The stock can only go up or down by a known factor next period. It sounds too simple, yet this binomial framework is the backbone of option pricing. Every multi-period tree and even Black-Scholes emerge as limiting cases. The key insight: price through replication, not prediction. The actual probability of the stock going up never appears in the formula.
Stock at moves to (up) or (down) over period . No-arbitrage requires .
HIGH-FREQUENCY: The risk-neutral probability and one-period formula appear on most FAM sittings.
This is not the true probability. It makes the expected stock return equal the risk-free rate.
KEY: The risk-neutral probability is NOT the actual probability of the stock going up. It is a pricing construct that makes the expected return equal the risk-free rate.
Common mistakes
- Using the wrong in . Two periods over one year means , so , not . Trap: computed with total time instead of per-period time.
- Forgetting to discount at each step. Each backward step requires . Skipping one gives an answer that is too large. Trap: an option price about 2-3% too high.
- Computing with the wrong formula. Numerator is , not . Reversing gives . Trap: swapped up/down payoff weights.
Bottom line
- Risk-neutral probability: , valid only when (no arbitrage).
- One-period price: ; actual probabilities are irrelevant.
- Replicating portfolio: , , with for calls and for puts.
- Multi-period: work backwards from terminal payoffs, with the same at every node.
Exam shortcut
Compute first (you use it at every node. For two-period problems, draw the full tree on scratch paper: stock prices at every node, then option values right to left. Remember: "p-star = (growth minus down) over (up minus down)") how far the risk-free growth exceeds the down move, relative to the full range. "Work backwards", start at terminal payoffs, always.
The full lesson (about 1,813 words, 12 min read) adds 2 worked examples, all 5 common mistakes, a self-check, free in the app.
Learning objectives
- 6b
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