is the number of shares of stock required to hedge the price risk from selling an option. When selling a call option, the hedge ratio is positive, indicating that the marker maker is to hedge away the risk of a short call by going long on $\Delta$ shares of stock with an appropriate amount in borrowing. When selling a put option, the hedge ratio is negative, indicating that the marker maker is to hedge away the risk of a short put by going short on $\Delta$ shares of stock with an appropriate amount in lending.

The initial stock price in Example 1 and Example 2 is $50. In Example 1, the strike price of the call option is $55. Given the price position, there is no incentive for the call option buyer to exercise when the stock price is $50. The strike price of the put option in Example 2 is $45. So there is no incentive for the put option buyer to exercise when the stock price is $50. In other words, both options are out of the money. When can we say about the hedge ratio $\Delta$ when the options are increasingly in the money? For the call option in Example 1, what if the initial stock price is not $50 but is higher, say $55, $60, $65, or $70? For these higher initial stock prices, the option will have an increasingly greater chance of being in the money. What can we say about $\Delta$ ? We examine these scenarios in Example 3. In Example 4, we will examine similar scenarios for the put option in Example 2.

Example 3
For the call option in Example 1, determine the replication portfolio and calculate the price of the call option as the initial stock price varies from $50, $55, $60, $65, to $70. The results are in the following table.

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Table 1 – Call option hedge ratio when initial stock prices are increasing

$\left[\begin{array}{lllllllll} \text{Call Option} \\ \text{Strike Price} & \text{ } & \text{Initial Stock Price} & \text{ } & \text{Option Price} & \text{ } & \text{Hedge Ratio } \Delta & \text{ } & \text{Borrowing} \\ \text{ } & \text{ } \\ \$ 55 & \text{ } & \$ 50 & \text{ } & \$ 4.3168 & \text{ } & 0.4 & \text{ } & \$ 15.6832 \\ \$ 55 & \text{ } & \$ 55 & \text{ } & \$ 7.1228 & \text{ } & 0.6 & \text{ } & \$ 25.8772 \\ \$ 55 & \text{ } & \$ 60 & \text{ } & \$ 9.9287 & \text{ } & 0.7667 & \text{ } & \$ 36.0713 \\ \$ 55 & \text{ } & \$ 65 & \text{ } & \$ 12.7346 & \text{ } & 0.9077 & \text{ } & \$ 46.2654 \\ \$ 55 & \text{ } & \$ 70 & \text{ } & \$ 16.0891 & \text{ } & 1.000 & \text{ } & \$ 53.9109 \\ \end{array}\right]$
$\text{ }$

In Table 1, the initial stock prices are increasingly higher than the strike price. This means that the call option is increasingly in the money. As a result, the hedge ratio is increasingly becoming 1.0. To explain this phenomenon, let’s take the point of view of a market maker. Suppose that a market maker has sold a 55-strike call option. If the initial stock price is much higher than the strike price, it is much more likely that the option will finishes in the money. The market maker must then buy more shares initially in order to be able to cover the obligation of the short call position at expiration. Thus the hedge ratio $\Delta$ increases as the initial stock price increases. When $\Delta$ is 1, the option is all but certain to expire in the money that the market maker has to hedge by holding one share for one option.

Example 4
For the put option in Example 2, determine the replication portfolio and calculate the price of the put option as the initial stock price varies from $50, $45, $40, $35, to $30. The results are in the following table.

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Table 2 – Put option hedge ratio when initial stock prices are decreasing

$\left[\begin{array}{lllllllll} \text{Put Option} \\ \text{Strike Price} & \text{ } & \text{Initial Stock Price} & \text{ } & \text{Option Price} & \text{ } & \text{Hedge Ratio } \Delta & \text{ } & \text{Lending} \\ \text{ } & \text{ } \\ \$ 45 & \text{ } & \$ 50 & \text{ } & \$ 2.7426 & \text{ } & -0.2 & \text{ } & \$ 12.7426 \\ \$ 45 & \text{ } & \$ 45 & \text{ } & \$ 4.9366 & \text{ } & -0.4 & \text{ } & \$ 22.9366 \\ \$ 45 & \text{ } & \$ 40 & \text{ } & \$ 7.1307 & \text{ } & -0.65 & \text{ } & \$ 33.1307 \\ \$ 45 & \text{ } & \$ 35 & \text{ } & \$ 9.3248 & \text{ } & -0.9714 & \text{ } & \$ 43.3248 \\ \$ 45 & \text{ } & \$ 30 & \text{ } & \$ 14.1089 & \text{ } & -1.0000 & \text{ } & \$ 44.1089 \\ \end{array}\right]$
$\text{ }$

In Table 2, the movement goes in the opposite direction. The initial stock prices are decreasingly lower than the strike price. This means that the put option is increasingly in the money. As a result, the hedge ratio is increasingly becoming -1.0. To explain this phenomenon, we again take the point of view of a market maker. Suppose that a market maker has sold a 45-strike put option. If the initial stock price is much lower than the strike price, it is much more likely that the put option will finish in the money. The market maker must then short more shares initially in order to be able to cover the obligation of the short put position at expiration. Thus the hedge ratio $\Delta$ decreases as the initial stock price decreases. When $\Delta$ is -1, the put option is all but certain to expire in the money that the market maker has to hedge by shorting one share for one option.

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Remarks

The discussion of $\Delta$ in this post is from a market maker’s point of view. It is the number of shares a market maker needs to buy or short in order to cover the obligation of a short option position. When the initial price is sufficiently far from the strike price (when the option is extremely likely to expire in the money), the market maker must buy or short the stock on a one share to one option basis.

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Practice problems

Practice problems for this post are found in here.

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

The binomial option pricing model – part 2

June 4, 2015 Leave a comment

This is post #2 on the binomial option pricing model. In part 1, we derive the one-period binomial option pricing formulas. The purpose of post #2:

Post #2: Discuss the underlying issues in the one-period model – e.g. arbitrage in the binomial tree and risk-neutral pricing.

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The one-period binomial option pricing formulas

For easier reference, we list out the option pricing formulas derived in part 1. The binomial tree models the stock price at expiration of the option.

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Figure 1 – binomial tree

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The following is a tree showing the value of the option at expiration.

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Figure 2 – option value tree

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Replicating Portfolio

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$\displaystyle \Delta=e^{-\delta h} \ \frac{C_u-C_d}{S(u-d)} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)$

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$\displaystyle B=e^{-r h} \ \frac{u \ C_d-d \ C_u}{u-d} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)$
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Price of the Option

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$C=\Delta S + B \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)$

$\text{ }$

$\displaystyle C=\Delta S + B=e^{-r h} \biggl(C_u \ \frac{e^{(r-\delta) h}-d}{u-d} +C_d \ \frac{u-e^{(r-\delta) h}}{u-d} \biggr) \ \ \ \ \ \ \ \ \ (4)$

$\text{ }$

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Arbitrage in the binomial tree

In formulas (1), (2) and (4), it seems that we choose the up factor $u$ and the down factor $d$ arbitrarily. It turns out that the assumed stock price factors $u$ and $d$ should be set in such a way that arbitrage opportunities are not possible. The factors $u$ and $d$ must follow the following relationship.

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$\displaystyle d < e^{(r-\delta) h} < u \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (5)$

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Multiplying (5) by the initial stock price $S$ yields the following:

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$\displaystyle dS < Se^{(r-\delta) h} < uS \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (6)$

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The middle term in (6) is the forward price on the stock. The relationship (6) indicates that whatever the values of the up factor $u$ and the down factor $d$ are, the end of period upped stock price must be larger than the forward price and the downed stock price must be below the forward price. Violation of this requirement will yield arbitrage opportunities.

To see that arbitrage opportunities will arise if (5) is violated, suppose that $e^{(r-\delta) h} > u$ . Multiply by the initial stock price produces $Se^{(r-\delta) h} > Su$ . Since $Su > Sd$ , we have the following:

$Se^{(r-\delta) h} > Su > Sd \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (a)$

Based on the above inequality (a), the arbitrage opportunity: short $e^{-\delta h}$ shares of stock (borrow that many shares and sell) and lend $Se^{-\delta h}$ (the short sales proceeds). At time $h$ , you need to buy back 1 share at price $S_h$ . The value of the bond is $Se^{-\delta h} e^{r h}=S e^{(r-\delta) h}$ . What occurs at time $h$ is that you pay $S_h$ to buy back 1 share and receive $S e^{(r-\delta) h}$ . Based on (a), both $Se^{(r-\delta) h} - Su > 0$ and $Se^{(r-\delta) h} - Sd > 0$ , which mean risk-free profit. So it must be the case that $e^{(r-\delta) h} < u$ .

