Intermediate
Practice Drills: Pricing an American Option Using a Binomial Tree
A drill-heavy course for quant analyst aspirants, prop trading applicants and systematizing traders who know what a binomial tree is but have never priced an American option on one from scratch. Every lesson is a worked exercise on an NSE stock: you set up the inputs, calibrate u, d and p, build the tree by hand, roll it back with an early-exercise check at every node, map the exercise boundary, split out the early-exercise premium, validate against Black-Scholes and the intrinsic floor, extract the Greeks, deal with dividends, and finish by pricing and reporting an American put end to end in Python. The kind of exercise interviewers at prop desks and quant funds hand you on a whiteboard.
Binomial TreesAmerican OptionsEarly ExerciseCox-Ross-RubinsteinOption GreeksPython for Quant Finance
MODULES
5
DURATION
~3 hrs
TRACK
Quantitative Finance
What You'll Master
Turn the terms of an option on an NSE stock into the six inputs a binomial pricer needs
Compute u, d and the risk-neutral probability with the Cox-Ross-Rubinstein parameterization
Build a multi-step recombining stock price tree by hand and fill in terminal payoffs
Roll a tree back with an early-exercise check at every node and price an American put
Locate the early-exercise boundary and read which nodes should be exercised
Measure the early-exercise premium as the American price minus the European price
Sanity-check a tree price against intrinsic value, put-call bounds and Black-Scholes
Read delta, gamma and theta straight off the nodes of a finished tree
Handle dividend-paying stocks and explain when an American call is worth exercising early
Price, validate and report an American put end to end in a short Python script
Access Level
LEARNER
Everything included
Full Text Playbooks
Actionable Exercises
Mobile Reading Mode
Lifetime Updates