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Stochastic Models in Biology, Finance and Epidemics · Tutorial 974 of 994

Multi-Period Binomial Option Valuation by Backward Induction

Build option values from maturity back to today, using replication at every node and comparing continuation with immediate exercise for American options.

Intermediate 12 min read

What You'll Learn

  • Set up a finite multi-period binomial stock tree and its pricing parameters
  • Derive the one-period replication and discounting formula
  • Compute European option values by backward induction
  • Compare continuation value with immediate exercise value for American options
  • Verify node values by replication and an independent calculation
  • Avoid common discounting and early-exercise errors

From One-Step Replication to a Multi-Period Tree

A multi-period option tree is a sequence of linked one-period pricing problems. At each node, the option’s possible values one step later can be replicated with shares and a risk-free asset. That replication gives the node’s continuation value. For a European option, continue this calculation back from the maturity payoff. For an American option, compare the continuation value at each node with the value of exercising there.

Fix a horizon of \(N\) periods. Use the finite sample space \(\Omega=\{u,d\}^N\), with its power-set sigma-field and any probability measure \(\mathbb{P}\) that assigns positive probability to every path. Let \(\mathcal{F}_n\) record the first \(n\) moves. The stock price \(S_n\) is determined by the path up to time \(n\): from a node with price \(S\), its next price is \(uS\) after an up move and \(dS\) after a down move. The risk-free asset is worth \(R^n\) at time \(n\), where \(R>0\) is its gross return per period. Assume throughout that \(0<d<R<u\).

The inequalities ensure that the two next-period stock prices lie on opposite sides of the risk-free growth of the current price. Define the pricing weight \(q=(R-d)/(u-d)\). It satisfies \(0<q<1\), since \(R-d>0\), \(u-R>0\), and \(u-d>0\); moreover \(1-q=(u-R)/(u-d)\). These are weights derived from replication. They are not, by definition, the probabilities under the underlying measure \(\mathbb{P}\).

Definition: A node at time \(n\) is a particular history of the first \(n\) moves. Its continuation value is the current cost of a portfolio that replicates the option’s values in the two child nodes. Backward induction means calculating these values from time \(N\) toward time \(0\).

The One-Step Replication Formula

Suppose the required values at the up and down child nodes are \(V^u\) and \(V^d\). A portfolio holding \(\Delta\) shares and \(b\) units of the risk-free asset has value \(\Delta S+b\) now and values \(\Delta uS+Rb\) and \(\Delta dS+Rb\) next period. Replication requires those two future values to equal \(V^u\) and \(V^d\).

$$ \Delta=\frac{V^u-V^d}{S(u-d)},\qquad b=\frac{uV^d-dV^u}{R(u-d)}. $$

Substitution into the portfolio’s current cost gives the one-step pricing formula. The result holds at every node, provided the same \(u,d,R\) apply there and \(0<d<R<u\).

Theorem (One-step replication): For \(S>0\), \(0<d<R<u\), and finite child values \(V^u,V^d\), there is a unique portfolio of shares and risk-free asset that produces those child values. Its current value is \(\big(qV^u+(1-q)V^d\big)/R\), where \(q=(R-d)/(u-d)\).

Proof. The two replication equations are \(\Delta uS+Rb=V^u\) and \(\Delta dS+Rb=V^d\). Subtracting the second from the first gives \(\Delta S(u-d)=V^u-V^d\), which determines \(\Delta\) uniquely because \(S(u-d)>0\). Substitution into either equation gives \(b=(uV^d-dV^u)/(R(u-d))\), so \(b\) is also unique. The current cost is therefore

$$ \Delta S+b =\frac{R(V^u-V^d)+uV^d-dV^u}{R(u-d)} =\frac{(R-d)V^u+(u-R)V^d}{R(u-d)} =\frac{qV^u+(1-q)V^d}{R}. $$

The last equality uses \(q=(R-d)/(u-d)\) and \(1-q=(u-R)/(u-d)\). Thus the stated portfolio exists, is unique, and has the stated cost. \(\square\)

European Options: Work Back from Maturity

A European option can be exercised only at maturity. Let its payoff at time \(N\) be \(g(S_N)\), such as \((S_N-K)^+\) for a call or \((K-S_N)^+\) for a put, where \(x^+=\max(x,0)\). Set \(V_N=g(S_N)\). At a node at time \(n<N\), let \(V^u\) and \(V^d\) be the already calculated values at its up and down children. The one-step theorem gives the recursion below.

Theorem (European backward induction): Under the one-step assumptions at every node, the value at maturity is \(V_N=g(S_N)\), and at every earlier node $$ V_n=\frac{qV^u+(1-q)V^d}{R}. $$ These values are obtained by a self-financing replicating strategy, constructed one step at a time from maturity to time \(0\).

