Advanced Options Volatility Trading: Strategies and Risk Management
No Cost EMI available
- Live Trading
- Learning Track
- Prerequisites
- Syllabus
- About author
- Testimonials
- Faqs
Live Trading
- Comprehend the foundational aspects of trading options volatility, the role of options pricing models, and the relationship between IV and the price of an option.
- Evaluate the concept of skew and mean-reversion in volatility. Calculate IV skew, IV rank, skew rank and delta neutral skew.
- Develop entry and exit trading signals by using volatility properties, using machine learning models or by exploiting volatility behaviour surrounding events such as FOMC meetings.
- Design and backtest options trading strategies, including straddles and calendar spreads. Analyse performance and conduct trade-wise analysis.
- Manage the risk of options portfolios using Greeks and implement risk management techniques, such as dollar-based risk management and delta hedging.
Skills Covered
Python
- Pandas
- NumPy
- Sklearn
- Talib
- Matplotlib
Concepts & Trading
- Delta-neutral Skew
- IV Rank and Skew Rank
- LSTM
- Options Portfolio Hedging
Options Strategies
- Calendar Spread
- Long/Short Straddle
- Delta Hedging
- Volatility around FOMC meetings
learning track 3
This course is a part of the Learning Track: Quantitative Trading in Futures and Options Markets
Course Fees
Full Learning Track
These courses are specially curated to help you with end-to-end learning of the subject.
Course Features
CommunityFaculty Support on Community
- Interactive Coding Exercises
Interactive Coding Practice
- Capstone Project
Capstone Project Using Real Market Data
- Trade & Learn Together
Trade and Learn Together
- Get Certified
Get Certified
Prerequisites
Fluency with Python, including Python libraries like Pandas, Numpy, and Matplotlib. Awareness of the basics of options, such as call and put options, option Greeks 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 our course on ‘Options Trading Strategies: Basics’ if you are not familiar with options.
Syllabus
- IntroductionThis section provides an overview of the course and outlines its contents. The interactive methods employed will help you grasp the concepts and address all your questions about options volatility trading. It details the course structure and the various teaching tools used, including videos, quizzes, coding exercises, and the capstone project.
- Overview of VolatilityIn this section, you will be taken through a brief overview of the concepts covered in the first part of the course along with some basic but essential concepts of volatility.Part Overview on Volatility and Its Properties2m
Volatility2m
What is Volatility?2m
Implied Volatility2m
Historical vs Realised Volatility2m
Options VolatilityHere, you will be introduced to the fundamentals of trading options volatility. Upon completing this section, you will understand typical volatility behaviour and how options traders can exploit this behaviour.
Why Trade Options Volatility?2m
Trading Volatility Instead of Direction5m
Implied Volatility vs Realised Volatility5m
Volatility Characteristics5m
Mean Reversion of Volatility5m
Behaviour of Volatility5m
Volatility Around Events5m
Characteristics of Volatility2m
Volatility and Returns5m
Volatility and Mean Reversion5m
Volatility and Volatility-of-Volatility5m
Predicting Near-Future Volatility5m
Volatility and Its Characteristics5m
FAQs on Options Volatility2m
Additional Reading on Options Volatility2m
- Sourcing DataData is an important part of options trading, as it provides the foundation for making informed decisions and executing strategies. In this section, you will learn about the data necessary for options trading. You will also learn how to source and store this data in a pickle file. Finally, you will be provided with a few sources to procure options data as well as data for other assets.Option Type and Applicability2m
Sourcing US Options Data2m
How to Use Jupyter Notebook?2m 5s
Working With Pickle File5m
Options Data Storing5m
Other Assets Data5m
Data Vendors2m
Data Preprocessing2m
Incorrect Values5m
Pre-Processing Data5m
- Options PricingDid you know that the Black-Scholes-Merton model, introduced in 1973, revolutionised financial markets by providing a systematic method to price European options? In this section, you will learn about the role of options pricing models and why traders use them. You will also gain an intuitive understanding of the Black-Scholes-Merton (BSM) model and its assumptions. Additionally, you'll explore some other models developed to address the limitations of the BSM model.Understanding Options Pricing2m
Role of an Options Pricing Model5m
Standard Normal Cumulative Distribution Function5m
Reason for Limited Gain5m
Volatility and Options' Price5m
Discounted Value of the Strike Price5m
Assumptions of BSM2m
Identify the Assumption5m
Exercising an Option5m
Volatility Skew in an Options Pricing Model5m
Identify the Appropriate Factor5m
IV Calculation5m
Calculate Implied Volatility5m
FAQs on Options Pricing2m
Additional Reading on Options Pricing2m
Test on Options Volatility and Pricing12m
- Volatility SkewVolatility skew occurs because the implied volatility of out-of-the-money put options is more than out-of-the-money call options. Notice why implied volatility varies for options with different strike prices and plot the volatility skew.
