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(Courses on)# Options trading strategies in python

An ultimate guide to learning basic as well as advanced options trading strategies and automating them using Python programming.

course 1

course 2

course 1### Intermediate

#### Section 1: Options Pricing Models

#### Section 2: Evolved Options Pricing Models

#### Section 3: Options Greeks

#### Section 4: Options Trading Strategies

#### Section 5: Volatility Trading Strategies

Understand popular options pricing model, the Black Scholes Model. Learn to implement the python package useful for options trading and use it to compute the theoretical price of an option.

Learn other options pricing models such as Derman Kani Model and Heston Model. These models provide different approaches to options pricing.

Learn different options Greeks which affect the options pricing. Greeks covered are Delta, Gamma, Theta, and Vega. Also understand various advanced options Greeks such as Rho, Volga, Vanna, Charm, and Veta.

Learn various options trading strategies based on the Greeks. Covers two arbitrage strategies based on put-call parity. Also learn a time value strategy called calendar spread and two more strategies which can be implemented during the earnings announcement of a company.

Learn three strategies based on the volatility viz. Forward Volatility, Volatility Smile, and Volatility Skew. Also, learn to back-test these options volatility strategies in IPython notebook.

course 2### Advanced

#### Section 1: Introduction

#### Section 2: Dispersion Trading

#### Section 3: Machine Learning

#### Section 4: Exotic Options

#### Section 5: Risk Management

#### Section 6: Scenario Analysis

Learn essential mathematical concepts to derive options pricing models such as Binomial Trees. Learn Wiener Process and Ito’s Lemma to understand how Robert Merton expanded the Black Scholes Model to Black Scholes Merton Model or BSM.

Learn a mean-reversion strategy on implied correlation known as Dispersion Trading. An entire video lecture and an IPython notebook are dedicated to making you understand the working and application of Dispersion Trading.

Understand how to predict the options price through decision tree classifier and practise it through interactive exercises which makes it easier to implement the same in your options trading.

Learn the concept and valuation of various exotic and compound options. Also learn risk measures such as VaR, Expected Shortfall, and learn how to code them in Python.

Learn how Delta of a portfolio can be hedged to protect the portfolio's value from the change in the price of the underlying asset. Also, learn how to preserve the portfolio's value using Gamma Scalping and practise coding the same in Python. Additionally, learn how to make a portfolio Vega neutral.

A video lecture on scenario analysis and how to use options to earn profits when major events impact the financial markets.

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Customized Video Experience

Jupyter Notebook Documents

Machine Driven Interactive Exercises

"Awesome Course, totally worth the money. Best part is the support you get from the Quant team in case you have doubts on any part of the course. I will recommend this course to anyone who has done the options trading strategies in Python: Basic."

"It’s really a good course one should do the same ASAP"

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