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Intermediate

Practice Drills: Pricing an Option Using Black Scholes in Python

A drill-heavy course for quant analyst aspirants, prop trading applicants and systematizing traders who understand the Black-Scholes formula on paper but have never turned it into code they would trust with a real position. Every lesson is a worked exercise on a Nifty index option: you pull the inputs off the NSE option chain, calculate d1 and d2 by hand, write and test call and put functions, vectorise them across the whole chain, code and verify the Greeks, solve for implied volatility, harden the pricer against the inputs that break it, and compare your model prices with what the market is actually quoting. The course ends with a capstone where you build, test and report a pricer for a monthly Nifty expiry, the kind of exercise interviewers at prop desks and quant funds hand you on a laptop.

Black-ScholesOption PricingOption GreeksImplied VolatilityNifty OptionsPython for Quant Finance

MODULES

5

DURATION

~3 hrs

TRACK

Python for Finance

What You'll Master

Turn a row of the NSE Nifty option chain into the six inputs a Black-Scholes pricer needs

Compute d1, d2 and N(d) by hand, then reproduce the same numbers in Python

Write tested Black-Scholes call and put functions from scratch with NumPy and SciPy

Prove your pricer is right with put-call parity and known reference values

Vectorise the pricer to value an entire Nifty option chain in one call

Code delta, gamma, vega, theta and rho, and verify each one with finite differences

Back out implied volatility from a market premium with Newton-Raphson and Brent's method

Handle the edge cases that break a naive pricer: expiry day, near-zero volatility and deep out-of-the-money strikes

Build, test and report a Black-Scholes pricer for a monthly Nifty expiry end to end

Access Level

LEARNER

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Everything included

Full Text Playbooks

Actionable Exercises

Mobile Reading Mode

Lifetime Updates

Curriculum Breakdown

Chapter 1: Setting Up the Drill

3 Lessons

Drill Setup: The Nifty Call We Will Price in Python9 min read

Drill: Turning an NSE Option Chain Row into S, K, T, r, q and Sigma11 min read

Drill: A Minimal NumPy and SciPy Setup for Option Pricing9 min read

Chapter 2: Coding the Formula

4 Lessons

Drill: Computing d1, d2 and N(d) by Hand, Then in Python12 min read

Drill: Writing Black-Scholes Call and Put Functions from Scratch12 min read

Drill: Testing Your Pricer with Put-Call Parity and Reference Values11 min read

Drill: Vectorising the Pricer to Value a Full Nifty Option Chain12 min read

Chapter 3: Greeks and Implied Volatility

3 Lessons

Drill: Coding Delta, Gamma, Vega, Theta and Rho as Python Functions13 min read

Drill: Verifying Every Greek with Finite Differences11 min read

Drill: Backing Out Implied Volatility with Newton-Raphson and Brent's Method13 min read

Chapter 4: Edge Cases and Reality Checks

3 Lessons

Drill: Expiry Day, Near-Zero Volatility and Deep OTM Strikes That Break a Naive Pricer11 min read

Drill: Model Price vs NSE Last Traded Price, Reading the Gap11 min read

Drill: Adjusting the Pricer for Dividends on NSE Stock Options10 min read

Chapter 5: Capstone

2 Lessons

Drill: Plotting Price and Greek Profiles Across Strikes and Days to Expiry11 min read

Capstone Drill: Build, Test and Report a Black-Scholes Pricer for a Monthly Nifty Expiry15 min read