Options Trading: The Complete Guide to Greeks & Python Tools

Name: Options Trading: The Complete Guide to Greeks & Python Tools
Rating: 4.6 (42 reviews)

Master options trading by building payoffs, calculating Greeks and IV, and analyzing real strategies using Python

Created byPython for Finance Mastery

Last updated 5/2025

English

English [Auto],

What you'll learn

Calculate Greeks (Delta, Gamma, Theta, Vega) using the Black-Scholes model — fully implemented in Python
Build and compare real-world options strategies like protective puts, iron condors, and butterflies
Estimate implied volatility using both Newton-Raphson and Brent’s method based on real market option prices
Analyze strategy performance using live option chain data from Binance and Bybit
Understand moneyness, intrinsic vs. extrinsic value, and the role of volatility in pricing and strategy selection
Use Python to simulate, test, and break down payoff profiles across different market conditions

Course content

6 sections • 32 lectures • 2h 39m total length

Introduction1:48
Master options trading from fundamentals to Greeks, using Python tools to model payoff, price with Black-Scholes, estimate implied volatility, and run strategy simulations with real data.
Risk Disclaimer0:25
Read this risk disclaimer to learn the course is for educational purposes only, not financial advice, and to do your own research or consult a licensed professional before trading.
What Are Options?2:11
Explore the basics of options as derivatives that give you the right, not the obligation, to buy or sell an asset, with calls and puts enabling leverage, hedging, and income.
Key Terminology (Strike, Premium, Moneyness, Expiration, American vs European)3:10
Explore option terminology including strike price, premium, expiration, and moneyness, compare American vs European styles, and learn to read an option chain with bid-ask, implied volatility, volume, and open interest.
Use Cases (Hedging, Speculation, Income)1:53
Use options to hedge risk, speculate on price movements, and generate income with selling strategies like covered calls. Learn how puts protect, calls enable leverage, and selling options boosts returns.
Hands-On: Visualizing Options with Python6:01
Fetch real option chain data for Tesla, build payoff diagrams for calls and puts, and show how these tools connect to module one concepts using Python, Yfinance, and Pandas.
Test your knowledge

Intrinsic vs Extrinsic Value2:57
Explore intrinsic value and extrinsic value, including time value, that together determine an option's price. See how time, volatility, and demand shape the premium, with strike price context.
The Greeks4:57
Explore how the four greeks—delta, gamma, theta, and vega—shape option pricing by measuring price reactions to stock moves, time decay, and implied volatility, guiding risk decisions.
Time Decay & Volatility2:51
Explore time decay and implied volatility as key drivers of options pricing. Learn how theta erodes value toward expiry and how IV shifts premiums, including the risk of IV crush.
Black-Scholes Intuition4:49
Build an intuitive understanding of the Black-Scholes model, its five inputs, and the assumptions behind it, and learn how it prices European options and derives the Greeks for implied volatility.
Black-Scholes Pricing + Greeks Explained7:38
Python: Option Pricing & Greeks Using Black-Scholes7:56
Implement the Black-Scholes option pricing model in Python, computing call and put prices and the four Greeks: delta, gamma, vega, and theta, using NumPy and SciPy.
Python: Reverse Engineering a Bitcoin Option price5:16
Reverse engineer a Bitcoin call option price from Binance with Python and Black-Scholes. Use current price, strike, time to expiration, and implied volatility to compare model and market prices.
Python: Monte Carlo Simulation for Option Pricing6:37
Price a european call with Monte Carlo simulation using geometric Brownian motion, compare results to the Black-Scholes formula, and explain when Monte Carlo excels for path dependent options.
Test your Knowledge

What is Implied Volatility?3:12
Explore implied volatility and how it differs from historical volatility, using market price and the Black-Scholes framework. See how it reflects market expectations and informs option pricing and trading strategies.
Pythion: IV Solver - Newton-Raphson Method6:43
Estimate the implied volatility of a European call by applying the Newton-Raphson method in Python, updating sigma with vega until the Black-Scholes price matches the market price.
Python: IV Solver - Brent’s Method (Robust Root Finding)3:51
Estimate the implied volatility of a European call with Brent's method, using Black-Scholes pricing, an objective function, and a sign-change interval to ensure convergence.
Python: Reverse Engineering Implied Volatility using real market data6:59
Reverse engineer implied volatility from live Binance vanilla options data using the Black-Scholes model and Brandes’ method, via requests, extracting strike and mid price to solve for sigma.
The Volatility Smile2:29
Explore how the volatility smile contradicts Black-Scholes by showing implied volatility is lowest at the money and rises toward the wings, affecting pricing, risk, and strategies like spreads or condors.
Test your Knowledge