Suppose that $e^{(r-\delta) h} < d$ . This also leads to arbitrage opportunities. Multiplying by the initial stock price produces the following:

$Se^{(r-\delta) h} < Sd < Su \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (b)$

The arbitrage opportunity: borrow $Se^{-\delta h}$ at the risk-free rate and use the borrowed fund to buy $e^{-\delta h}$ shares of stock. The relationship (b) says that regardless of the stock price at time $h$ (up or down), the stock price is always greater than the amount that has to be repaid. Thus there are risk-free profits in either case: $0 < Sd - Se^{(r-\delta) h}$ and $0 < Su - Se^{(r-\delta) h}$ .

Thus relationship (5) must hold for the stock price movement factors $u$ and $d$ . In fact, one way to set the factors $u$ and $d$ is to increase or decrease a volatility adjustment to the risk-free return factor $e^{(r-\delta) h}$ . The resulting $u$ and $d$ are:

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

$\displaystyle d = e^{(r-\delta) h \ - \ \sigma \sqrt{h}} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (7)$

For more information about (7), see part 1.

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Risk-neutral pricing

At first glance, the pricing of an option on stock ought to require the use of a probability model. The price of the option depends on the price of the stock at expiration of the European option. The stock price at the end of the option period is uncertain. Thus to price the option, we need to find a way to characterize the uncertainty of the stock prices at expiration. Since the future stock prices are random, it is natural to think that we need a probability model to describe the uncertain stock prices. The above derivation of the binomial option pricing model shows that probabilities of the future stock prices are not necessary. All we use is the binomial assumption of stock prices. The trick is then to determine a replicating portfolio of holding $\Delta$ shares and lending a dollar amount $B$ . Because the replicating portfolio has the same payoff as the option, the movement of the stock prices (the up and the down prices) is irrelevant to the calculation of the price of the option.

However, there is a probabilistic interpretation of the option price in (4). Note that the terms $\displaystyle \frac{e^{(r-\delta) h}-d}{u-d}$ and $\displaystyle \frac{u-e^{(r-\delta) h}}{u-d}$ in formula (4) sum to 1.0. The two terms are also positive because of relationship (5). So they can be interpret as probabilities. So we have:

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

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

Then pricing formula (4) becomes:

$\text{ }$

$\displaystyle C=\Delta S + B=e^{-r h} \biggl(p^* \ C_u +(1-p^*) \ C_d \biggr) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (5)$

$\text{ }$

The formula $p^*$ is called the risk-neutral probability. From a calculation standpoint, the risk-neutral probability is another way to calculate the price of an option in the one-period binomial model. Simply calculate the risk-neutral probabilities. Then use them to weight the option values $C_u$ and $C_d$ (and also discount to time 0).

If $p^*$ and $1-p^*$ are interpreted as probabilities, then the pricing formula (5) says that the price of an option is the expected value of the end of period options values discounted at the risk-free rate. On the other hand, let’s use $p^*$ and $1-p^*$ to compute the expected value of the stock prices.

$\text{ }$

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

$\text{ }$

The last term in the above derivation is $e^{(r-\delta) h}$ , which is the forward price on a stock that pays continuous dividends (derived in this previous post). Thus if we use $p^*$ and $1-p^*$ to calculated the expected value of the stock prices, we get the forward price. This is why $p^*$ and $1-p^*$ are called risk-neutral probabilities since they are the probabilities for which the expected value of the stock prices is the forward price. In particular, $p^*$ is the risk-neutral probability of an increase in the stock price.

We conclude this post with an example on using risk-neutral probabilities to compute option prices. This example is Example 3 in part 1.

Example 1
Suppose that the future prices for a stock are modeled with a one-period binomial tree with volatility $\sigma=$ 30% and having a period of 6 months. The current price of the stock is $60. The stock pays no dividends. The annual risk-free interest rate is $r=$ 4%. Use risk-neutral probabilities to price the following options.

A European 60-strike call option on this stock that will expire in 6 months.
A European 60-strike put option on this stock that will expire in 6 months.

First calculate the $u$ and $d$ , and the stock prices at expiration:

$\displaystyle u = e^{(0.04-0) 0.5 \ + \ 0.3 \sqrt{0.5}}=$ 1.261286251

$\displaystyle d = e^{(0.04-0) 0.5 \ - \ 0.3 \sqrt{0.5}}=$ 0.825197907

$\displaystyle uS =$ 60 (1.261286251) = $75.67717506

$\displaystyle dS =$ 60 (0.825197907) = $49.51187441

Now the risk-neutral probabilities:

$\displaystyle p^*=\frac{e^{(0.04-0) 0.5}-0.825197907}{1.261286251-0.825197907}=$

$\displaystyle 1-p^*=\frac{1.261286251-e^{(0.04-0) 0.5}}{1.261286251-0.825197907}=$ 0.552835026

Then the option prices are:

$C=e^{-0.04(0.5)} [0.447164974 (15.67717506) + 0.825197907(0)]=$

$P=e^{-0.04(0.5)} [0.447164974 (0) + 0.825197907(10.48812559)]=$ $5.683391065 (put)

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Practice Problems

Practice problems can be found in in this blog post in a companion blog.

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

The binomial option pricing model – part 1

June 4, 2015 Leave a comment

This is post #1 on the binomial option pricing model. Even though this is post #1, there are two previous posts with examples to illustrate how to price options using the one-period binomial pricing model (example of call and example of put). The purpose of post #1:

Post #1: Describe the option pricing formulas in the one-period binomial model.

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The one-period binomial option pricing model

We first consider the pricing of options on stock. The most important characteristic of the binomial option pricing model is that over a period of time, the stock price is assumed to follow a binomial distribution, i.e. the price of the stock can only take on one of two values – an upped value and a downed value. In this post, we describe how to price an option on a stock using this simplifying assumption of stock price movement.

Consider a stock with the following characteristics:

The current share price is $S$ .
If the stock pays dividends, we assume the dividends are paid at an annual continuous rate at $\delta$ .
At the end of a period of length $h$ (in years), the share price is either $S_h=uS$ or $S_h=dS$ , where $u$ is the up factor and $d$ is the down factor. The factor $u$ can be interpreted as one plus the rate of capital gain on the stock if the stock goes up. The factor $d$ can be interpreted as one plus the rate of capital loss if the stock goes down.
If $\delta>0$ , the end of period share price is $S_h=uS e^{\delta h}$ or $S_h=dS e^{\delta h}$ . This is to reflect the gains from reinvesting the dividends. Of course if $\delta=0$ , the share prices revert back to the previous bullet point.

The end of period stock prices are shown in the following diagram, which is called a binomial tree since it depicts the 2-state stock price at the end of the option period.

$\text{ }$

Figure 1 – binomial tree

$\text{ }$

Now consider a European option (either call or put) on the stock described above. When the stock goes up, we use $C_u$ to represent the value of the option. When the stock goes down, we use $C_d$ to represent the value of the option. The following is the binomial tree for the value of the option.

$\text{ }$

Figure 2 – option value tree

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Replicating Portfolio
The key idea to price the option is to create a portfolio consisting of $\Delta$ shares of the stock and the amount $B$ in lending. At time 0, the value of this portfolio is $C=\Delta S + B$ . At time $h$ (the end of the option period), the value of the portfolio is

$\text{ }$

Time $h$ value of the replicating portfolio

$\displaystyle \text{ } \left\{\begin{matrix} \displaystyle \Delta \times (dS \ e^{\delta h}) + B \ e^{r h}&\ \ \ \ \ \ \text{(when stock price goes down)}& \\ \text{ }&\text{ } \\ \Delta \times (uS \ e^{\delta h}) + B \ e^{r h}&\ \ \ \ \ \ \text{(when stock price goes up)} \end{matrix}\right.$

$\text{ }$

This portfolio is supposed to replicate the same payoff as the value of the option. By equating the portfolio payoff with the option payoff, we obtain the following linear equations.

$\text{ }$

There are two unknowns in the above two equations. All the other items – stock price $S$ , dividend rate $\delta$ , and risk-free interest rate $r$ – are known. Solving for the two unknowns $\Delta$ and $B$ , we obtain:

$\text{ }$

$\displaystyle \Delta=e^{-\delta h} \ \frac{C_u-C_d}{S(u-d)} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)$

$\text{ }$

$\displaystyle B=e^{-r h} \ \frac{u \ C_d-d \ C_u}{u-d} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)$
$\text{ }$

Once the replication portfolio of $\Delta$ shares and $B$ in lending is determined, the price of the option (the value at time 0) is:

$\text{ }$

$C=\Delta S + B \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)$

$\text{ }$

After plugging in (1) and (2) into (3), the option price formula becomes:

$\text{ }$

$\displaystyle C=\Delta S + B=e^{-r h} \biggl(C_u \ \frac{e^{(r-\delta) h}-d}{u-d} +C_d \ \frac{u-e^{(r-\delta) h}}{u-d} \biggr) \ \ \ \ \ \ \ \ \ (4)$

$\text{ }$

The price of the option described above is $C$ , either given by formula (3) or formula (4). One advantage of formula (4) is that it gives the direct calculation of the option price without knowing $\Delta$ and $B$ . Of course, if the goal is to create a synthetic option for the purpose of hedging or risk management, it will be necessary to know the make up of the replicating portfolio.