Why is Volatility Skewed?2m
Difference Between Historical and Implied Volatility5m
Assumption of Black Scholes Model5m
Impact of 1987 Crash on Option Pricing5m
Plotting the Volatility Surface2m
Volatility Skew and Option Pricing5m
Skew in Equity and Gold5m
Representation of X Axis on Volatility Surface5m
Plotting IV Surface5m
ATM Strike Price5m
Analysis of IV Skew5m
Gap in Skew Plot5m
- Kinks in Volatility SurfaceThe volatility surface is not a smooth curve all the time. Discover how and why certain irregularities appear on the volatility surface and learn their implications for trading. Understand the limitations of the usage of kinks for creating a trading strategy.Kinks in the Volatility Surface2m
Concept of Kinks5m
Appearance of Kinks5m
Trading Based on Kinks in Volatility Skew2m
Identification of Kinks5m
Action Based on Kinks5m
Inability of Retail Traders to Trade Kinks5m
- Calculation of Volatility SkewObserving the volatility surface to find the volatility skew is not the right approach. Learn to objectively calculate volatility skew and interpret its significance.
Calculation of Volatility Skew2m
Meaning of Volatility Skew5m
Importance of Quantifying Volatility5m
OTM Options in Volatility Skew Calculation5m
Range Selection of OTM Options5m
Limitation of Advanced Approach5m
Standardised Skew Value Calculation5m
Importance of Standardised Skew Values5m
Interpretation of Volatility Skew2m
Interpretation of Volatility Skew5m
Positive Skew and Market Participants5m
Interpretation of Negative Skew5m
Factors Affecting Volatility Skew5m
Use of Volatility Skew in Trading5m
Calculating Volatility Skew5m
Compute Volatility Skew5m
Strike Price Selection5m
Additional Reading2m
- Trading Volatility SkewVolatility skew analysis can provide you with information which can be used to create an effective trading strategy. Form the trading hypothesis and backtest the volatility skew based strategy in this section. Analyse the strategy performance as well.Trading Volatility Skew2m
Skew Value of 05m
Increase in Positive Skew5m
Contrarian Trading Strategy5m
Trading Volatility Skew5m
Contrarian Approach5m
Market’s Perception of Risk5m
Skew Threshold5m
Long Entry and Exit Signals5m
FAQs2m
- Delta Neutral Skew AnalysisUsing a range of options and finding the average OTM Put IV and OTM Call IV to calculate the volatility skew is a sound idea. But are there any other methods? Use the options Greek, Delta, to identify the optimal OTM Put and OTM Call options for calculating skew value and trading accordingly.Delta Neutral Skew2m
Delta in Options Trading5m
Similar Options Delta in Analysis5m
Calculation of Delta Neutral Skew2m
Calculation of Delta Neutral Skew5m
Trading Volatility Skew - Delta based Approach5m
Closest Delta5m
Short Entry and Exit Signals5m
Additional Reading2m
Summary2m
Test on Volatility Skew20m
- Volatility and Mean ReversionThe concept of mean reversion states that the variable will always return to a mean. Is volatility really mean-reverting? Why doesn’t volatility keep rising, or decline like a stock price? Find the answer to all these questions and explore strategies to trade on this behaviour.Mean Reversion Property of Volatility2m
Existence of VIX5m
VIX and Fear5m
Mean Reversion of VIX5m
Trading VIX5m
Alternative to Trading VIX Derivatives5m
Analysis of VIXY2m
Components of VIXY5m
Decrease in VIXY5m
Risk of Shorting VIXY5m
Correlation Between VIX and VIXY2m
VIX and VIXY Correlation5m
Use of Log Scale5m
Trading Action5m
Additional Reading2m