Proof. At maturity the claim pays \(g(S_N)\), so assigning that value at every terminal node is correct. Suppose the values at all nodes at time \(n+1\) have been calculated. At each time-\(n\) node, apply the one-step replication theorem to the two child values \(V^u,V^d\). It supplies a portfolio whose next-period values equal those child values and whose current cost is \(\big(qV^u+(1-q)V^d\big)/R\). Therefore the portfolio replicates the claim from that node onward. Starting at \(n=N-1\) and repeating this argument down to \(n=0\) constructs replication at every node. Uniqueness at each step follows from the one-step theorem, so the recursion determines the replicating value uniquely. \(\square\)

Worked Example: A Two-Period European Call

Take \(S_0=4\), \(u=\tfrac32\), \(d=\tfrac12\), \(R=\tfrac54\), and a call strike \(K=4\). The pricing weight is \(q=(\tfrac54-\tfrac12)/(\tfrac32-\tfrac12)=\tfrac34\), so \(1-q=\tfrac14\). At each node the up and down weights sum to \(\tfrac34+\tfrac14=1\), and the parameter condition holds: \(0<\tfrac12<\tfrac54<\tfrac32\).

The stock prices at time \(1\) are \(6\) and \(2\). At time \(2\), the prices following the up node are \(9\) and \(3\), and following the down node they are \(3\) and \(1\). The call payoffs at those four terminal nodes are respectively \(5,0,0,0\), because \((9-4)^+=5\), \((3-4)^+=0\), and \((1-4)^+=0\).

At the time-1 up node, the continuation value is \(\big(\tfrac34\cdot5+\tfrac14\cdot0\big)/(\tfrac54)=3\). At the time-1 down node, both terminal payoffs are zero, so its value is \(\big(\tfrac34\cdot0+\tfrac14\cdot0\big)/(\tfrac54)=0\). Hence at time \(0\) the value is \(\big(\tfrac34\cdot3+\tfrac14\cdot0\big)/(\tfrac54)=\tfrac95\).

Check by direct terminal weighting: The only positive payoff is reached by two up moves, whose product pricing weight is \((\tfrac34)^2=\tfrac9{16}\). Discounting two periods gives \((\tfrac9{16}\cdot5)/(\tfrac54)^2=\tfrac{45}{16}\cdot\tfrac{16}{25}=\tfrac95\), as above.

Check by replication: At the up node, \(\Delta=5/(6( \tfrac32-\tfrac12))=\tfrac56\) and \(b=(\tfrac32\cdot0-\tfrac12\cdot5)/(\tfrac54\cdot1)=-2\). The cost is \(\tfrac56\cdot6-2=3\). At the root, \(\Delta=(3-0)/(4\cdot1)=\tfrac34\) and \(b=(\tfrac32\cdot0-\tfrac12\cdot3)/(\tfrac54\cdot1)=-\tfrac65\); the cost is \(\tfrac34\cdot4-\tfrac65=\tfrac95\).

American Options: Compare Exercise with Continuation

An American option may be exercised at any allowed time up to and including maturity. At a node with stock price \(S\), immediate exercise pays \(g(S)\). Continuing means holding the option for at least one more period; its value is found by replicating the values in the next two nodes. Define \(A_N=g(S_N)\). At earlier nodes, calculate the continuation value \(C_n\) from the children’s American values and choose the larger of exercise and continuation.

$$ C_n=\frac{qA^u+(1-q)A^d}{R},\qquad A_n=\max\{g(S_n),C_n\}. $$
Theorem (American backward induction): On a finite binomial tree satisfying \(0<d<R<u\), the recursion \(A_N=g(S_N)\) and \(A_n=\max\{g(S_n\},C_n\}\), with \(C_n\) as above, gives the value at every node when exercise is permitted at any time through \(N\). Choosing exercise when the first term is at least the second, and otherwise continuing, attains this value.

Proof. At time \(N\), exercise is required, so the value is \(g(S_N)\). Assume the stated values are optimal at all nodes at time \(n+1\). At a node at time \(n\), any permitted strategy either exercises immediately, receiving \(g(S_n)\), or continues for one step. If it continues, its remaining value in the two child nodes cannot exceed \(A^u,A^d\), by the induction assumption. The one-step replication formula and the positive weights \(q,1-q\) show that the cost of continuing with those optimal child values is \(C_n\), and no continuation using smaller child values has a larger value. Thus no strategy at the current node exceeds \(\max\{g(S_n),C_n\}\). Exercising now attains the first candidate. Continuing and using the optimal choices in each child attains the second candidate. Selecting the larger therefore attains the maximum. Induction from \(N\) back to \(0\) proves the recursion and the stated exercise rule. \(\square\)

Worked Example: An American Put with Early Exercise

Use \(S_0=4\), \(u=\tfrac32\), \(d=\tfrac12\), \(R=\tfrac54\), and a two-period American put with strike \(K=4\). Here \(q=\tfrac34\), \(1-q=\tfrac14\), and each node’s pricing weights sum to \(1\). The parameter condition is \(0<\tfrac12<\tfrac54<\tfrac32\).