The $\Delta$ calculated in (1) is also called the hedge ratio and is examined in greater details in in this subsequent post.

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Examples

Example 1
Let’s walk through a quick example to demonstrate how to apply the above formulas. Suppose that the future prices for a stock are modeled with a one-period binomial tree with $u=$ 1.3 and $d=$ 0.8 and having a period of 6 months. The current price of the stock is $50. The stock pays no dividends. The annual risk-free interest rate is $r=$ 4%.

Determine the price of a European 55-strike call option on this stock that will expire in 6 months.
Determine the price of a European 45-strike put option on this stock that will expire in 6 months.

The two-state stock prices are $65 and $40. The two-state call option values at expiration are $10 and $0. Apply (1) and (2) to obtain the replicating portfolio and then the price of the call option.

$\text{ }$

$\displaystyle \Delta=\frac{10-0}{65-40}=\frac{10}{25}=$

$\displaystyle B=e^{-0.04(0.5)} \ \frac{1.3(0)-0.8(10)}{1.3-0.8}=-16 e^{-0.02}=$ -$15.68317877

The replicating portfolio consists of holding 0.4 shares and borrowing $15.68317877.

Call option price = $50 \Delta+B=$ $4.316821227

$\text{ }$

The 2-state put option values at expiration are $0 and $5. Now apply (1) and (2) and obtain:

$\text{ }$

$\displaystyle \Delta=\frac{0-5}{65-40}=\frac{-5}{25}=-0.2$

$\displaystyle B=e^{-0.04(0.5)} \ \frac{1.3(5)-0.8(0)}{1.3-0.8}=13 e^{-0.02}=$ $12.74258275

The replicating portfolio consists of shorting 0.2 shares and lending $12.74258275.

Put option price = $50 \Delta+B=$ $2.742582753

$\text{ }$

Example 1 is examined in greater details in this subsequent post.

More Examples
Two more examples are in these previous posts:

example of call

example of put

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What to do if options are mispriced

What if the observed price of an option is not the same as the theoretical price? In other words, what if the price of a European option is not given by the above formulas? Because we can always hold stock and lend to replicate the payoff of an option, we can participate in arbitrage when an option is mispriced by buying low and selling high. The idea is that if an option is underpriced, then we buy low (the underpriced option) and sell high (the corresponding synthetic option, i.e. the replicating portfolio). On the other hand, if an option is overpriced, then we buy low (the synthetic option) and sell high (the overpriced option). Either case presents risk-free profit. We demonstrate with the options in Example 1.

Example 2

Suppose that the price of the call option in Example 1 is observed to be $4.00. Describe the arbitrage.
Suppose that the price of the call option in Example 1 is observed to be $4.60. Describe the arbitrage.

For the first scenario, we buy low (the option at $4.00) and sell the synthetic option at the theoretical price of $4.316821227. Let’s analyze the cash flows in the following table.

$\text{ }$

Table 1 – Arbitrage opportunity when call option is underpriced

$\left[\begin{array}{llll} \text{Expiration Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Sell synthetic call} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Short 0.4 shares} & \text{ } & - \$ 16 & - \$ 26 \\ \ \ \ \ \text{Lend } \$ 15.683 & \text{ } & + \$ 16 & + \$ 16 \\ \text{ } & \text{ } \\ \text{Buy call } & \text{ } & \ \ \$ 0 & \ \ \$ 10 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

$\text{ }$

The above table shows that the buy low sell high strategy produces no loss at expiration of the option regardless of the share prices at the end of the option period. But the payoff at time 0 is certain: $4.316821227 – $4.00 = $0.316821227.

For the second scenario, we still buy low and sell high. This time, buy low (the synthetic call option at $4.316821227) and sell high (the call option at the observed price of $4.60). Let’s analyze the cash flows in the following table.

$\text{ }$

Table 2 – Arbitrage opportunity when call option is overpriced

$\left[\begin{array}{llll} \text{Expiration Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Buy synthetic call} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Long 0.4 shares} & \text{ } & + \$ 16 & + \$ 26 \\ \ \ \ \ \text{Borrow } \$ 15.683 & \text{ } & - \$ 16 & - \$ 16 \\ \text{ } & \text{ } \\ \text{Buy call } & \text{ } & \ \ \$ 0 & - \$ 10 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

$\text{ }$

These two examples show that if the option price is anything other than the theoretical price, there are arbitrage opportunities and there is risk-free profit to be made.

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How to construct a binomial tree

In the binomial tree in Figure 1, we assume that the share price at expiration is obtained by multiplying the original share price by the movement factors of $u$ and $d$ . The binomial tree in Figure 1 may give the impression that the choice of the movement factors $u$ and $d$ is arbitrary as long as the up factor is greater than 1 and the down factor is below 1. In the next post, we show that $u$ and $d$ have to satisfy the following relation, else there will be arbitrage opportunities.

$\displaystyle d < e^{(r-\delta) h} < u \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (5)$

Thus the choice of $u$ and $d$ cannot be entirely arbitrary. In particular the relation (5) shows that the future stock prices have to revolve around the forward price.

$\displaystyle dS < Se^{(r-\delta) h} < uS \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (6)$

The purpose pf the factors $u$ and $d$ in the binomial tree is to incorporate uncertainty of the stock prices. In light of (6), we can set $u$ and $d$ by applying some volatility adjustment to $e^{(r-\delta) h}$ . We can use the following choice of $u$ and $d$ to model the stock price evolution.

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

$\displaystyle d = e^{(r-\delta) h \ - \ \sigma \sqrt{h}} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (7)$

where

$\sigma$ is the annualized standard deviation of the continuously compounded stock return,

$\sigma \sqrt{h}$ is the standard deviation of the continuously compounded stock return over a period of length $h$ .

The standard deviation $\sigma$ measures how certain we are that the stock return will be close to the expected return. There will be a greater chance of a return far from the expected return if the stock has a higher $\sigma$ . If $\sigma=0$ , then there is no uncertainty about the future stock prices. The formula (7) shows that when $\sigma=0$ , the future stock price is precisely the forward price on the stock. When the binomial tree is constructed using (7), the tree will be called a forward tree.

A note on calculation. If a problem does not specific $u$ and $d$ but assume a standard deviation of stock return $\sigma$ , then assume that the binomial tree is the forward tree. We now use a quick example to demonstrate how to price an option using the forward tree.

Example 3
Everything is the same as Example 1 except that the up and down stock prices are constructed using the volatility $\sigma=$ 30% (the standard deviation $\sigma$ ). The following calculates the stock prices at expiration of the option.

$\displaystyle uS = 50 \ e^{(0.04-0) 0.5 \ + \ 0.3 \sqrt{0.5}}=$

$\displaystyle dS = 50 \ e^{(0.04-0) 0.5 \ - \ 0.3 \sqrt{0.5}}=$ $41.25989534

$\displaystyle u=\frac{63.06431255}{50}=$ 1.261286251

$\displaystyle d=\frac{41.25989534}{50}=$ 0.825197907

Using formulas (1), (2) and (3), the following shows the replicating portfolio and the call option price. Note that the binomial tree is based on a different assumption than that in Example 1. The option price is thus different than the one in Example 1.

$\text{ }$

$\displaystyle \Delta=\frac{8.064312548-0}{63.06431255-41.25989534}=$ 0.369847654

$\displaystyle B=e^{-0.04(0.5)} \ \frac{1.261286251(0)-0.825197907(8.064312548)}{1.261286251-0.825197907}=$ –$14.95770971

The replicating portfolio consists of holding 0.369847654 shares and borrowing $14.95770971.

Call option price = $50 \Delta+B=$ $3.534672982

$\text{ }$

The following shows the calculation for the put option.

$\text{ }$

$\displaystyle \Delta=\frac{0-3.740104659}{63.06431255-41.25989534}=$

$\displaystyle B=e^{-0.04(0.5)} \ \frac{1.261286251(3.740104659)-0.825197907(0)}{1.261286251-0.825197907}=$ $10.60320232

The replicating portfolio consists of shorting 0.171529678 shares and lending $10.60320232.

