In this episode we’re discussing the results of a quantitative study on stop losses completed by Cesar Alvarez of Alvarez Quant Trading. Cesar was also a guest of the show way back in Episode 3.

Cesar was director of research for Connors Research for almost 9 years, developing quantitative trading models for individuals, prop traders and hedge funds.

In this episode he’s going to share the results of a quantitative study on stop losses, also testing out some common pieces of trading advice to see if they're actually true.

Stops can have such a huge impact on trading results so I'm sure traders of all levels will find this research invaluable.

We will be discussing backtesting results and some charts. We'll be explaining them for those who are listening along but if you’d also like to see the results while we discuss them, you can download a copy or even watch as a video in the show notes page at bettersystemtrader.com/37.

I hope you enjoy Cesars discussion of ‘Stops - the Good, the Bad and the Ugly’.

In this episode we discuss

• Different types of stops, their application and performance results
• Percentage vs Volatility based stops
• Intraday vs End of Day stops
• Trailing stops vs Targets
• Some common trading statements that are often assumed to be true and the results of testing them - do they hold up?
• The levels of Stop knowledge, which level are you at?

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.

Creating robust trading strategies can be a difficult task, sometimes taking months or even years to generate something you find acceptable. Even then, once you start trading it live there is no guarantee it’ll work in the future.

With strategy creation being such an involved process at times, how would you like it if you could just tell the computer the results you wanted and let it figure out the trading rules? Is it actually possible to create robust trading strategies that way?

In this episode Michael Bryant from Adaptrade talks to us about automatic code generation, methods to exploit trade dependency and techniques to trade the equity curve.

Michael has been trading the markets since 1994, providing trading systems for the futures markets and even managing money as a CTA.

He is founder of Adaptrade, a company which provides innovative software tools for individual and professional traders.

In this episode we discuss

• The traditional approach to creating trading systems and issues caused by this approach
• Potential areas of improvement in traditional approaches to system development
• Evolution of the strategy creation process
• Genetic programming and optimisation and it’s use in trading strategy creation
• The advantages of automatic code generation
• Measuring and reducing over-fitting when using genetic optimisation techniques
• Addressing concerns with removing human logic from the strategy development process
• Degrees of freedom and the impact if can have on strategy results
• Trade dependency, how to detect it and methods to exploit it
• Trading the equity curve based on trade dependency and trading style
• Which stage of the strategy creation process to include position sizing
• Common position sizing mistakes traders make

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.