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TL;DR

A method for solving sequential games by analyzing from the last decision point backward to the first. At each node, the player chooses the action that maximizes their payoff given optimal future play.

By Valenke Exam Prep Team·Last updated 2026-06-03

Backward Induction

A method for solving sequential games by analyzing from the last decision point backward to the first. At each node, the player chooses the action that maximizes their payoff given optimal future play.

Why it matters for interviews

The standard technique for solving game trees, option pricing (binomial tree), and dynamic programming problems in quant interviews. It yields subgame perfect equilibria.

Definition and Mathematical Foundation

A method for solving sequential games by analyzing from the last decision point backward to the first. At each node, the player chooses the action that maximizes their payoff given optimal future play.

Application in Quantitative Finance

The standard technique for solving game trees, option pricing (binomial tree), and dynamic programming problems in quant interviews. It yields subgame perfect equilibria.

Related Concepts

Related Terms

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Frequently Asked Questions

What is a subgame perfect equilibrium?
A Nash equilibrium where the strategies constitute a Nash equilibrium in every subgame. Backward induction always produces subgame perfect equilibria in finite games of perfect information.
How does backward induction relate to binomial tree pricing?
Start at terminal nodes with known payoffs. At each earlier node, compute the risk-neutral expected value of the two successor nodes, discounted by one period. This is backward induction applied to option pricing.
When does backward induction fail?
It requires finite horizon and perfect information. In infinite-horizon games, games with simultaneous moves, or games with imperfect information, other techniques (repeated game theory, Bayesian equilibrium) are needed.