Put option price = $50 \Delta+B=$ $2.026718427

$\text{ }$

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More examples

We present two more examples in illustrating the calculation in the one-period binomial option model where the stock prices are modeled by a forward tree.

Example 4
The stock price follows a 6-month binomial tree with initial stock price $60 and $\sigma=$ 0.3. The stock is non-dividend paying. The annual risk free interest rate is $r=$ 4%. What is the price of a 6-month 55-strike call option? Determine the replicating portfolio that has the same payoff as this call option.

We will use risk-neutral probabilities to price the option.

$\displaystyle uS = 60 \ e^{(0.04-0) 0.5 \ + \ 0.3 \sqrt{0.5}}=$

$\displaystyle dS = 60 \ e^{(0.04-0) 0.5 \ - \ 0.3 \sqrt{0.5}}=$ $49.51187441

$\displaystyle C_u=$ 75.67717506 – 55 = 20.67717506

$\displaystyle C_d=$ 0

$\displaystyle u=\frac{75.67717506}{60}=$ 1.261286251

$\displaystyle d=\frac{49.51187441}{60}=$ 0.825197907

$\displaystyle p^*=\frac{e^{(0.04-0) 0.5} - 0.825197907}{1.261286251 - 0.825197907}=$ 0.447164974

$\displaystyle 1-p^*=$ 0.552835026

$\displaystyle C=(p^* \times C_u + (1-p^*) \times C_d) e^{-0.02}=$ 9.063023234

$\text{ }$

$\displaystyle \Delta=\frac{20.67717506-0}{75.67717506-49.51187441}=$ 0.790251766

$\displaystyle B=e^{-0.04(0.5)} \ \frac{1.261286251(0)-0.825197907(20.67717506)}{1.261286251-0.825197907}=$ –$38.35208275

The replicating portfolio consists of holding 0.79025 shares and borrowing $38.352.

$\text{ }$

Example 5
The stock price follows a 3-month binomial tree with initial stock price $40 and $\sigma=$ 0.3. The stock is non-dividend paying. The annual risk free interest rate is $r=$ 5%. What is the price of a 3-month 45-strike put option on this stock? Determine the replicating portfolio that has the same payoff as this put option.

The calculation is calculated as in Example 3.

$\displaystyle uS = 40 \ e^{(0.05-0) 0.25 \ + \ 0.3 \sqrt{0.25}}=$

$\displaystyle dS = 40 \ e^{(0.05-0) 0.25 \ - \ 0.3 \sqrt{0.25}}=$ $34.861374

$\displaystyle C_u=$ 0

$\displaystyle C_d=$ 45 – 34.861374 = $10.138626

$\displaystyle u=\frac{47.05793274}{40}=$ 1.176448318

$\displaystyle d=\frac{34.861374}{40}=$ 0.87153435

$\displaystyle p^*=\frac{e^{(0.05-0) 0.25} - 0.87153435}{1.176448318 - 0.87153435}=$ 0.462570155

$\displaystyle 1-p^*=$ 0.537429845

$\displaystyle C=(p^* \times C_u + (1-p^*) \times C_d) e^{-0.0125}=$ 5.381114117

$\text{ }$

$\displaystyle \Delta=\frac{0-10.138626}{47.05793274-34.861374}=$

$\displaystyle B=e^{-0.05(0.25)} \ \frac{1.176448318(10.138626)-0.87153435(0)}{1.176448318 - 0.87153435}=$ $38.63188995

The replicating portfolio consists of shorting 0.831269395 shares and lending $38.63188995.

$\text{ }$

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Remarks

The discussion in this post is only the beginning of the binomial pricing model. The concepts and the formulas for the one-period binomial option model are very important. The one-period model may seem overly simplistic (or even unrealistic). One way to make it more realistic is to break up the one-period into multiple smaller periods and thus produce a more accurate option price. The calculation for the multi-period binomial model is still based on the calculation for the one-period model. Before moving to the multi-period model, we discuss the one-period model in greater details to gain more understanding of the one-period model.

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Practice problems

Practice Problems
Practice problems can be found in the companion problem blog via the following links:

Practice problem for pricing call

Practice problem for pricing put

basic problem set 1

basic problem set 2

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

Pricing a put option – an example

May 25, 2015 Leave a comment

This post is a continuation of the example discussed in this previous post, which gives an example to illustrate the pricing of a call option using the binomial option pricing model. This post illustrates the pricing of a put option. Links to practice problems are found at the bottom of the post.

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The example

The following gives the information about the stock:

The stock of XYZ company is currently selling for $50 per share. The price per share 1 year from now is expected to increase to $65 or to decrease to $40. The stock pays no dividends.

Consider a put option with the following specifics:

The underlying asset of the put option is the XYZ stock.
The strike price is $55.
The option will expire in one year.
The option is assumed to be a European option, i.e. it can be exercised only at expiration.

The annual risk-free interest rate is 2%. There is a benefit to the buyer of the option described above. If the price of the stock goes down to $40 at the end of the 1-year period, the buyer of the put option has the right to sell a share of XYZ for $55 ($15 higher than the market price). If the price of the stock goes up to $65 at the end of the 1-year period, exercising the option would mean selling a share at $55 which is $10 below the market price, but the put option owner can simply walk away. The put option owner sells the stock only when he makes money. What would be the fair price of having this privilege? What is the fair price of this put option?

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Pricing the put option

In this example, the current stock price is $50 and the stock price can be only one of the two possible values at the end of the option contract period (either $65 or $40). The following diagram shows the future state of the stock prices.

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Figure 1 – Stock Price

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The assumption of the 2-state stock prices in 1 year simplifies the analysis of the put option. The value of the put option at the end of 1 year is either zero or $15 (=55-40). Note that when the share price at the end of the 1-year contract period is higher than the strike price of $55, the put option expires worthless. The following diagram shows the value of the put option.

$\text{ }$

Figure 2 – Put Option Payoff

$\text{ }$

In the above diagram, the value of the put option at the end of 1-year is either $0 or $15. The value of the option at time 0 is $C$ , which is the premium of the put option in this example. Our job here is to calculate $C$ . The key to finding the value of the option is to compare the payoff of the put to that of a portfolio consisting of the following investments:

Portfolio B

Short 0.6 shares of XYZ.
Lend $38.2277 at the risk-free rate.

The idea for setting up this portfolio is given below. For the time being, we take the 0.6 shares and the lending of $38.2277 as a given. Note that $38.2277 is the present value of $39 at the risk-free rate of 2%. Let’s calculate the value of Portfolio B at time 0 and at time 1 (1 year from now). The following diagram shows the calculation.

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Figure 3 – Portfolio B Payoff

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Note that the payoff of the put option is identical to the payoff of Portfolio B. Thus the put option in this example and Portfolio B must have the same cost. Since Portfolio B costs $8.2277, the price of the option must be $8.2277. The Portfolio B of 0.6 shares of stock in short sales and $15.683 in lending is a synthetic put since it mimics the put option described in the example. Portfolio B is called a replicating portfolio because it replicates the payoff of the put option in question.

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Arbitrage opportunities

In deriving the cost of the put option of $8.2277, we rely on the idea that if two investments have the same payoff, they must have the same cost. This idea is called the law of one price, which is a commonsensical idea and is also an important principle in derivative pricing. If the law of one price is violated, in particular if the price of the put option discussed here is not $8.2277, there would be arbitrage opportunities that can be exploited to gain risk-free profit.

What if the law of one price is violated? For example, what if the option were selling for a higher price (say $8.50)? If the price of the replicating portfolio is less than the price of the option, then we can “buy low and sell high” (i.e. buy the replicating portfolio and sell put option) and obtain a risk-free profit of $0.2723. The arbitrage is to buy the synthetic call (Portfolio B) at $8.2277 and sell the put option at $8.50. The following table shows the Year 1 cash flows of this arbitrage opportunity.

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Table 1 – Arbitrage opportunity when put option is overpriced

$\left[\begin{array}{llll} \text{Year 1 Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Long synthetic put} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Short 0.6 shares} & \text{ } & - \$ 24 & - \$ 39 \\ \ \ \ \ \text{Receive the lending of } \$ 38.2277 & \text{ } & + \$ 39 & + \$ 39 \\ \text{ } & \text{ } \\ \text{Short put } & \text{ } & - \$ 15 & \ \ \$ 0 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

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The above table shows that buying a synthetic put (shorting 0.6 shares and lending $38.2277) and selling a put will have no loss at the end of 1 year. Yet, the time 0 cash flow is $0.2723 (=8.50 – 8.2277), and is thus a risk-less profit.