Covered Call and Protective Put3:30
Apply option theory to two foundational strategies: covered call and protective put, combining stock and options to generate income or protect against downside with premiums, strike prices, and payoffs.
Python: Covered Call and Protective Put10:08
Simulate and compare the payoff of covered calls and protective puts using numpy and matplotlib, translate the theory into code, and visualize payoffs to analyze break-even and risk-reward.
Vertical Spreads: Bull Call and Bear Put Spread2:23
Explore vertical spreads, a two-leg options strategy with defined risk and reward. Learn bull call spreads for moderate upside and bear put spreads for moderate downside.
Python: Bull Call and Bear Put Spread9:31
Simulate and compare the payoff of bull call spread and bear put spread in Python, using NumPy and Matplotlib, with long/short legs, strikes, premiums, and final stock prices.
Iron Condor & Butterfly3:06
Explore non-directional options strategies for rangebound markets with iron condor and butterfly, profiting from time decay and low volatility through net credit and capped risk.
Python: Iron Condor & Butterfly10:19
Simulate and compare the iron condor and butterfly payoffs by translating multi-leg option strategies into Python with NumPy and Matplotlib, visualizing payoffs across expiration stock prices.
Why Greeks Matter in Strategies4:04
Explore how the option greeks drive real strategies like covered calls, vertical spreads, and iron condors, using delta, theta, vega, and gamma to manage time decay and volatility.
Options Strategy Execution & Visualization with Bybit11:19
Apply Bybit's option constructor to simulate strategies, preview payoffs, and analyze the Greeks before trading. Explore protective puts, butterflies, iron condors, and straddles with payoff diagrams and Greeks.
Test your Knowledge

Common Execution Mistakes & Slippage2:52
Learn to prevent losses by mastering execution, slippage, and bid-ask spreads in options trading. Avoid market orders on illiquid options and wide spreads to protect your gains.
Market Orders & Limit Orders2:15
Use limit orders for most option trades to control price and reduce slippage. Reserve market orders for very liquid underlyings when speed matters, and always check the bid-ask spread.
Risk Mindset & Position Sizing2:32
Build a risk mindset with disciplined position sizing, risking 1 to 2% per trade and sizing for the worst case while reducing near expiration to manage gamma risk.
Test your Knowledge

Pulling Live Option Prices from Binance8:00
Pull live bitcoin option prices from Binance via the vanilla options websocket, stream data, and save to a csv for analysis to estimate implied volatility and build a volatility smile.
Structuring & Analyzing the Option Chain8:05
Structure a bitcoin option price csv into an option chain with underlying, expiry, strike, and type; filter by strike and expiry and track mark prices for implied volatility via Black-Scholes.
Test your Knowledge

Requirements

Basic understanding of Python (variables, functions, lists, plotting)
No prior options trading experience required — all core concepts are introduced from scratch
Interest in applying Python to real financial markets

Description

This course is designed to turn you into a confident, strategy-driven options trader—without wasting your time on fluff or outdated theory. You’ll learn how to apply options trading in the real world using Python and live market data from day one.

We start hands-on: building strategies, calculating Greeks, estimating implied volatility, and simulating payoffs based on actual prices from exchanges like Binance and Bybit. Whether you're a developer, trader, or finance student, this course equips you with the tools to move from theory to execution fast—and with confidence.

You'll cover all the fundamentals—calls, puts, payoffs, moneyness—but we don’t stop there. You’ll build full pricing models, calculate Greeks from scratch, and estimate implied volatility using both Brent’s method and Newton-Raphson. You’ll break down and simulate complex strategies like Iron Condors, Vertical Spreads, and Butterflies—and see how they play out using real data from real exchanges.

We even explore how options platforms visualize risk and payoffs—giving you a full perspective from code to market execution, and from simulation to strategy validation.

By the end of this course, you’ll be able to build, analyze, and understand real options trades—powered by Python, guided by real data, and grounded in strategy that works in today’s markets.

Who this course is for:

Finance students and professionals looking to understand and model options in a hands-on, practical way
Python users who want to apply their skills to options pricing, Greeks, and implied volatility
Traders who want to go beyond surface-level options theory and start building real strategies
Anyone who wants to learn how real-world options strategies work — from payoff structure to execution logic — using real market data

Options Trading: The Complete Guide to Greeks & Python Tools

What you'll learn

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Course content

Module 1 – Options Basics6 lectures • 15min

Module 2 – Option Pricing & Greeks8 lectures • 43min

Module 3 - Estimating Implied Volatility5 lectures • 23min

Module 4 - Option Strategies8 lectures • 54min

Module 5 - Execution & Risk Management3 lectures • 8min

Module 6 - Real Market Application & Final Project2 lectures • 16min

Requirements

Description

Who this course is for: