Description
QuantInsti – Options Trading Strategies In Python: Intermediate download, QuantInsti – Options Trading Strategies In Python: Intermediate review, QuantInsti – Options Trading Strategies In Python: Intermediate free
QuantInsti – Options Trading Strategies In Python: Intermediate
Profitable Options Trading strategies are backed by quantitative techniques and analysis. This course will teach you just how to do that. It is a part-1 of the two-course bundle that covers Options Pricing models, and Options Greeks, with implementation on market data using Python.
LEVEL
Intermediate
AUTHOR
NSE Academy
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LIVE TRADING
Backtest Options Trading strategies and use them to trade in live markets
Explain Options Greeks
Calculate the Options Price and Options Greeks
Visualize the payoff of Calendar Spread strategy
Predict movement of indices using implied volatility of the options
Backtest various volatility based trading strategies
Implement strategies in the live markets and analyze the performance
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LEARNING TRACK 3
This course is a part of the Learning Track: Quantitative Trading in Futures and Options Markets
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
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SYLLABUS
Options Pricing Models
This section introduces and explains the Black Scholes Model along with its formula and a Python package for options trading.
Course Introduction
Course Structure
Quantra Features & Guidance
Analogy to Pricing a Call Option: Dice Game
Expected Value of Payoff
Fair Value of Pricing a Game
Intuitive Explanation of Bsm Model
Components of BSM Formula
Strike Price in BSM Formula
Python Package for Options Trading
How to Use Jupyter Notebook?
Theoretical Price of Option
Theoretical Price of Option
Recap
Evolved Options Pricing Model
This section moves on to further explain other options pricing models like Derman-Kani Model and Heston Model.
Derman-Kani Model and Heston Model
Derman-Kani and Heston Models
Volatility Smile
Other Options Pricing Models
Options Greeks: Delta
This section includes a primer on Options Greeks with a special focus on the intuitive explanation of sensitivity of Delta.
Greeks Primer
Greeks Calculator
Greeks Calculator
Delta
Call Price
Delta Definition
Higher Delta Value
Delta of 0.5
Delta With Respect to Underlying Price
Delta With Respect to Underlying Price
Delta With Respect to Time to Expiry
Call Delta With Respect to Time to Expiry
Delta With Respect to Volatility
Delta With Respect to Volatility
Delta Sensitivity
Option Greeks: Gamma
This section focuses on how the delta changes, or the Gamma factor in option pricing.
Gamma
Calculate Delta
Options With Higher Gamma
Gamma Sensitivity
Properties of Gamma
Option Price Using Delta and Gamma
Option Greeks: Vega
The section involves the study of how volatility affects option pricing by discussing the greek Vega.
Vega
Calculate Price of Call Option
Option With Higher Vega
Option Price Using Vega
Vega With Respect to Time to Expiry and Vol
Vega Sensitivity
Option Greeks: Theta and Rho
This section focuses on the time to expiry and interest rates that influence option pricing. It also introduces some of the advanced Options Greeks concepts.
Theta
What Will Be the Call Price
What Drives the Theta of Option
Rho
Properties of Rho
Advanced Greeks
Recap
Options Trading Strategies
This section explains various options trading strategies like arbitrage strategy, calendar spread strategy, earnings strategy, box trading, and how to use them to trade in live markets. It also includes a case study on a strategy during the earnings announcement of the company.
Arbitrage Strategy
Calculate Call Price Using Put-Call Parity
Calculate Put Price Using Put-Call Parity
What is Calendar Spread
Calculate Calendar Spread Payoff
Greeks in Calendar Spread
Most Profitable Calendar Spread
Box Trading
Implement Box Spread Strategy
Long Box Spread Strategy
Implied Volatility in Earnings Strategy
Rise in Implied Volatility
Stock Price Movement in Earnings Strategy
Buying a Bull Call Spread
Recap
Run Codes Locally on Your Machine
Learn to install the Python environment in your local machine.
Python Installation Overview
Flow Diagram
Install Anaconda on Windows
Install Anaconda on Mac
Know your Current Environment
Troubleshooting Anaconda Installation Problems
Creating a Python Environment
Changing Environments
Quantra Environment
Troubleshooting Tips For Setting Up Environment
How to Run Files in Downloadable Section?
Troubleshooting For Running Files in Downloadable Section
Volatility Trading Strategies
This section covers strategies based on implied volatility with concepts of Forward Volatility, Volatility Smile and Volatility Skew.
Forward Volatility
Calculate the Daily Variance
Calculate the Monthly Variance
Strategy Using Forward Volatility
Forward Volatility Vs Near Month Volatility
Calculate Strategy Returns
Volatility Smile
Strategy Using Volatility Smile
Defining Binary Variables
Computing Cumulative PnL
Volatility Skew
Predicting Market Movement: Volatility Skew
Volatility Skew
Market Prediction
Volatility Skew Strategy Logic
Strategy Using Volatility Skew
Calculate ATM IV
Volatility Skew Calculation
Long Entry Position
Short Position
Calculate ATM Strike Price
Compute Volatility Skew
Calculate Strategy Returns
Calculate Compounded Returns
Additional Reading on Volatility Skew
Recap
Test on Options Trading Strategies
Live Trading on IBridgePy
Section Overview
Live Trading Overview
Vectorised vs Event Driven
Process in Live Trading
Real-Time Data Source
Code Structure
API Methods
Schedule Strategy Logic
Fetch Historical Data
Place Orders
IBridgePy Course Link
Additional Reading
Paper and Live Trading
In this section, a live trading strategy template will be provided to you. You can tweak the strategy template to deploy your strategies in the live market!
Template Documentation
Template Code File
Wrapping Up!
This section summarises the course and provides downloadable strategy codes.
Summary
Python Codes and Data
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