If the option is underpriced, then we can still buy low and sell high (in this case, buy put option and sell the replicating portfolio) and obtain risk-free arbitrage profit. For example, let’s say you observe a put option price of $8.00. Then the arbitrage opportunity is to buy the put option at $8.00 and sell a synthetic put (Portfolio B) at $8.2277. The time 0 payoff is $0.2723, which is a risk-less arbitrage profit. The following table shows the Year 1 cash flows.

$\text{ }$

Table 2 – Arbitrage opportunity when put option is underpriced

$\left[\begin{array}{llll} \text{Year 1 Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Short synthetic put} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Long 0.6 shares} & \text{ } & + \$ 24 & + \$ 39 \\ \ \ \ \ \text{Repay the borrowing of } \$38.2277 & \text{ } & - \$ 39 & - \$ 39 \\ \text{ } & \text{ } \\ \text{Long put } & \text{ } & \ \ \$ 15 & + \$ 0 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

$\text{ }$

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To complete the picture

The put option price of $8.2277 is derived by showing that the replicating portfolio has the same payoff as the put option. How do we know that the replicating portfolio consists of shorting 0.6 shares and lending of $38.2277?

In general, the replicating portfolio of a European option consists of $\Delta$ shares of the stock and the amount $B$ in lending at time 0 (borrowing if negative). By equating the payoff of the replicating portfolio and the payoff of the put option in this example, we have the following equations:

$\text{ }$

$\displaystyle \begin{array}{ccc} \displaystyle 40 \ \Delta + B \ e^{0.02} & = & 15 \\ \displaystyle 65 \ \Delta + B \ e^{0.02} & = & 0 \end{array}$

$\text{ }$

Solving these two equations, we obtain $\Delta=\frac{-15}{25}=-0.6$ and $B=39 \ e^{-0.02}=38.2277$ . Therefore, the replicating portfolio for the put option in this example consists of shorting 0.6 shares of the stock and $38.2277 in lending. The net investment for the replicating portfolio is $8.2277 (=-0.6(50)+38.2277). Because there are only two data points in the future stock prices, the option premium is a linear function of $\Delta$ and $B$ . The following is the premium of the call (or put) option using the one-period binomial tree

$C=\Delta \ S+B$

where $S$ is the stock price at expiration. The above formula gives the cost of the portfolio replicating the payoff of a given option. It works for call option as well as for put option. The above example shows that for put options, $\Delta$ is negative and $B$ is positive (i.e. shorting stock and lending replicate the payoff of a put). The number $\Delta$ has a special interpretation that will be important in subsequent discussion of option pricing. It can be interpreted as the sensitivity of the option to a change in the stock price. For example, if the stock price changes by $1, then the option price, $\Delta \ S + B$ , changes by the amount $\Delta$ . In other words, $\Delta$ is the change in the option price per unit increase in the stock price.

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Put-call parity

The put-call parity relates the price of a European call with a European put that has the same strike price and the same time to expiration. The following is a call on XYZ stock that is compatible to the put described above.

The underlying asset of the call option is the XYZ stock.
The strike price is $55.
The option will expire in one year.
The option is assumed to be a European option, i.e. it can be exercised only at expiration.

The previous post shows that the premium of this call option is $4.316821227. The put-call parity also derive the same cost for the put.

$\displaystyle \begin{aligned} P(55,1)&=C(55,1)-50+55 \ e^{-0.02} \\&=4.316821227-50+55 \ e^{-0.02} \\&=\$ 8.2277 \end{aligned}$

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Remarks

The examples discussed in this post and in the previous post have value even though the examples may seem like an extreme simplification. These two examples are an excellent introduction to the subject of option pricing theory. The one-period example can be extended to a multi-period approach to describe far more realistic pricing scenarios. For example, we can break a year into many subintervals. We then use the 2-state method to describe above to work backward from the stock prices and option values of the last subinterval to derive the value of the replicating portfolio.

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Practice problems

Practice problems can be found in the companion problem blog via the following links:

Practice problem for pricing call

Practice problem for pricing put

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

Pricing a call option – an example

May 25, 2015 Leave a comment

The example in this post illustrates how to price a call option using the one-period binomial option pricing model. The next post will present an example on pricing a put option. The two posts are designed to facilitate the discussion on the binomial option pricing (given in a series of subsequent posts). Links to practice problems are found at the bottom of the post.

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The example

The following gives the information about the stock:

The stock of XYZ company is currently selling for $50 per share. The price per share 1 year from now is expected to increase to $65 or to decrease to $40. The stock pays no dividends.

Consider a call option with the following specifics:

The underlying asset of the call option is the XYZ stock.
The strike price is $55.
The option will expire in one year.
The option is assumed to be a European option, i.e. it can be exercised only at expiration.

The annual risk-free interest rate is 2%. There is a benefit to the buyer of the option described above. If the price of the stock goes up to $65 at the end of the 1-year period, the owner of the option has the right to exercise the option, i.e., buying one share at the strike price of $55 and then selling it at the market price of $65, producing a payoff of $10. If the price of the stock goes down to $40 at the end of the 1-year period, the buyer of the option has the right to not exercise the option. The call option owner buys the stock only when he makes money. What would be the fair price of having this privilege? What is the fair price of this call option?

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Pricing the call option

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Figure 1 – Stock Price

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The assumption of the 2-state stock prices in 1 year simplifies the analysis of the call option. The value of the call option at the end of 1 year is either $10 (=65-55) or zero. Note that when the share price at the end of the 1-year contract period is less than the strike price of $55, the call option expires worthless. The following diagram shows the value of the call option.

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Figure 2 – Call Option Payoff

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In the above diagram, the value of the call option at the end of 1-year is either $10 or $0. The value of the option at time 0 is $C$ , which is the premium of the call option in this example. Our job here is to calculate $C$ . The key to finding the value of the option is to compare the payoff of the call to that of a portfolio consisting of the following investments:

Portfolio A

Buy 0.4 shares of XYZ.
Borrow $15.683 at the risk-free rate.

The idea for setting up this portfolio is given below. For the time being, we take the 0.4 shares and the borrowed amount of $15.683 as a given. Note that $15.683 is the present value of $16 at the risk-free rate of 2%. Let’s calculate the value of Portfolio A at time 0 and at time 1 (1 year from now). The following diagram shows the calculation.

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Figure 3 – Portfolio A Payoff

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Note that the payoff of the call option is identical to the payoff of Portfolio A. Thus the call option in this example and Portfolio A must have the same cost. Since Portfolio A costs $4.317, the price of the option must be $4.317. The Portfolio A of 0.4 shares of stock and $15.683 in borrowing is a synthetic call since it mimics the call option described in the example. Portfolio A is called a replicating portfolio because it replicates the payoff of the call option in question.

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Arbitrage opportunities

In deriving the cost of the call option of $4.137, we rely on the idea that if two investments have the same payoff, they must have the same cost. This idea is called the law of one price, which is a commonsensical idea and is also an important principle in derivative pricing. If the law of one price is violated, in particular if the price of the call option discussed in this example is not $4.317, there would be arbitrage opportunities that can be exploited to gain risk-free profit.

What if the law of one price is violated? For example, what if the option were selling for a higher price (say $4.50)? If the price of the replicating portfolio is less than the price of the option, then we can “buy low and sell high” (i.e. buy the replicating portfolio and sell call option) and obtain a risk-free profit of $0.183. The arbitrage is to buy the synthetic call (Portfolio A) at $4.317 and sell the call option at $4.50. The following table shows the Year 1 cash flows of this arbitrage opportunity.

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Table 1 – Arbitrage opportunity when call option is overpriced

$\left[\begin{array}{llll} \text{Year 1 Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Long synthetic call} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Hold 0.4 shares} & \text{ } & + \$ 16 & + \$ 26 \\ \ \ \ \ \text{Repay borrowed amount of } \$ 15.683 & \text{ } & - \$ 16 & - \$ 16 \\ \text{ } & \text{ } \\ \text{Short call } & \text{ } & \ \ \$ 0 & - \$ 10 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

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The above table shows that buying a synthetic call (holding 0.4 shares and borrow $15.683) and selling a call will have no loss at the end of 1 year. Yet, the time 0 cash flow is $0.183 (=4.50 – 4.317), and is thus a risk-less profit.

If the option is underpriced, then we can still buy low and sell high (in this case, buy call option and sell the replicating portfolio) and obtain risk-free arbitrage profit. For example, let’s say you observe a call option price of $4.00. Then the arbitrage opportunity is to buy the call option at $4.00 and sell a synthetic call (Portfolio A) at $4.317. The time 0 payoff is $0.317, which is a risk-less arbitrage profit. The following table shows the Year 1 cash flows.

