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Analyze Newton-Raphson Convergence, Choose Sigma, and Derive Vega

Last updated: Mar 29, 2026

Quick Overview

This question evaluates numerical root-finding and option pricing competencies, specifically understanding Newton–Raphson convergence properties, implied volatility inference under the Black–Scholes model, and option sensitivity (Vega).

  • medium
  • Intercontinental Exchange
  • Statistics & Math
  • Data Scientist

Analyze Newton-Raphson Convergence, Choose Sigma, and Derive Vega

Company: Intercontinental Exchange

Role: Data Scientist

Category: Statistics & Math

Difficulty: medium

Interview Round: Technical Screen

You are valuing options under the Black–Scholes model and need to compute implied volatility. 1) Explain the Newton–Raphson method for root-finding in this context and detail the conditions under which it fails to converge (e.g., properties of the objective function and its derivative, step-size issues, and edge cases). 2) How would you select an initial volatility (sigma) seed before running Newton–Raphson, and what practical heuristics or data would you use to justify that choice? 3) Write the closed-form formula for Vega under Black–Scholes for a European option, define all variables and units, and explain how Vega’s magnitude influences Newton–Raphson updates.

Quick Answer: This question evaluates numerical root-finding and option pricing competencies, specifically understanding Newton–Raphson convergence properties, implied volatility inference under the Black–Scholes model, and option sensitivity (Vega).

Intercontinental Exchange logo
Intercontinental Exchange
Sep 6, 2025, 12:00 AM
Data Scientist
Technical Screen
Statistics & Math
3
0

Context

You are given the market price of a European option and must infer the Black–Scholes implied volatility. This requires solving for the volatility parameter σ\sigmaσ such that the Black–Scholes price equals the observed market price. Define the root-finding objective as

  • f(σ)=PBS(σ)−Pmktf(\sigma) = P_{BS}(\sigma) - P_{mkt}f(σ)=PBS​(σ)−Pmkt​ , where PBS(σ)P_{BS}(\sigma)PBS​(σ) is the Black–Scholes price (call or put) and PmktP_{mkt}Pmkt​ is the observed market price.

Tasks

  1. Explain the Newton–Raphson method for solving f(σ)=0f(\sigma)=0f(σ)=0 in this setting, and detail when it fails to converge (objective/derivative properties, step-size issues, edge cases).
  2. Describe how to choose an initial volatility seed before running Newton–Raphson, including practical heuristics and justifications.
  3. Write the closed-form Vega for a European option under Black–Scholes, define all variables and units, and explain how Vega’s magnitude affects Newton–Raphson updates.

Solution

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