Developing robust trading systems

TraderFeed: Designing a Robust Mechanical Trading Strategy: A Best Practice in Trading

 

developing robust trading systems

"Tomas is a professional trader, who for the last 10 years has specialized in developing trading systems. We have been tracking his trading systems for about 5 years and they generally show very robust, stable and above average performance. Apr 03,  · Strategy Development with Perry Kaufman [Better System Trader] Im sure we all want to create trading strategies that perform better and last for longer but there are a number of issues we need to look out for when developing robust trading strategies, . May 25,  · Chat with Traders Episode The casino edge, mean reversion strategies, and how to develop robust trading systems w/ Nick Radge, The Chartist.


- Strategy Development with Perry Kaufman - Better System Trader


In this first article we will discuss how to verify if a certain trading system is robust or not. Does the system work on a variety of time frames? Does the system work on a variety of instruments? Does the system work on at least 6 years developing robust trading systems past data without the need to be re-optimized frequently? This is a simple system with only two key parameters that can be optimized: PeriodS developing robust trading systems lookback period in bars of a slow indicator and PeriodF the lookback period in bars of a developing robust trading systems indicator, developing robust trading systems.

The system has the following characteristics: Intraday Entry: developing robust trading systems move with increase in volatility Exit: stop loss, change of trend, end-of-day Risk management: volatility based stop loss, trailing stop loss, range contraction filter, limitation on max number of trades per day Position sizing: 1 contract Does the system work on a variety of parameter combinations? In order to check robustness of the variety of parameter combinations we optimize PeriodS from bars to bars with steps of 25 and PeriodF from 10 bars to 40 bars with steps of We can see that the SQN average is 4.

Basically it is the average trade, divided by the standard deviation of the average trade and multiplied by the square root of the number of trades. You can find more information below. Values over 2. The second test relates to time frames. A robust system will maintain good results across a variety of time frames. In order to check robustness over various time frames we keep the two parameters fixed at PeriodS and 30 PeriodF and optimize the time frame from 10 to 50 bars with steps of 5.

We can see that the lowest SQN value is 3. The charts indicates that this system is most effective at lower and higher time frames, however it maintains a good SQN value throughout. A robust system will maintain good results across a variety of instruments.

The most robust systems will have good results with the exact same parameters across many instruments. At the very least one should focus on systems that can actually work across different instruments, even though the best parameters may be different. The optimization provides the following results: The results above, from January to Aprildeveloping robust trading systems, show this particular system can be profitable — with different parameters — on several futures markets.

However, the most robust systems will maintain good results across different tradables whilst maintaining the same parameters. A robust system will maintain good results over various years without the need to be re-optimized frequently.

In conclusion, when evaluating the robustness of a trading system there are four key tests to perform. Only if a system performs well across a variety of parameter combinations, a variety of time frames, a variety of instruments and over at least 6 years of past data without the need to be re-optimized frequently it can be considered fully robust, developing robust trading systems.

All optimizations described in this article have been done using NinjaTrader and Kinetick 1-minute data. Amon Licini, the founder of Vbo Systems, has been a private trader for 15 years and a senior manager with various corporates in Italy. About the Author System Trader Success Contributor Contributing authors are active participants in the financial markets and fully engrossed in technical or quantitative analysis.

They desire to share their stories, insights and discovers on System Trader Success and hope to make you a better system trader. Contact us if you would like to be a contributing author and share your message with the world. Related Posts.

 

Developing Robust Trading Systems

 

developing robust trading systems

 

Sep 15,  · This video interview discusses how to develop a robust trading system. Featured Trading Resources Etoro Tap into the wisdom of the crowds by following and copying thousands of top performing traders. Your capital is at risk. Regal Assets Gold IRA Company #1 Rated Gold Company 7 years in a row. Get your free gold investing ycomymyjomob.tk: Guy. 22 A manual trading system is a system where the trader decides when to make an entry or an exit for its trades. Nowadays it is common for traders to use computer programs to study the market or to set indicators and screeners that will provide the trader some analytical information. VbO Systems is a developer of % automated trading systems coded in NinjaTrader that can be auto-traded on almost all asset classes. Amon Licini, the founder of Vbo Systems, has been a private trader for 15 years and a senior manager with various corporates in Italy.