Andrew Gibbs has been involved in the financial markets since 2001 and is the founder and CEO of Halifax New Zealand.

Andrew has extensive experience in all forms of equity and derivative contracts, managing millions of dollars and trading a number of markets around the world.

In this episode we discuss volatility and methods to trading the VIX plus the benefits and methods of including fundamental data in technical quant models.

Topics discussed

Instruments you can use to trade volatility and the benefits or disadvantages of each
What makes the VIX attractive to trade and why it often trends over time
The types of trading styles that suit the VIX
The dangers of trading volatility products
Seasonality in the VIX
How to get started building volatility trading models
Fundamental data and the types of fundamental datasets that work well in quantitative models
Why some fundamentals work better than others
The frequency of fundamental data release and how that dictates trading model style
How to account for revisions to data
The impact of including fundamental data can have on trading results
Technical vs Fundamental data and which tends to be more robust
Issues with fundamental data and company reporting accuracy
How to reduce the chances of investing in a company that is likely to go bust
Combining fundamentals and technical data and how to test
How to get started building fundamental quant models

Disclaimer:
Trading in the financial markets involves a substantial risk of loss and is not suitable for everyone. All content produced by Better System Trader is for informational or educational purposes only and does not constitute trading or investment advice. Past performance is not necessarily indicative of future results.

035: Andrew Gibbs discusses volatility and trading the VIX plus the benefits and methods of including fundamental data in technical quant models.

Better System Trader

035: Andrew Gibbs discusses volatility and trading the VIX plus the benefits and methods of including fundamental data in technical quant models.