- Trading Strategy on VIXY Using VIXThe Volatility Index (VIX) gives insights into the market’s expectation of implied volatility. Since the VIX cannot be traded directly, we have VIX-based futures and options, and an ETF called VIXY ETF. Apply the concept of mean reversion to determine optimal short positions on VIXY.How to Trade VIXY Using VIX2m
Peak VIX5m
VIX values for Analysis5m
Highest Quartile5m
RSI Indicator Time Period5m
Exit Rules of Trading VIXY2m
Decision to Short VIXY5m
RSI Levels and Entry Signal5m
Interpretation of VIX Value and First Quartile5m
Exit Signal and First Quartile5m
Conditions for Entry Signal5m
VIX - Mean Reversion Strategy5m
RSI Values5m
Calculate the Percentile5m
FAQs2m
Summary2m
Additional Readings2m
- Limitations of Mean Reversion StrategyThe mean reversion properties of volatility can be traded, but are there any limitations to this approach? This section lists and explains the limitations of trading the mean reversion property of volatility.Limitations of Trading Volatility Mean Reversion2m
VIX Moves up After Taking a Short Position5m
Need for Optimised Entry and Exit Prices5m
Effect of Volatility Clustering5m
Risk of Higher Leverage5m
Geopolitical Events and Macroeconomic Reports5m
Limitations of Trading the Mean Reversion Property5m
Conditions to Monitor When Trading Mean Reversion5m
Additional Reading on Limitations of Mean Reversion Strategy2m
Test on Mean Reversion Property of Volatility18m
- IV and Options PremiumWhile trading volatility, it is essential to understand its impact on options pricing. In this section, you will learn how volatility can affect your trades by understanding the relationship between volatility and the price of an option.Part Overview: Trading Volatility using Straddle and Spread2m
Effect of Volatility on Options' Prices2m
Intrinsic Value of Call5m
Implied Volatility after Earnings Release5m
Implied Volatility after Earnings Release5m
Failure of John's Trade5m
Impact of High Implied Volatility5m
Decline in Implied Volatility5m
FAQs on IV and Options Premiums2m
Additional Reading on Effect of Volatility2m
- IV RankKnowing the IV values may not always be enough. You should also know how high or low is the IV value in relation to the recent past range of IV values. Grasp the intuition and calculation of IV rank, and learn how it can be utilised in options trading.
Importance of IV Rank2m
Limitation of Implied volatility5m
Relation Between IV and Short Straddle5m
Higher Current IV Relative to Past5m
Higher IV rank5m
Calculation of IV Rank2m
Purpose of IV rank5m
Standard Time Period for Comparison of IV Values5m
Denominator in IV Rank Formula5m
Numerator in IV Rank Formula5m
Minimum IV Rank Value5m
Maximum IV Rank Value5m
IV Rank Calculation5m
Calculate Rolling Minimum Values5m
Calculate IV Rank5m
- IV Rank in TradingThe IV rank can help you determine the current IV value stands in relation to its past values. This information can be utilised to create and backtest a trading strategy. Analyse the entry and exit rules of an IV Rank-based trading strategy and evaluate its performance.IV Rank in Trading2m
Interpretation of High IV Rank5m
Trading Implication of High IV Rank5m
Interpretation of Low IV Rank5m
Strategy Based on Low IV Rank5m
IV Rank Based Short Straddle Strategy5m
Entry Signals for Short Straddle5m
Exit Signals for Short Straddle5m
FAQs2m
Additional Reading2m
Summary2m
- Skew RankSimilar to the IV rank, the skew rank tells you if the current skew value is high or low in comparison to the recent past range of values. Understand the intuition and calculation of skew rank, and learn how to combine IV rank and skew rank to formulate an options trading strategy.
