Quant Interview Expected Value Roadmap
A quant interview expected value roadmap covering linearity, indicators, stopping rules, betting games, and fair prices.
Candidates who need to turn probability reasoning into valuation and decision-making.
Start with direct expectation
Begin with direct expected value: list outcomes, assign probabilities, and multiply payoff by probability. This builds the habit of valuing uncertainty instead of guessing from the most likely outcome.
Use linearity early
Linearity of expectation is one of the highest-value tools in quant interviews. Practice sums of dice, indicator variables, matching problems, and occupancy questions. The key lesson is that expectation can add cleanly even when events are dependent.
Add stopping rules
Stopping questions need state definitions. If a game ends after a pattern, threshold, or choice, write the value of the current state and condition on the next event. This turns a messy path tree into a small recurrence.
Connect EV to trading decisions
Expected value prep is incomplete until it becomes a decision. After computing the value of a bet or game, ask what price is fair, whether variance matters, how size should change, and what information would make you refuse the trade.
Concrete roadmap example
A focused EV block can start with direct dice and card payoffs, move to indicator variables, then practice one-step stopping games, and finish with betting prompts where you explain price, size, and risk.
Common mistakes
Candidates often enumerate too much, confuse expectation with the most likely outcome, or stop after "positive EV" without discussing risk. In interviews, the value is only part of the decision.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.