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Compute variance of trading profits

Last updated: Mar 29, 2026

Quick Overview

This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Compute variance of trading profits states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • medium
  • Citadel
  • Statistics & Math
  • Data Scientist

Compute variance of trading profits

Company: Citadel

Role: Data Scientist

Category: Statistics & Math

Difficulty: medium

Interview Round: Technical Screen

##### Question Consider a stock price that starts at 0 and evolves as a simple symmetric random walk, moving +1 or -1 each discrete time step. At each time T you: Buy one share if the price change from T−1 to T is +1. Short (sell) one share if the price change is −1. Assuming you can accumulate multiple positions purchased at different prices, derive the variance of the cumulative profit of your holdings at time T. Follow-up: What is the expected profit and why? How would the answer extend if the random walk is replaced by continuous-time Brownian motion?

Quick Answer: This interview question evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer for Compute variance of trading profits states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/Statistics & Math/Citadel

Compute variance of trading profits

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Citadel
Aug 4, 2025, 10:55 AM
mediumData ScientistTechnical ScreenStatistics & Math
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Compute variance of trading profits

Symmetric Random Walk Trading Strategy: Profit Variance and Expectation

Setup

  • Let S_t be a simple symmetric random walk with S_0 = 0 and increments X_t = S_t − S_{t−1} taking values ±1 with equal probability, independent across t.
  • Time is discrete: t = 1, 2, ..., T.

Trading Rule

At each time t (after observing the move from t−1 to t):

  1. If X_t = +1, buy 1 share.
  2. If X_t = −1, short 1 share.

You accumulate all positions and mark them to market at the terminal time T.

Tasks

  1. Derive a closed form for the cumulative profit at time T and compute its variance.
  2. What is the expected profit? Explain.
  3. How do these results extend if S_t is replaced by continuous-time standard Brownian motion B_t?

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify the random variables, distributional assumptions, independence assumptions, and desired output.
  • Show enough derivation for the interviewer to follow the reasoning.
  • Explain how you would validate the result with simulation or sensitivity checks.

What a Strong Answer Covers

  • A correct setup with definitions, formulas, and boundary conditions.
  • A step-by-step derivation or estimation plan.
  • Interpretation of the result, including uncertainty and practical limitations.
  • Checks for assumptions, edge cases, and numerical stability.

Follow-up Questions

  • How would the result change if the assumptions were relaxed?
  • Can you verify the answer with a simulation?
  • What is the most likely source of estimation error?
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