How to Build a Binomial Tree for Option Pricing

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A binomial tree is one of the cleanest ways to understand option pricing because it turns a continuous-time idea (“price evolves with uncertainty”) into a small set of possible up/down paths. If you can build the tree correctly, you can price European options, handle early exercise for American options, and compute hedge ratios step by step.

What it is: A binomial tree models the stock price over discrete time steps, where each step moves the price up by factor \(u\) or down by factor \(d\).

How you use it: Build the stock-price lattice, compute option payoffs at maturity, then work backward using risk-neutral probabilities and discounting to get today’s option price.

Why Binomial Trees Work

In a one-step model, the option can be replicated by holding \(\Delta\) shares and borrowing/lending an amount \(B\). Replication implies a unique no-arbitrage price. The binomial tree extends the same logic across many short steps.

Key idea: price by expected discounted payoff under a risk-neutral probability \(p\), not the real-world probability.

How to Build a Binomial Tree (Step by Step)

Step 1: Choose inputs

  • Current stock price \(S_0\)
  • Strike \(K\)
  • Risk-free rate \(r\) (per period)
  • Number of steps \(N\)
  • Up and down factors \(u\) and \(d\)

Common choice (CRR): \(u=e^{\sigma\sqrt{\Delta t}}\), \(d=e^{-\sigma\sqrt{\Delta t}}=\frac{1}{u}\).

Step 2: Build the stock-price lattice

After \(i\) steps with \(j\) up moves:

\[ S_{i,j} = S_0\,u^j d^{\,i-j}. \]

Step 3: Compute risk-neutral probability

\[ p=\frac{(1+r)-d}{u-d}. \]

Step 4: Compute option payoff at maturity

For a call:

\[ C_{N,j}=\max(S_{N,j}-K,0). \]

Step 5: Backward induction (discounted expectation)

\[ C_{i,j}=\frac{1}{1+r}\left(p\,C_{i+1,j+1}+(1-p)\,C_{i+1,j}\right). \]

For an American option, compare continuation vs immediate exercise at each node.

Numerical Example (1-Step Call)

Suppose \(S_0=100\), \(K=100\), \(r=0.05\), \(u=1.2\), \(d=0.9\).

Stock outcomes: \(S_u=120\), \(S_d=90\). Call payoffs: \(C_u=20\), \(C_d=0\).

Risk-neutral probability:

\[ p=\frac{1.05-0.9}{1.2-0.9}=\frac{0.15}{0.3}=0.5. \]

Option price:

\[ C_0=\frac{1}{1.05}\left(0.5\cdot 20+0.5\cdot 0\right)=\frac{10}{1.05}\approx 9.52. \]

Common Mistakes

  • Using real-world probabilities instead of risk-neutral \(p\).
  • Forgetting to discount by \(1+r\) at each step.
  • Choosing \(u\) and \(d\) that make \(p\notin[0,1]\) (arbitrage problem).
  • Mixing up indices: \(S_{i,j}\) has \(j\) up moves after \(i\) total steps.
  • For American options, forgetting to check early exercise at every node.

Why This Matters

Binomial trees are used to price options, teach replication and no-arbitrage, and build intuition for Black–Scholes. They also show you how hedge ratios \(\Delta\) change through time, which is a common exam and interview target.

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