Meaning of Skew Rank2m
Skew Rank5m
Similarity Between Skew Rank and IV Rank5m
Historical Range of Skew Values5m
Range of Skew Values5m
Example of Skew Value5m
Calculation of Skew Rank2m
Skew Rank Formula5m
Calculation of Skew Rank5m
Option's Skew Value5m
Skew Rank5m
Current Skew Value and Historical Skew Values5m
Skew Rank Calculation5m
Calculate Rolling Maximum Values5m
- Skew Rank in TradingCan the inclusion of two variables enhance the performance of an existing strategy which used only one variable? You will learn how to integrate the IV rank and skew rank in creating and optimising an options trading strategy.Using IV Rank and Skew Rank in Trading2m
Strategy for IV rank5m
Exit Short Straddle5m
Low Skew Rank5m
Mean Reversion in Volatility for Trading5m
Short Straddle Strategy - IV Rank and Skew Rank5m
IV Rank Exit5m
Skew Rank Exit5m
FAQs2m
Additional Reading2m
Summary2m
Test on IV Rank and Skew Rank20m
- Capstone Project on StrangleIn this section, you will apply the knowledge you have gained in the course. You will pick up a capstone project where you will deploy a short strangle, backtest it and analyse the strategy performance.Getting Started2m
Problem Statement2m
Capstone Project Model Solution5m
Strangle Capstone Data Files2m
- Forecasting IV Using Machine LearningYou will explore the integration of multiple variables to predict implied volatility through the application of machine learning models. By examining the principles of data-driven decision-making in machine learning, you will evaluate its effectiveness in forecasting implied volatility.Need for Forecasting IV Using ML2m
Limitation of IV Rank for Short Straddle5m
Variables and Volatility Prediction5m
Machine Learning and Trading Strategies5m
Features and Target Variables2m
Strike Prices and Prediction of IV5m
Stationary Features5m
Significance of Scaling5m
Application of Technical Indicators5m
Usage of Days to Expiry Feature5m
Forecasting IV Using LSTM - Features and Target Variable5m
Calculate the ADX Indicator5m
Create the Target Variable5m
- LSTM's Role in Forecasting IVThe LSTM model is a good candidate to forecast implied volatility values. You will learn how the LSTM model is set up and further create a trading strategy based on the predicted implied volatility values.How to Setup the LSTM Network2m
Dimensions of Input Data5m
Role of Time Steps5m
Multiple LSTM Layers5m
Loss Function and Optimiser5m
Forecasting IV Using LSTM - Predictions5m
Trade Using Forecasted IV2m
Threshold for Exit5m
Threshold for Entry5m
Set Trading Signal5m
Short Straddle Gains5m
Short Straddle-Forecasted IV5m
Entry Signals Based on Predicted IV5m
Exit Signals Based on Predicted IV5m
FAQs2m
Additional Reading2m
- Forecasting IV Using LSTM: Challenges and LimitationsIn this section, you will be taken through the challenges often faced while using LSTM and the limitations that it is exposed to.Challenges and Limitations of Forecasting IV Using LSTM2m
Real-Time Trading5m
Poor Performance of LSTM Model5m
Unpredictable Future Events5m
Issue of Delay in Processing5m
Retraining an LSTM Model5m
Additional Reading on Challenges of Forecasting IV Using LSTM2m
Test on LSTM14m
- Volatility Around EventsUsually, the implied volatility (IV) changes in anticipation of significant events. By evaluating historical data, you will identify patterns of volatility changes preceding events. Further, you will synthesise this information to develop and apply a trading strategy tailored to capture the pre-event volatility surges.Volatility Around Events2m
Application of Mean Reversion5m
Predictable Events5m
IV and FOMC Meeting5m
IV Increase and Options strategy5m
Entry and Exit Rules of Event Based Volatility2m
Long Straddle and FOMC Meeting5m
Long Straddle Before FOMC Meeting5m
Exit of Long Straddle5m
Volatility Rush5m
Trade Volatility Around Events5m
Long Straddle Entry5m
Unique Expiry Dates5m
FAQs2m
Additional Readings2m
Summary2m
- Relative View on VolatilityHere, you'll learn how to trade around events by developing a relative view on volatility, that is, by having an idea of how volatility might change over time. We’ll break down a popular strategy called the long calendar spread, and understand how to set it up.
