Course Overview
Looking to explore the world of options volatility trading? This course has got you covered! Dive into topics like options Greeks, volatility estimators (Garman-Klass and Parkinson), GARCH modelling, and analysing PnL distribution for popular strategies like straddles and strangles. With a hands-on capstone project and a live trading template, you’ll gain practical experience applying these concepts in real-life scenarios. Join us on this options volatility trading journey today!
Live Trading
Recall and differentiate between risk and edge in options trading.
Explain the concepts and characteristics of options Greeks, including Delta, Theta, Rho, Vega, and Gamma.
Demonstrate an understanding of volatility estimation techniques, including close-to-close, Parkinson, and Garman-Klass estimators.
Explain the GARCH model and its application in forecasting volatility.
Apply Monte Carlo simulation to estimate the profit and loss (P/L) distribution of straddle and strangle options positions.
Backtest and evaluate a volatility-based options trading strategy using historical data.
Utilise capstone project and live trading templates to implement learned concepts in real-world trading scenarios.
Skills Covered
Strategies
GARCH Model-based strategy
VIX-based Straddle
Concepts & Trading
Options Greeks
Volatility Estimation
GARCH
Monte-Carlo Simulation
Python
Pandas
Numpy
Matplotlib
Mibian
Scipy
Learning Track 7
This course is a part of the Learning Track: Quantitative Trading in Futures and Options Markets Enroll to the entire track to enable 30% discount.
Foundation
Options Trading Strategies In Python: Basic
Beginner
Futures Trading: Concepts & Strategies
Intermediate
Options Trading Strategies In Python: Intermediate
Systematic Options Trading
Trading using Options Sentiment Indicators
Advanced
Options Trading Strategies In Python: Advanced
Options Volatility Trading: Concepts and Strategies
Course Features
Faculty Support on Community
Interactive Coding Practice
Capstone Project Using Real Market Data
Trade and Learn Together
Get Certified
Prerequisites
Fluency with Python including Python libraries like Pandas, Numpy, Matplotlib and a good understanding of financial markets. You can enrol for the Python for Trading: Basic course on Quantra to attain a basic level of understanding of Python. You can also check the Stock Market Basics course for understanding financial market terms.
Syllabus
Introduction
Edge and Risk
American vs European Options
Put and Call Parity
Pricing Models
Options Valuation
Greeks: Price & Time
Greeks: Volatility and Interest Rates
Volatility
Implied Volatility
Close-to-Close Estimator
Parkinson Estimator
Garman-Klass Estimator
Volatility Estimators
Volatility Forecasting
How to Trade Variance Premium
P/L Distribution of Options Strategies
Monte Carlo Simulation
Practical Hedging
Capstone Project
Live Trading on IBridgePy
Paper and Live Trading
Run Codes Locally on Your Machine
Summary
About Author
Dr Euan Sinclair has over 27 years of experience in the industry and specialises in the design, implementation, and risk management of quantitative trading strategies. He has worked with various trading firms like Bluefin Trading, Hull Tactical, Medway Capital Management, Trađing Solutions Ltd, and The Helios Group. He was the co-founder and CEO of FactorWave lnc (a fintech company) and a managing partner at Talton Capital Management (a volatility hedge fund). He is also a member of the editorial board of the Journal of Investment Strategies, a publication of Risk Journals. All three of his books: Options Trading, Volatility Trading and Positional Option Trading, have been warmly received by the community.
Why Quantra ?
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Get taught by practitioners
Learn at your own pace
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