The terminal stock prices are \(9,3,3,1\), and the corresponding put payoffs are \(0,1,1,3\). At the time-1 up node, \(S_1=6\), so immediate exercise pays \((4-6)^+=0\). The continuation value is \(\big(\tfrac34\cdot0+\tfrac14\cdot1\big)/(\tfrac54)=\tfrac15\). The American value at this node is therefore \(\max\{0,\tfrac15\}=\tfrac15\).

At the time-1 down node, \(S_1=2\), so immediate exercise pays \((4-2)^+=2\). Its continuation value is \(\big(\tfrac34\cdot1+\tfrac14\cdot3\big)/(\tfrac54)=(\tfrac34+\tfrac34)/(\tfrac54)=\tfrac65\). Thus the node value is \(\max\{2,\tfrac65\}=2\), and exercise is optimal there.

At the root, immediate exercise pays \((4-4)^+=0\). Continuing gives \(\big(\tfrac34\cdot\tfrac15+\tfrac14\cdot2\big)/(\tfrac54)=(\tfrac3{20}+\tfrac12)/(\tfrac54)=\tfrac{13}{25}\). Therefore the American put value is \(\max\{0,\tfrac{13}{25}\}=\tfrac{13}{25}\). The decision at the root is to continue, even though exercise is optimal at the later down node.

Check against the European put: If exercise is allowed only at maturity, the time-1 continuation values are \(\tfrac15\) and \(\tfrac65\). The root value is \(\big(\tfrac34\cdot\tfrac15+\tfrac14\cdot\tfrac65\big)/(\tfrac54)=(\tfrac3{20}+\tfrac3{10})/(\tfrac54)=\tfrac9{25}\). The American value \(\tfrac{13}{25}\) is larger, as expected because the holder can choose the European strategy or exercise early.

A Three-Period Calculation and a Common Error

Worked Example: A Three-Period European Put

Let \(S_0=8\), \(u=\tfrac32\), \(d=\tfrac12\), \(R=1\), and \(K=8\), with maturity after three periods. Then \(q=(1-\tfrac12)/(\tfrac32-\tfrac12)=\tfrac12\) and \(1-q=\tfrac12\); the weights at every node sum to \(1\), and \(0<\tfrac12<1<\tfrac32\).

At time \(3\), the stock prices with zero, one, two, and three up moves are \(1,3,9,27\). The put payoffs are \(7,5,0,0\), respectively. At time \(2\), the nodes with zero, one, and two up moves have stock prices \(2,6,18\). Their values are \((7+5)/2=6\), \((5+0)/2=\tfrac52\), and \((0+0)/2=0\).

At time \(1\), the down node has stock price \(4\), and its children have values \(6\) and \(\tfrac52\), giving \((6+\tfrac52)/2=\tfrac{17}{4}\). The up node has stock price \(12\), and its children have values \(\tfrac52\) and \(0\), giving \((\tfrac52+0)/2=\tfrac54\). The root value is \((\tfrac{17}{4}+\tfrac54)/2=\tfrac{11}{4}\).

Check by terminal weighting: With \(q=\tfrac12\), the probabilities generated by the pricing weights for zero, one, two, and three up moves are \(\tfrac18,\tfrac38,\tfrac38,\tfrac18\). The weighted terminal payoff is \(\tfrac18\cdot7+\tfrac38\cdot5+\tfrac38\cdot0+\tfrac18\cdot0=\tfrac{22}{8}=\tfrac{11}{4}\). Since \(R=1\), discounting three periods does not change this value.

Common mistake: discounting only once. In the two-period call example, the time-1 up-node value is \(3\), but it is not yet the time-0 price. A wrong calculation omits the root-period discount and reports \(\tfrac34\cdot3=\tfrac94\). The root calculation must discount the next-period value by \(R=\tfrac54\): \((\tfrac34\cdot3+\tfrac14\cdot0)/(\tfrac54)=\tfrac95\). The direct terminal check also discounts twice, by \(R^2=(\tfrac54)^2\), and confirms \(\tfrac95\).

Backward induction is useful because it reduces a large tree to local calculations at its nodes. The terminal payoffs are the only initial data for a European option; for an American option, each node also requires the immediate exercise payoff. The replication formula then gives the continuation value, and the exercise comparison makes the optimal stopping decision explicit. A reliable calculation records both quantities at American nodes, keeps the discount factor at every step, and checks the root value by a second route whenever the tree is small enough.

Check Your Understanding

Use the one-step replication formula and show the intermediate values in each calculation.

  1. For \(u=\tfrac43\), \(d=\tfrac23\), and \(R=1\), calculate \(q\) and verify that both pricing weights are positive and sum to \(1\).
  2. At a node with \(S=10\), suppose the two child values are \(V^u=6\) and \(V^d=2\). With \(u=\tfrac32\), \(d=\tfrac12\), and \(R=\tfrac54\), find the replicating holdings and current value.
  3. For a European option, explain why its maturity payoffs are the starting values for backward induction.
  4. At an American-option node, the immediate exercise value is \(3\) and the continuation value is \(\tfrac{11}{4}\). Which action is optimal, and what is the node value?
  5. In the three-period put example, verify the time-1 down-node value by substituting its two child values into the recursion.