Long Calendar Spread Strategy2m
Objective of Long Calendar Spread5m
Calendar Spread Positions5m
Vega Comparison5m
Impact of Theta5m
Significance of Greeks5m
Constructing Calendar Spread5m
Impact on Premiums5m
Impact on the Spread5m
- Trading Based on a Relative ViewAfter learning how to set up the long calendar spread strategy, it is now time to implement it! In this section, you will learn how to implement the strategy based on the defined entry and exit rules. You will also learn how to backtest it and analyse its performance.Trading the Long Calendar Spread Around Events2m
Objective of Long Calendar Spread5m
Selecting the Asset5m
Ideal Scenario5m
Entry Rules5m
Exit Rules5m
Selecting the Expiries5m
Calendar Spread Strategy5m
FAQs on Long Calendar Spreads2m
Additional Reading on Calendar Spreads2m
Test on Volatility Around Events16m
- Risk Management of a Volatility PositionIt’s very important to understand the risk of an options trading strategy and take steps to manage the risk. This section focuses on the need for risk management of an options volatility position and also explains the ‘dollar-based risk management’ method to manage the risk.Part Overview: Risk of a Volatility Position2m
Need for Risk Management2m
Long-Term Capital Management Case5m
The Objective of Risk Management5m
Impact of Rising Volatility5m
Price Movement Expectation5m
Risk of Price Increase5m
Major Sources of Risk5m
- Managing Risk of a Volatility PositionThis section focuses on implementing dollar-based risk management for a short straddle position using Python.How to Manage Risk2m
Stop-Loss Strategy5m
Take-Profit Strategy5m
Dollar-Based Risk Management Definition5m
Setting Stop-Loss and Take-Profit5m
Volatility Decline Scenario5m
Apply Dollar-Based Risk Management5m
Dollar-Based Risk Management5m
Compute the Stop-Loss5m
Exit Conditions5m
Additional Reading on the Risk of a Volatility Position2m
FAQs on the Risk of a Volatility Position2m
Summary of Risk of a Volatility Position2m
Test on Risk of a Volatility Position16m
- Risk Management Using Option GreeksThis section explains the intuition behind managing the risk of a volatility position using options Greeks. After completing this section, you will be able to explain the need to include Greeks in your study to manage the risk of options position effectively.Pre-Reading on Option Greeks2m
Need to Study Greeks for Risk Management2m
Impact of Market Volatility on Options5m
Profit from Short Straddle5m
Impact of a Sharpe Move on a Short Straddle5m
Loss Trade Despite Expected Market Move5m
Consideration of Options Greeks5m
Effect of Options Greeks on a Volatility Position2m
Need for Options Greeks in Risk Management5m
Impact of Gamma on Delta5m
Impact of Vega on Premium5m
Impact of Theta on Short Straddle5m
Impact of Delta on Short Straddle5m
Managing Options Greeks5m
Additional Reading to Risk Management Using Greeks2m
FAQs on Risk Management Using Greeks2m
Summary of Risk Management Using Options Greeks2m
- Hedging the Option GreeksHedging is the technique used to manage the risk of an options position by studying the options Greeks. This section explains the concept of risk management by hedging the option Greeks. After completing this section, you will be able to explain how hedging of a short straddle position can be done using option Greeks.Risk Management Using Hedging2m
Hedging Impact on PnL5m
Should You Perform Hedging?5m
Impact of Hedging on Profit Potential5m
Which Greek to Hedge in Short Straddle?5m
Delta Hedging Example5m
Test on Risk Management Using Option Greeks, Hedging14m
- Risk Management Using Delta HedgingDelta hedging is used to hedge the impact of the options Greek, delta, on an options position. This section explains delta hedging and how the risk of an options volatility position is managed using delta hedging with an example of short straddle.What is Delta Hedging?2m
Purpose of Delta Hedging5m
Non-Tradable Underlying5m
Delta of Futures Contract5m
Adjusting Delta Hedging5m
Delta Hedging Scenario5m
What is Dynamic Delta Hedging?2m
Impact of Continuous Hedging5m
Dynamic Delta Hedging with a Threshold5m
Hedging with a Threshold for Decline5m
Continuous Hedging Without a Threshold5m
Hedging a Short Straddle5m
Additional Reading on Risk Management Using Delta Hedging2m
FAQs on Risk Management Using Delta Hedging2m
- Threshold for Delta HedgingTo avoid higher transaction costs due to continuous hedging, selective hedging can be done by defining a threshold for delta to hedge. This section explains the techniques to decide the suitable delta threshold to use for hedging.How to Define Delta Threshold2m
Reason to Avoid Continuous Hedging?5m
Alternative to Continuous Hedging?5m
Hedge With a Threshold of Delta5m
Do you hedge?5m
Find the Issue With Hedging5m
Additional Reading on Threshold of Delta for Hedging2m
Summary of Threshold of Delta for Hedging2m
- Implementation of Delta HedgingThis section explains the implementation of selective delta hedging on a short straddle strategy. After completing this section, you will be able to implement delta hedging in Python.Implementation Of Delta Hedging2m
Impact on PnL5m
Threshold Selection5m
Delta of a Short Straddle5m
Delta Threshold Decision5m
Hedging Frequency5m
