| Module 1: Introduction & Core Concepts |
| Introduction: Course overview, structure, and interactive learning tools. |
| Options Volatility: Fundamentals of volatility behaviour and trading opportunities. |
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| Sourcing Data: Importance of data, sourcing/storing in pickle files, and available sources. |
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| Options Pricing: Black-Scholes-Merton model, its assumptions, and alternative pricing models. |
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| Deliverable: Starter notebook with data sourcing and BSM model examples. |
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| Module 2: Volatility Skew & Surfaces |
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| Volatility Skew: OTM puts vs calls, IV differences, plotting skew. |
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| Kinks in Volatility Surface: Why surfaces aren’t always smooth, irregularities, and trading limitations. |
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| Calculation of Volatility Skew: Objective methods and interpretation. |
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| Trading Volatility Skew: Hypothesis formation, backtesting skew-based strategies, performance analysis. |
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| Deliverable: Volatility skew analysis notebook. |
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| Module 3: Delta-Neutral & Volatility Strategies |
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| Delta Neutral Skew Analysis: Using delta vs average OTM IVs, trading delta-neutral skew. |
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| Volatility and Mean Reversion: Mean-reversion behaviour of volatility, why it doesn’t trend like prices, and trading strategies. |
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| Trading Strategy on VIXY Using VIX: VIX index insights, VIXY ETF, and applying mean reversion to short VIXY strategies. |
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| Deliverable: Delta-neutral and VIXY trading strategy backtest. |
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| Module 4: Ranks & Advanced Forecasting |
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| IV Rank: Intuition and calculation, context of IV values. |
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| IV Rank in Trading: Strategy creation, backtest, and performance. |
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| Skew Rank: Intuition, calculation, and combining IV & Skew Rank. |
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| Skew Rank in Trading: Short Straddle Strategy – IV Rank and Skew Bank. |
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| Forecasting IV Using Machine Learning: Using multiple variables, ML-driven predictions. |
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| LSTM’s Role in Forecasting IV: LSTM for IV forecasting, trading strategies on predicted IV. |
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| Deliverable: Forecasting and rank-based strategy generator. |
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| Module 5: Event-Driven Volatility & Options Pricing |
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| Volatility Around Events: Historical patterns, pre-event volatility surges, and event-driven strategies. |
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| Volatility and Options Pricing: Impact of volatility on option pricing and trading. |
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| Relative View on Volatility: Long calendar spread strategy, backtest, and performance analysis. |
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| Deliverable: Event-driven volatility strategy backtest notebook. |
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| Module 6: Risk Management & Hedging |
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| Risk Management of a Volatility Position: Dollar-based risk management. |
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| Risk Management Using Option Greeks: Managing risk through Greeks in volatility positions. |
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| Hedging the Option Greeks: Example of hedging a short straddle with Greeks. |
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| Risk Management Using Delta Hedging: Concept and application in short straddle. |
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| Threshold for Delta Hedging: Selective hedging to reduce transaction costs. |
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| Implementation of Delta Hedging: Selective delta hedging in Python. |
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| Hedging an Options Portfolio Using Greeks: Portfolio-level hedging across multiple assets. |
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| Summary: Recap of learnings, with downloadable code and data. |
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| Deliverable: Risk management and hedging implementation notebook. |
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| Capstone Project 1: Strategy Deployment and Analysis |
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| In this project, you will apply all the concepts you have learned to design, test, and evaluate a trading strategy. You will: |
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| Deploy a short strangle strategy. |
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| Backtest it on historical data. |
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| Analyse the strategy’s performance using key metrics. |
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| Deliverable: A complete backtest notebook with performance analysis. |
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| Capstone Project 2: Risk Management of an Options Volatility Position |
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| This project challenges you to tackle risk management in a practical setting. You will be presented with a problem statement related to managing the risks of an options volatility position. Along with this, you will receive a solution template to guide your work and a model solution for reference. |
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| Deliverable: A risk management notebook and a completed template with your solution. |
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