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Table 2 – Arbitrage opportunity when call option is underpriced

$\left[\begin{array}{llll} \text{Year 1 Cash Flows} & \text{ } & \text{Share Price = } \$ 40 & \text{Share Price = } \$ 65 \\ \text{ } & \text{ } \\ \text{Short synthetic call} & \text{ } & \text{ } & \text{ } \\ \ \ \ \ \text{Short 0.4 shares} & \text{ } & - \$ 16 & - \$ 26 \\ \ \ \ \ \text{Receive the amount of } \$ 15.683 & \text{ } & + \$ 16 & + \$ 16 \\ \text{ } & \text{ } \\ \text{Long call } & \text{ } & \ \ \$ 0 & + \$ 10 \\ \text{ } & \text{ } \\ \text{Total payoff} & \text{ } & \text{ } \ \$ 0 & \ \ \$ 0 \end{array}\right]$

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To complete the picture

The call option price of $4.317 is derived by showing that the replicating portfolio has the same payoff as the call option. How do we know that the replicating portfolio consists of holding 0.4 shares and the borrowing of $15.683?

In general, the replicating portfolio of a European call option consists of $\Delta$ shares of the stock and the amount $B$ in lending at time 0 (borrowing if negative). By equating the payoff of the replicating portfolio and the payoff of the call option in this example, we have the following equations:

$\text{ }$

$\displaystyle \begin{array}{ccc} \displaystyle 40 \ \Delta + B \ e^{0.02} & = & 0 \\ \displaystyle 65 \ \Delta + B \ e^{0.02} & = & 40 \end{array}$

$\text{ }$

Solving these two equations, we obtain $\Delta=\frac{10}{25}=0.4$ and $B=-16 \ e^{-0.02}=15.683$ . Therefore, the replicating portfolio for the call option in this example consists of 0.4 shares of the stock and $15.683 in borrowing. The net investment for the replicating portfolio is $4.317 (=0.4(50)-15.683). Because there are only two data points in the future stock prices, the option premium is a linear function of $\Delta$ and $B$ . The following is the premium of the call (or put) option using the one-period binomial tree

$C=\Delta \ S+B$

where $S$ is the stock price at expiration. The above formula gives the cost of the portfolio replicating the payoff of a given option. It works for call option as well as for put option. We will see that for put options, $\Delta$ is negative and $B$ is positive (i.e. shorting stock and lending replicate the payoff of a put). The number $\Delta$ has a special interpretation that will be important in subsequent discussion of option pricing. It can be interpreted as the sensitivity of the option to a change in the stock price. For example, if the stock price changes by $1, then the option price, $\Delta \ S + B$ , changes by the amount $\Delta$ . In other words, $\Delta$ is the change in the option price per unit change in the stock price.

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Put-call parity

The put-call parity relates the price of a European call with a European put that has the same strike price and the same time to expiration. The following is a put on XYZ stock that is compatible to the call described above.

The underlying asset of the put option is the XYZ stock.
The strike price is $55.
The option will expire in one year.
The option is assumed to be a European option, i.e. it can be exercised only at expiration.

By the put-call parity, the following gives the price of the put option.

$\displaystyle \begin{aligned} P(55,1)&=C(55,1)-50+55 \ e^{-0.02} \\&=4.316821227-50+55 \ e^{-0.02} \\&=\$ 8.2277 \end{aligned}$

The next post will calculate the price of the same put using the binomial model.

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Remarks

We would like to comment that even though the example here may seem like an extreme simplification, the example has great value. First of all, this is an excellent introduction to the subject of option pricing theory. Secondly, the one-period example can be extended to a multi-period approach to describe far more realistic pricing scenarios. For example, we can break a year into many subintervals. We then use the 2-state method to describe above to work backward from the stock prices and option values of the last subinterval to derive the value of the replicating portfolio.

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Practice problems

Practice problems can be found in the companion problem blog via the following links:

Practice problem for pricing call

Practice problem for pricing put

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

Put-Call Parity, Part 2

May 16, 2015 1 Comment

Put-call parity is a key idea in option pricing theory. It provides a tool for constructing equivalent positions. The previous post gives a general discussion of the put-call parity. In this post, we discuss the put-call parity for various underlying assets, i.e. the parity relations in this post are asset specific. The following is one form of the general put-call parity. This is the version (0) discussed in the previous post.

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Put-Call Parity

$\displaystyle PV(F_{0,T})=C(K,T)-P(K,T)+PV(K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (0)$

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The put-call parity has four components – the price of the call, the price of the put, the present value of the strike price and the present value of the forward price. In the general form of the put-call parity, the present value of the forward price completely take the dividends and time value of money into account. For a specific type of underlying asset, in order to make the put-call parity more informative, we may have to take all the interim payments such as dividends into account. Thus in the parity relations that follow, the general forward price is replaced with the specific forward price for that asset. Synthetic assets can then be created from the asset-specific put-call parity that is obtained.

The notations used here are the same as in the previous posts. The notation $F_{0,T}$ is the forward price. All contracts – forward and options and other type of contracts – are set at time 0 (today) and are to end at time $T$ . The strike price for the options is $K$ . The letter $r$ denotes the risk-free annual continuous interest rate. If the strike price $K$ is paid for an asset at time $T$ , its present value at time 0 is $PV(K)=e^{-r T} K$ . All options discussed here are European options, i.e. they can be exercised only at expiration.

All the parity relations that follow will obviously involve a call and a put. To make this extra clear, the call and the put in these relations have the same strike price and the same time to expiration. Thus whenever we say buying a call and selling a put, we mean that they are compatible in this sense.

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Put-call parity for stocks

Forward prices for stocks are discussed here. For a non-dividend paying stock, the forward price is $F_{0,T}=S_0 e^{r T}$ , i.e. the price to pay for the stock in the future is the future value of the time 0 stock price. The following is the put-call parity of a non-dividend paying stock.

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Put-Call Parity – non-dividend paying stock

$\displaystyle S_0=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (S1)$

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The parity (S1) says that there are two ways to buy a non-dividend paying stock at time 0. One is the outright stock purchase (the left side). The other way (the right hand side) is to buy a call, sell a put and lend the present value of the strike price $K$ . By buying a call and selling a put, it is certain that you will buy the stock by paying $K$ , which is financed by the lending of $PV(K)=e^{-r T} K$ at time 0. In both ways, you own the stock at time $T$ . There is a crucial difference. In the outright stock purchase, you own the stock at time 0. In the “options” way, the stock ownership is deferred until time $T$ . For the non-dividend paying stock, an investor is probably indifferent to the deferred ownership in the right hand side of (S1). For dividend paying stock, deferred ownership should be accounted for the parity equation.

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Put-Call Parity – dividend paying stock (discrete dividend)

$\displaystyle S_0-PV(\text{Div})=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (S2)$

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In (S2), $\text{Div}$ refers to the dividends paid during the period from time 0 to time $T$ and $PV(\text{Div})$ refers to the time 0 value of $\text{Div}$ . The deferred stock ownership on the right hand side of (S2) does not have the dividend payments while the outright stock ownership has the benefit of the interim dividend payments. Thus the cost of deferred stock ownership must be reduced by the amount of the dividend payments. This is why the dividend payments are subtracted on the left hand side. The next parity relation is for a stock or stock index paying continuous dividend.

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Put-Call Parity – dividend paying stock (continuous dividend)

$\displaystyle S_0 e^{-\delta T}=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (S3)$

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Continuous dividends are reinvested (as additional shares) where $\delta$ is the annual continuous compounded dividend rate. The forward price is $F_{0,T}=S_0 e^{(r-\delta) T}$ . The present value of the forward price is $S_0 e^{-\delta T}$ , which is the left hand side of (S3). The left side of (S3) is saying that $e^{-\delta T}$ shares at time 0 will accumulate to 1 share at time $T$ . The right hand side is saying that buying a call, selling a put and lending out the present value of $K$ at time 0 will lead to ownership of 1 share at time $T$ .

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Synthetic stocks and other synthetic assets

In this section, we consider synthetic assets that can be created from the parity relations on stocks. These synthetic assets are parity relations. The left side of each of these relations is an asset that exists naturally in the financial market place. The right hand side is the synthetic asset – a portfolio that is an alternative asset that has the same cost and payoff, thus a portfolio that mimics the natural asset. For example, a synthetic stock is a combination of put and call and a certain amount of lending that will replicate the same payoff as owning a share of stock. In the next section, we will resume the discussion of put-call parity on underlying assets.

Each of the parity relation in this section is derived from an appropriate stock put-call parity by solving for the desired asset. For a synthetic stock, we put the stock on the left hand side by itself.

