Volatility Trading Analysis with R

Learn volatility trading analysis from basic to expert level through a practical course with R statistical software.

Course Description

Learn volatility trading analysis through a practical course with R statistical software using CBOE S&P 500 volatility and options indexes® and replicating ETFs or ETNs historical data for back-testing. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your research as sophisticated investor. All of this while exploring the wisdom of Nobel Prize winners and best practitioners in the field.

Become a Volatility Trading Analysis Expert in this Practical Course with R

  • Download CBOE S&P 500 volatility and options indexes® data to perform trading analysis operations by installing related packages and running script on RStudio IDE.
  • Estimate historical or realized volatility through Close to Close, Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang metrics.
  • Calculate forecasted volatility through Random Walk, Historical Mean, Simple, Exponentially Weighted, or Autoregressive Integrated Moving Averages and General Autoregressive Conditional Heteroscedasticity models.
  • Evaluate market participants implied volatility through CBOE Volatility Index VIX®.
  • Estimate futures contract prices and explore volatility and asset returns correlation, volatility risk premium, volatility term structure and volatility skew patterns.
  • Implement volatility risk premium and capped volatility risk premium futures trading strategies using CBOE S&P 500 Volatility Indexes®.
  • Approximate options call and put prices through Black and Scholes and Binomial Trees models together with related Options Greeks.
  • Apply buy write, put write and volatility tail hedge options trading strategies using CBOE Options and Volatility Indexes® and replicating ETFs or ETNs.

Become a Volatility Trading Analysis Expert and Put Your Knowledge in Practice

Learning volatility trading analysis is indispensable for finance careers in areas such as derivatives research, derivatives development, and derivatives trading mainly within investment banks and hedge funds. It is also essential for academic careers in derivatives finance. And it is necessary for sophisticated investors’ volatility trading strategies research.

But as learning curve can become steep as complexity grows, this course helps by leading you step by step using CBOE S&P 500 volatility and options indexes® and replicating ETFs or ETNs historical data for back-testing to achieve greater effectiveness.

Content and Overview

This practical course contains 41 lectures and 5 hours of content. It’s designed for all volatility trading analysis knowledge levels and a basic understanding of R statistical software is useful but not required.

At first, you’ll learn how to download CBOE S&P 500 volatility and options indexes® replicating data to perform volatility trading analysis operations by installing related packages and running script on RStudio IDE.

Then, you’ll do volatility analysis by estimating historical or realized volatility through Close to Close, Parkinson, Garman-Klass, Rogers-Satchell, Garman-Klass-Yang-Zhang and Yang-Zhang metrics. After that, you’ll use these estiomations to forecast volatility through Random Walk, Historical Mean, Simple Moving Average, Exponentially Weighted Moving Average, Autoregressive Integrated Moving Average and General Autoregressive Conditional Heteroscedasticity models. Next, you’ll evaluate market participants implied volatility through CBOE Volatility Index VIX®.

Later, you’ll estimate futures contract prices and compare them with actual historical data. Then, you’ll explore volatility and asset returns correlation, volatility risk premium, volatility term structure and volatility skew patterns. Next, you’ll implement two futures trading strategies using CBOE S&P 500 Volatility Indexes®. First strategy you’ll implement is Volatility Risk Premium by evaluating historical risk adjusted performance of CBOE VIX Premium Strategy VPD®. Second strategy you’ll implement is Capped Volatility Risk Premium by evaluating historical risk adjusted performance of CBOE Capped VIX Premium Strategy VPN®.

After that, you’ll estimate option call and put prices through Black and Scholes and Binomial Trees models together with related Options Greeks. Finally, you’ll implement three options trading strategies using CBOE Options and Volatility Indexes® and replicating Exchange Traded Funds ETFs and Exchange Traded Notes ETNs. First strategy you’ll implement is Buy Write by evaluating historical risk adjusted performance of CBOE 30-Delta Buy Write Index BXMD® and related investment vehicle. Second strategy you’ll implement is Put Write by only evaluating historical risk adjusted performance of CBOE Put Write Index PUT®. Third strategy you’ll implement is Volatility Tail Hedge by evaluating historical risk adjusted performance of CBOE VIX Tail Hedge Index VXTH® and related investment vehicle.

What are the requirements?

  • R statistical software is required. Downloading instructions included.
  • RStudio Integrated Development Environment (IDE) is recommended. Downloading instructions included.
  • R script files provided by instructor.
  • Prior basic R statistical software knowledge is useful but not required.

What am I going to get from this course?

  • Download CBOE S&P 500 volatility and options indexes® data to perform trading analysis operations by installing related packages and running script on RStudio IDE.
  • Estimate historical or realized volatility through Close to Close, Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang metrics.
  • Calculate forecasted volatility through Random Walk, Historical Mean, Simple, Exponentially Weighted, or Autoregressive Integrated Moving Averages and General Autoregressive Conditional Heteroscedasticity models.
  • Evaluate market participants implied volatility through CBOE Volatility Index VIX®.
  • Estimate futures contract prices and explore volatility and asset returns correlation, volatility risk premium, volatility term structure and volatility skew patterns.
  • Implement volatility risk premium and capped volatility risk premium futures using CBOE S&P 500 Volatility Indexes®.
  • Approximate options call and put prices through Black and Scholes and Binomial Trees models together with related Options Greeks.
  • Apply buy write, put write and volatility tail hedge options trading strategies using CBOE Options and Volatility Indexes® and replicating ETFs or ETNs.

Who is the target audience?

  • Students at any knowledge level who want to learn about volatility trading analysis using R statistical software.
  • Finance professionals or academic researchers who wish to deepen their knowledge in derivatives finance.
  • Sophisticated investors who desire to research volatility trading strategies.
  • This course is NOT about “get rich quick” trading strategies or magic formulas.

Full Details : [ Take Course Now ]
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