💰 Quant Finance • Intermediate • 20-30 min

Option Pricing

Black-Scholes options pricing calculator with Greeks. Learn derivatives pricing and risk management.

About Demo Browser Local analytics + optional AI toggle Attribution: vinallcontact@gmail.com

What this demo is about

Concept first, interaction second

Developed in 1973 by Fischer Black, Myron Scholes, and Robert Merton. Based on **stochastic calculus** and **risk-neutral valuation**.

Learning objectives

  • Explain the main quant decision that Option Pricing is designed to support.
  • Change input assumptions and predict how the output should respond before running the demo.
  • Interpret the result in plain language, not just as a number, chart, or AI recommendation.
  • State one limitation, risk, or governance consideration before using the result in a real decision.

Run modes

  • Supported modes: Browser
  • Demo type: Interactive browser demo
  • Primary launch surface: index.html

Before you start

Starts immediately in browser with no installs, no API keys, and classroom-safe defaults.

This helps set classroom expectations before students click into the live experience.

Business or domain context

Why this demo matters

Students should connect the demo to a real decision, not treat it as a standalone screen.

Core context

Look for intrinsic value, time value, volatility input, and option price.

Observe how moneyness and time affect option valuation.

Concepts covered

Risk-return trade-off
Sensitivity analysis
Simulation
Valuation logic

What students should note

Note that option pricing should be linked to hedging and risk-management decisions.

How to use the demo

Recommended classroom flow

List of steps

  • Choose the run mode that fits the class: Browser.
  • Review the default assumptions before changing anything.
  • Change one or two inputs, then use `Run the main action`.
  • Read the output first, then compare any supporting metrics, charts, or AI text.
  • Capture one insight, one limitation, and one action recommendation.

Input variables explained

  • Start with the default assumptions, then change one variable at a time so students can isolate cause and effect.
  • Treat each input as a lever that changes the scenario, baseline, or business context behind the result.

Decision buttons explained

  • Use the main run or simulate action to compute the scenario after inputs are set.
  • Use export or reset actions, when present, to compare runs or return to a classroom-safe baseline.

Outputs and interpretation

How to read the result

Outputs explained

  • Read the top-line result first, then look for supporting metrics, tables, or narratives that explain why it changed.
  • Students should explain whether the output is descriptive, predictive, simulated, or recommended.

What to notice

  • Look for intrinsic value, time value, volatility input, and option price
  • Observe how moneyness and time affect option valuation
  • Note that option pricing should be linked to hedging and risk-management decisions

Discussion and reflection

  • What business or technical decision would you make differently after using Option Pricing?
  • If you changed one assumption and ran `main action`, which output moved the most and why?
  • What would you still want to validate with real data, policy, or expert review before acting on the result?

Faculty guide

Prompt for discussion or assessment

Use a before/after discussion: what does the number mean for an investment, hedge, or funding decision?

Suggested interpretation prompt: Ask learners to explain how the output changed, what assumption caused it, and what real-world check they would do next.

Feedback

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Attribution & reuse

Created by Professor Vinaya Sathyanarayana as part of KateelLearningDemosToStudents. Please retain attribution and notify usage at vinallcontact@gmail.com.