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Synthetic stock – non-dividend paying

$\displaystyle S_0=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (Syn1)$

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Synthetic stock – discrete dividend paying

$\displaystyle S_0=C(K,T)-P(K,T)+e^{-r T} K+PV(\text{Div}) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (Syn2)$

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Synthetic stock – continuous dividend paying

$\displaystyle S_0 =(C(K,T)-P(K,T)+e^{-r T} K) \ e^{\delta T} \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (Syn3)$

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Note that (Syn1) is identical to (S1) since there is no dividend. The portfolio on the right hand side is the synthetic stock. For example, for (Syn2), the strategy of buying a call, selling a put, and lending out the present values of the strike price and the interim dividends is an alternative way to own a discrete dividend paying stock. There is a crucial difference between outright stock ownership on the left hand side and the deferred stock ownership on the right hand side. The synthetic stock pays no dividends. Thus the outright stock ownership is worth more than the synthetic stock. In other words, the cost of outright stock ownership exceeds the synthetic cost. By how much? By the present value of the interim dividends. This is why the present value of the dividend payments is added to the right hand side of (Syn2) and (Syn3).

Now we consider synthetic T-bills (or synthetic risk-free asset).

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Synthetic T-bill – based on non-dividend paying stock

$\displaystyle e^{-r T} K=S_0-C(K,T)+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (T1)$

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Synthetic T-bill – based on discrete dividend paying stock

$\displaystyle e^{-r T} K+PV(\text{Div})=S_0-C(K,T)+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (T2)$

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Synthetic T-bill – based on continuous dividend paying stock

$\displaystyle e^{-r T} K=S_0 e^{-\delta T}-C(K,T)+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (T3)$

$\text{ }$

In (T1), (T2) and (T3), the right hand side is the synthetic way of creating a T-bill. Let’s look at (T3).

$e^{-\delta T}$

$T$

$e^{-\delta T}$

$K$

$T$

$K$

$T$

$K$

Next we consider synthetic call options.

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Synthetic call – based on non-dividend paying stock

$\displaystyle C(K,T)=S_0-e^{-r T} K+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (C1)$

$\text{ }$

Synthetic call – based on discrete dividend paying stock

$\displaystyle C(K,T)=S_0-e^{-r T} K-PV(\text{Div})+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (C2)$

$\text{ }$

Synthetic call – based on continuous dividend paying stock

$\displaystyle C(K,T)=S_0 e^{-\delta T}-e^{-r T} K+P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (C3)$

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The right hand side of the above three equations are synthetic ways to buy a stock call option. They can be derived by solving for $C(K,T)$ in the put-call parity relation in respective stock. It also pays to think through the cash flows on both sides. The right hand side of each of (C1) through (C3) consists of a leveraged position (stock purchase plus borrowing) and a long put to insure the leveraged position. For example, in the right hand side of (C1), borrow $e^{-r T} K$ and buy one share of stock (the leveraged position). Then use a purchased put to insure this leveraged position.

Another way to look at synthetic call is that the right hand side consists of a protective put and borrowing. A protective put is the combination of a long asset and a long put. For example, the right hand side of (C1) consists of $S_0+P(K,T)$ (a protective put) and the borrowing of $e^{-r T} K$ , the present value of $K$ .

Here’s the synthetic put options.

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Synthetic put – based on non-dividend paying stock

$\displaystyle P(K,T)=C(K,T)-S_0+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (P1)$

$\text{ }$

Synthetic put – based on discrete dividend paying stock

$\displaystyle P(K,T)=C(K,T)-S_0+e^{-r T} K+PV(\text{Div}) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (P2)$

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Synthetic put – based on continuous dividend paying stock

$\displaystyle P(K,T)=C(K,T)-S_0 e^{-\delta T}+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (P3)$

$\text{ }$

The right hand side of each of (P1) through (P3) is a synthetic put, a portfolio that mimics the payoff of a put option. Note that the right hand side consists of a long call and a short stock position (this is a protective call) and the lending of the present value of $K$ .

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Put-call parity for currencies

A previous post on forward prices shows that the currency forward price is $F_{0,T}=x_0 \ e^{(r-r_f) T}$ where $x_0$ is the exchange rate (units of domestic currency per unit of foreign currency, e.g. dollars per euro), $r$ is the domestic risk-free rate and $r_f$ is the foreign currency risk-free rate. The present value of $F_{0,T}$ is then $e^{-r T} \ F_{0,T}=x_0 \ e^{-r_f T}$ , which is the number of units of the domestic currency (e.g. dollars) at time 0 in order to have one unit of foreign currency (e.g. euro) at time $T$ . Substituting $e^{-r T} \ F_{0,T}=x_0 \ e^{-r_f T}$ into the parity relation of (0), we have:

$\text{ }$

Put-Call Parity – Currencies

$\displaystyle x_0 \ e^{-r_f T}=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (F1)$

$\text{ }$

$\displaystyle x_0 \ e^{-r_f T}-e^{-r T} K=C(K,T)-P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (F2)$

$\text{ }$

In (F1) and (F2), we assume that the call and the put are denominated in dollars, i.e. both the strike price $K$ and the put premium and call premium are denominated in dollars. For ease of discussion, let’s say the foreign currency is euro. The premium $C(K,T)$ discussed here is in dollars and grants the right to pay $K$ to get 1 euro. The premium $P(K,T)$ discussed here is in dollars and grants the right to pay 1 euro to get $K$ . Thus the strike price $K$ is an exchange rate of USD per euro.

For example, let’s say $K=$ 0.80 USD/Euro at time 0. If at time $T$ the exchange rate is $x_T=$ 0.9 USD/Euro, the call buyer would want to exercise the option by paying 0.8 USD for 1 euro. If at time $T$ the exchange rate is $x_T=$ 0.7 USD/Euro, then the long put position would want to exercise the put by paying 1 euro to get 0.8 USD.

The relation (F1) indicates that the difference in the call and put premiums plus lending the present value of the strike price is the same as lending the present value of the amount in dollars (the domestic currency) that is required to buy 1 euro at time $T$ .

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Put-call parity for bonds

For a zero-coupon bond, the forward price is simply the future value of the bond price. For a coupon paying bond, the future price has to reflect the value of the coupon payments. In the following parity relations, $B_0$ is the bond price at time 0. The amount $PV(\text{Coupons})$ is the present value of the coupon payments made during the life of the options.

$\text{ }$

Put-Call Parity – zero-coupon bond

$\displaystyle B_0=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (B1)$

$\text{ }$

$\displaystyle B_0-PV(\text{Coupons})=C(K,T)-P(K,T)+e^{-r T} K \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (B2)$

$\text{ }$

Note that for the zero-coupon bond, the parity relation is similar to the one for non-dividend paying stock.

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Summary

The following is the list of all the asset specific put-call parity relations discussed in this post.

$\text{ }$

Forward/Futures

$\displaystyle e^{-r T} \ F_{0,T}=C(K,T)-P(K,T)+PV(K)$

$\text{ }$

Non-dividend paying stock
$\displaystyle S_0=C(K,T)-P(K,T)+e^{-r T} K$
$\text{ }$

Discrete dividend paying stock
$\displaystyle S_0-PV(\text{Div})=C(K,T)-P(K,T)+e^{-r T} K$
$\text{ }$

Continuous dividend paying stock
$\displaystyle S_0 e^{-\delta T}=C(K,T)-P(K,T)+e^{-r T} K$
$\text{ }$

Currency
$\displaystyle x_0 \ e^{-r_f T}=C(K,T)-P(K,T)+e^{-r T} K$
$\text{ }$

Bond
$\displaystyle B_0=C(K,T)-P(K,T)+e^{-r T} K$
$\text{ }$

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

Put-Call Parity, Part 1

May 13, 2015 Leave a comment

Put–call parity is a relationship between the price of a European call option and European put option with the same strike price and time to expiration. It is one of the most important relationships in option pricing. It provides a tool for constructing equivalent positions. This post is a general discussion of put-call parity. In the next post, we discuss put-call parity in greater details for various underlying assets – e.g. stocks, treasuries and currencies.

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Synthetic forward – buying a call and selling a put

Suppose you follow the strategy of buying a call and selling a put (at time 0) where both options have the same underlying asset, the same strike price $K$ and the same time $T$ to expiration. At time $T$ , it is certain that you will buy the underlying asset by paying the strike price $K$ . Too see this, if at expiration of the options, the asset price is more than $K$ , then you, as a call buyer will want to exercise the call option and pay $K$ to buy the asset. If the asset price at expiration is less than $K$ , then you as a call buyer will not want to exercise but the put buyer that bought from you will want to exercise the put option. As a result, you will also buy the asset by paying the strike price $K$ . Thus by entering into a long call and a short put (on the same underlying asset, with the same strike and same time to expiration), you will end up buying the underlying asset at time $T$ at the strike price $K$ . What is being described sounds very much like a forward contract – a contract in which you can lock in a price today to pay for an asset a time $T$ in the future. For this reason, the strategy of buying a call and selling a put is called a synthetic forward contract.