Delta Hedging5m
FAQs on the Implementation of Delta Hedging2m
Summary of Implementation of Delta Hedging2m
- Hedging an Options PortfolioThe risk of a portfolio with multiple options strategies on multiple assets can be hedged using options Greeks. After completing this section, you will be able to explain how to hedge an options portfolio with an example.How to Hedge An Options Portfolio?2m
Understanding the Greeks5m
Calculating Delta Impact5m
Hedging an Options Portfolio5m
Hedging Delta5m
Portfolio Risk Management Using Delta5m
Additional Reading on Hedging an Options Portfolio2m
FAQs on Hedging an Options Portfolio2m
Test on Delta Hedging and Hedging an Options Portfolio14m
- Capstone Project on Risk ManagementIn this section, you will be presented with a problem statement on risk management of an options volatility position. You will also be given a solution template and model solution to complete the capstone project.Problem Statement2m
Risk Management Capstone Solution5m
Risk Management Capstone Data Files2m
- Run Codes Locally on Your MachineLearn to install the Python environment in your local machine.Uninterrupted Learning Journey with Quantra2m
Python Installation Overview1m 59s
Flow Diagram10m
Install Anaconda on Windows10m
Install Anaconda on Mac10m
Know your Current Environment2m
Troubleshooting Anaconda Installation Problems10m
Creating a Python Environment10m
Changing Environments2m
Quantra Environment2m
Troubleshooting Tips for Setting-up Environment10m
How to Run Files in Downloadable Section?10m
Troubleshooting For Running Files in Downloadable Section10m
- Live Trading on IBridgePyIn this section, you would go through the different processes and API methods to build your own trading strategy for the live markets, and take it live as well.Section Overview2m 2s
Live Trading Overview2m 41s
Vectorised vs Event Driven2m
Process in Live Trading2m
Real-Time Data Source2m
Code Structure2m 15s
API Methods10m
Schedule Strategy Logic2m
Fetch Historical Data2m
Place Orders2m
IBridgePy Course Link10m
Additional Reading10m
Frequently Asked Questions10m
- Paper/Live Trading TemplateTo make sure that you can use your learning from the course in the live markets, a live trading template has been created which can be used to paper trade and analyse its performance. This template can be used as a starting point to create your very own unique trading strategy.Template Documentation10m
Template Code Files2m
- SummaryIn this section, we will summarise all the learning from the course. All the data files and code used in this course can be downloaded from the downloadable unit of this section.Course Summary2m
Summary and Next Steps2m
Python Codes and Data2m
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Faqs
- When will I have access to the course content, including videos and strategies?
You will gain access to the entire course content including videos and strategies, as soon as you complete the payment and successfully enroll in the course.
- Will I get a certificate at the completion of the course?
Yes, you will be awarded with a certification from QuantInsti after successfully completing the online learning units.
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No, there are no live or classroom sessions in the course. You can ask your queries on community and get responses from fellow learners and faculty members.
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Yes, you can ask your queries related to the course on the community: https://quantra.quantinsti.com/community
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Fast-speed internet connection and a browser application are required for this course. For best experience, use Chrome.
- What is the admission criteria?
There is no admission criterion. You are recommended to go through the prerequisites section and be aware of skill sets gained and required to learn most from the course.
- Is there a refund available?
We respect your time, and hence, we offer concise but effective short-term courses created under professional guidance. We try to offer the most value within the shortest time. There are a few courses on Quantra which are free of cost. Please check the price of the course before enrolling in it. Once a purchase is made, we offer complete course content. For paid courses, we follow a 'no refund' policy.
- Is the course downloadable?
Some of the course material is downloadable such as Python notebooks with strategy codes. We also guide you how to use these codes on your own system to practice further.
- Can the python strategies provided in the course be immediately used for trading?
We focus on teaching these quantitative and machine learning techniques and how learners can use them for developing their own strategies. You may or may not be able to directly use them in your own system. Please do note that we are not advising or offering any trading/investment services. The strategies are used for learning & understanding purposes and we don't take any responsibility for the performance or any profit or losses that using these techniques results in.
- I want to develop my own algorithmic trading strategy. Can I use a Quantra course notebook for the same?
