Volatility Trading Analysis with R

Requirements

• R statistics software must be installed. Downloading instructions are included.
• RStudio Integrated Development Environment (IDE) is highly recommended. Downloading instructions are provided.
• Examples of experimental data and R script code files included with the course.
• A basic R statistics software experience is beneficial but not essential.

Description

Full Course Content Last Update 11/2018

Learn how to analyze volatility trading through an in-depth course using R statistical software, using CBOE(r) and S&P 500(r) strategy for volatility, benchmark indexes, and replication of ETFs and ETNs historical data to allow testing the risk-adjusted performance of back-testing. The course covers the fundamentals starting from the advanced that can help you get higher grades, advance your academic career, use your skills at work, or conduct your research as a knowledgeable and skilled investor. This is all while examining insights from Nobel Prize winners and best practitioners in the discipline.

Learn to become a Volatility Trading Analyst with this course that is practical and taught by R

• Download CBOE(r) and S&P 500(r) volatility strategies benchmark indexes and replicate the fund’s data for performing historical analysis of volatility trading through the installation of related programs and running scripts using RStudio IDE.
• Estimate historical or realized volatility through close to close, Parkinson, Garman-Klass, Rogers-Satchell, Garman-Klass-Yang-Zhang and Yang-Zhang metrics.
• Calculate predicted volatility using seasonal random walks historic mean simple moving average exponentially weighted moving mean and an integrated autoregressive moving average and general autoregressive conditional heteroscedasticity models.
• Determine the implied volatility of market participants by using the associated volatility index.
• Calculate futures prices and study the correlation between asset returns and volatility and volatility risk premium the structure of volatility terms and Skewed patterns.
• Review the trading strategy’s performance using risk-adjusted hedged equity volatility strategies for futures. Benchmark index that replicates ETF as well as ETN.
• Approximate price of options calls and put via Black and Scholes models of binomial trees and similar options Greeks.
• Examine the buy put write, the volatility tail hedge options trading strategy’ historical risk-adjusted performance by using the related buy-write put write, hedged equity volatility strategies benchmarks and replicating ETFs.

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

The ability to understand volatility trading analysis is vital for careers in finance in areas like derivatives research, development of derivatives and derivatives trading, mostly within hedge funds. It is also crucial for academic career opportunities in derivatives finance. It is essential for investors with a solid background in research on strategies to trade volatility.

The learning curve could be steeper as complexity increases. This course will help by guiding you step-by-step using CBOE(r) and S&P 500(r) risk strategies as benchmarks and replicating historical ETNs or ETFs data to allow risk-adjusted testing of performance to improve efficiency.

Content and Overview

This course includes 45 lectures and five hours of material. It’s intended for people with a high level of knowledge in volatility trading analysis and knowledge about R statistical software. But not necessary.

The first step is to learn the process of downloading the CBOE(r) and S&P 500(r) strategy for volatility benchmark indexes and replicate ETFs and ETNs data to analyze volatility over time by installing related packages and running the 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. Then, you’ll apply these estimates to forecast the volatility of markets using seasonal random walks historical mean simple moving average exponentially weighted moving mean and an autoregressive integrated move and general autoregressive heteroscedasticity models that are conditional. The next step is to measure the implied volatility of market participants using an index of related volatility.

In the next step, you’ll calculate the futures price and compare it against historical data. You’ll then study the relationship between volatility and asset returns and risk-based volatility. You’ll also study the volatility risk in addition to the structure of the volatility term and patterns of volatility skew. In the next step, you’ll analyze the volatility risk using the historical implied volatility index’s daily returns and probability distribution non-normality. In the next phase, you’ll examine the strategy of trading volatility hedged futures historical performance about risk-adjusted using the related to the hedged equity volatile futures strategies benchmark index that replicates ETF as well as ETN.

Following that, you’ll estimate the price of an option called by Black and Scholes binomial tree models and associated options Greeks. In the next step, you’ll evaluate the risk associated with asset returns using historical daily returns for stock indexes probabilities distributions that are not normal. Then, you’ll look at covered call or buy writing and cash-secured short puts or put write. Volatile tail hedged options strategies for trading’ historical performance that is risk-adjusted using the associated buy-write put write, hedged equity volatility strategies benchmark indexes, as well as replicating ETFs.

Who is this course intended for:

• Students in postgraduate or undergrad who wish to gain knowledge about trading volatility through R the statistical program.
• Academic researchers or finance professionals who want to expand their knowledge of the field of derivatives finance.
• Expert investors with knowledge of financial derivatives and want to learn about strategies for trading volatility.
• This course is not focused on “get rich quick” trading strategies or magical formulas.