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Put-call parity

The above discussion on synthetic forward suggests that there are two ways to buy an underlying asset (e.g. a stock) at time $T$ in the future. They are:

Enter into a forward contract to buy the underlying asset by paying the forward price $F_{0,T}$ at time $T$ .
Buy a call and sell a put today (on the same underlying asset, with the same strike price $K$ and the same time $T$ to expiration).

The two different strategies generate the same payoff. Hence they must have the same cost. Otherwise there would be arbitrage opportunities. By the “no-arbitrage pricing” principle, the net cost of the two strategies must equal. The cost at time 0 of the “buy call sell put” strategy is $C(K,T)-P(K,T)$ , plus the present value of the strike price $K$ , where $C(K,T)$ and $P(K,T)$ represent the call option premium and put option premium, respectively. The cost at time $T$ of the forward contract strategy is the forward price $F_{0,T}$ . Thus cost at time 0 of the forward contract strategy is the present value of $F_{0,T}$ . We can now equate the costs of the two strategies.

$\text{ }$

Put-Call Parity

$\displaystyle PV(F_{0,T})=C(K,T)-P(K,T)+PV(K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (0)$

$\text{ }$

The notation $PV(\cdot)$ denotes the time 0 value of an amount at the time $T$ . Equation (0) is one form of the put-call parity, which is a statement that buying a call and selling a put is equivalent to a synthetic forward contract. It also tells us that buying a call and selling a put plus lending the present value of the strike price is equivalent to buying the underlying asset.

Other versions can be derived by algebraically rearranging equation (0), some of which have interesting interpretations. The following is one of them.

$\text{ }$

Put-Call Parity

$\displaystyle C(K,T)-P(K,T)=PV(F_{0,T}-K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)$

$\text{ }$

The left hand side of (1) is the net option premium – the premium paid for the call less the premium received for the put. When this amount is not zero, it is in effect the premium of the synthetic forward contract (this amount is the initial cash outlay for the synthetic forward contract). This is one difference between a synthetic forward and an actual forward. Note that an actual forward contract has zero premium (the initial cash outlay is zero). Another difference is that the “forward price” of the synthetic forward is the strike price $K$ of the options and while the forward price of the actual forward is $F_{0,T}$ .

Suppose that the strike price $K$ is chosen to be less than the actual forward price $F_{0,T}$ . Then the holder of the synthetic forward contract can buy the asset at a price lower than the forward price. This is certainly a benefit. In order to get this benefit, the holder of the synthetic forward contract has to pay the net option premium, which is the result of the call being more expensive than the put. In this scenario, the net payment is a little higher at time 0. As a result, the payment at time $T$ is a little less.

Suppose that the strike price $K$ is chosen to be more than the actual forward price $F_{0,T}$ . Then the holder of the synthetic forward position is obliged to pay for the underlying asset at a price higher than the forward. It then makes sense for the holder of the synthetic forward position to be compensated by receiving a payment initially. This would occur if the put is more expensive than the call. In this scenario, the net payment is a little less at time 0, leading to a larger payment at time $T$ .

If the strike price is chosen to be the same as the forward price $F_{0,T}$ , then equation (1) suggests that the synthetic forward mimic exactly the actual forward (both have zero premium). For this to happen, premiums for the put and the call must be equal.

The right hand side of (1) is the value of the discount resulted from paying the strike price instead of the forward price. This version of the put-call parity says that the discount is identical to the net option premium.

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Protective put and covered call

The next two versions can be interpreted in terms of a protective put and a covered call. A protective put consists of a long asset position and a long put. It is the strategy of buying a put option to protect against the risk of falling prices of a long asset position. A covered call consists of a long asset position and a short call. The covered call uses the upside profit potential of the long asset to back up (or cover) the call option sold to the call buyer. First, the protective call version:

$\text{ }$

Put-Call Parity

$\displaystyle PV(F_{0,T})+P(K,T)=C(K,T)+PV(K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)$

$\text{ }$

The left hand side of (2) is the time 0 cash outlay of buying the underlying asset and buying a put. The right hand side of (2) is time 0 cash outlay of buying a call option (with the same strike and time to expiration as the put) and buying a zero-coupon bond costing $PV(K)$ . Thus equation (2) tells us that buying the underlying asset and buying a put on that asset (i.e. a protective put) have the same cost and generate the same payoff as the buying a call option and buying a zero-coupon bond. Adding a bond lifts the payoff graph but does not change the profit graph. Thus buying the asset and buying a put has the same profit as buying a call. Because of Equation (2), buying the underlying asset and buying a put is called a synthetic long call option. This point is also discussed in this previous post. Here’s the version of the put-call parity involving covered call.

$\text{ }$

Put-Call Parity

$\displaystyle PV(F_{0,T})-C(K,T)=PV(K)-P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)$

$\text{ }$

The left hand side of (3) is the time 0 cash outlay of buying the underlying asset and selling a call on that asset (i.e. a covered call). The right hand side of (3) is the time 0 cash outlay of buying a zero-coupon bond costing $PV(K)$ and selling a put. Thus a covered call has the same cost and same payoff as buying a bond and selling a put. Once again, adding a bond does not change the profit. Thus a covered call has the same profit as selling a put. For this reason, a buying the underlying asset and selling a call is called a synthetic short put option. This point is also discussed in this previous post.

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Summary

As a summary, we gather the various versions of the put-call parity in one place along with their interpretations.

$\text{ }$

Versions of Put-Call Parity

$\text{ }$

$\displaystyle PV(F_{0,T})=C(K,T)-P(K,T)+PV(K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (0)$

$\text{ }$

$\displaystyle C(K,T)-P(K,T)=PV(F_{0,T}-K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (1)$
Interpretation: Net option premium (call option premium that is paid out less put option premium received) = the value of the discount as a result of paying the strike price instead of the forward price.
$\text{ }$

$\displaystyle PV(F_{0,T})+P(K,T)=C(K,T)+PV(K) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (2)$
Interpretation: Time 0 cost of (Long Asset + Long Put) = Time 0 cost of (Long Call + Long Bond).
The portfolio on the left (Long Asset + Long Put) is called a protective put.
Because of (2), a protective put is considered a synthetic long call option.
$\text{ }$

$\displaystyle PV(F_{0,T})-C(K,T)=PV(K)-P(K,T) \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ (3)$
Interpretation: Time 0 cost of (Long Asset + Short Call) = Time 0 cost of (Long Bond + Short Put).
The portfolio on the left (Long Asset + Short Call) is called a covered call.
Because of (3), a covered call is considered a synthetic short put option.
$\text{ }$

In each of the above versions of parity, the portfolio of investments on the left side is equivalent to the portfolio of investment on the right side. More specifically, each version equates the costs of obtaining the portfolios at time 0. The bond indicated in the interpretations is a zero-coupon bond. A long position on a bond means lending.

One comment about the four parity relations discussed here. We derive the first one, which is version (0) by comparing the cash flows of two equivalent investments. The other three versions are then derived by algebraically rearranging the first version. As a learning device, it is a good idea to think through the cash flows and payoff of versions (2) through (3) independently of version (0). Doing so is a great practice and will help solidify the understanding of put-call parity. Drawing payoff diagrams can make the comparison easier. It is also possible to just think through the cash flows of both sides of the equation. For example,

$PV(K)$

$T$

$K$

$S_T-K$

$K$

$PV(F_{0,T})$

$T$

$F_{0,T}$

$T$

$K$

$S_T-K$

$K$

$T$

$K$

$T$

The basic put-call parity relations discussed in this post can be used in a “cookbook” fashion to create synthetic assets. For example, version (0) indicates that buying a call, selling a put and lending the present value of the strike price $K$ has the same cost and payoff as buying a non-dividend paying stock. Thus version (0) is a basis for constructing a synthetic stock. In the next post, we discuss the put-call parity for different underlying assets.

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

Financial Mathematics

Revisiting risk-neutral pricing of options

The binomial option pricing model – part 5

The binomial option pricing model – part 4

The binomial option pricing model – part 3

The binomial option pricing model – part 2

The binomial option pricing model – part 1

Pricing a put option – an example

Pricing a call option – an example

Put-Call Parity, Part 2

Put-Call Parity, Part 1

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