Quantra environment is a zero-installation solution to get beginners to start off with coding in Python. While learning you won't have to download or install anything! However, if you wish to later implement the learning on your system, you can definitely do that. All the notebooks in the Quantra portal are available for download at the end of each course and they can be run in the local system just the same as they run in the portal. The user can modify/tweak/rework all such code files as per his need. We encourage you to implement different concepts learnt from different learning tracks into your trading strategy to make it more suited to the real-world scenario.
- If I plug in the Quantra code to my trading system, am I sure to make money?
No. We provide you guidance on how to create strategy using different techniques and indicators, but no strategy is plug and play. A lot of effort is required to backtest any strategy, after which we fine-tune the strategy parameters and see the performance on paper trading before we finally implement the live execution of trades.
- What does "lifetime access" mean?
Lifetime access means that once you enroll in the course, you will have unlimited access to all course materials, including videos, resources, readings, and other learning materials for as long as the course remains available online. There are no time limits or expiration dates on your access, allowing you to learn at your own pace and revisit the content whenever you need it, even after you've completed the course. It's important to note that "lifetime" refers to the lifetime of the course itself—if the platform or course is discontinued for any reason, we will inform you in advance. This will allow you enough time to download or access any course materials you need for future use.
- Why do we need to learn about volatility to trade options?
Understanding volatility provides an advantage by allowing traders to align their trading strategies with market conditions, effective risk management and portfolio diversification.
- On which assets can the learnings from this course be implemented?
There are two main types of options: American and European. European options can only be exercised at expiration, unlike American options, which can be exercised at any time before expiration. You can apply the knowledge from this course to European options.
We have used the SPX index options as an example in the course. The principles and strategies you learn can be applied to any European options, no matter where they are traded. So, whether you are dealing with European options on assets in the US, Europe, or any other region, the learnings from this course will be relevant and useful. Just ensure there is enough trading activity (liquidity) in the asset you are working with to implement these strategies effectively.
- What datasets are used in the course?
We have used the following datasets:
- Daily SPX End-Of-Month options chain data for a period of 9 years, starting from 2015 to 2023.
- Daily VIX and VIXY data from 2014 to 2024
- Daily S&P 500 index data from 2015 to 2023
- Which strategies are covered in the course?
1. Volatility skew-based trading
2. Trading on IV mean-reversion
3. Short straddle based on IV rank and skew rank
4. Short straddle based on LSTM forecasted IV values
5. Long straddle around events
6. Long calendar spread around events
7. Risk management using stop-loss and take-profit
8. Implementation of delta hedging
- Should I enrol in this course if I have already enrolled in other options/volatility courses on Quantra?
Yes! This course is a blend of options and volatility trading, it explains the core concepts and properties related to volatility, and takes you through the implementation of options trading strategies based on volatility. It is different from other options/volatility courses because unlike other courses, this course focuses more on strategy implementation. It also covers risk management using dollar-based stop-loss and take-profit as well as risk management using Greeks. By taking this course, you'll gain a unique perspective and expand your knowledge in this specialised area, complementing what you have already learned from other courses.
- Are there any sources for options data?
There are many data vendors that provide services for options data and these could either be free or paid. The options data provided in this course was obtained from the vendor OptionsDX. Link.
However, do note that QuantInsti is not affiliated with OptionsDX and before getting the data from any vendor, it is essential that traders carry out necessary research about that vendor.
- Which brokers are illustrated in the course for live trading or paper trading?
We cover a generic framework for you to work with the broker of your choice. You can look for your broker in the list provided on this page and find out which broker/platform you can use to automate your strategies. If your broker is not listed here you can check the broker’s Python package or Rest API.
In this course, we have provided live trading templates that can be used to automate trading strategies with “Interactive Brokers LLC” using the IBridgePy python package.
You can also watch this webinar to explore integration with various other brokers & platforms.
- What are the prerequisites of this course?
The basics of both options trading and Python are not covered in this course. To develop foundation knowledge on options trading you can enrol to the “Options Trading Strategies: Basic” course on Quantra. To familiarise yourself with Python you can enrol in the “Python for Trading: Basic” course. You should have working knowledge of options such as delta, gamma, theta and vega.
- Will there be assessments or projects?
Yes, there will be periodic quizzes, assignments, and capstone projects to evaluate your understanding and application of the course material.