Random Thoughts on Trading Systems


Teaching a Grade 4 on Probability

Before summer started, my son was learning probability at school and his teacher gave his class some interesting questions to solve. The background is that they’ve just learned fraction, decimal numbers, etc.

(Lawrence: This is a copy of the article I have written for the new daytradingbias.com site last week. Enjoy!)
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Performance Sensitivity

For most traders, when tracking their own performances, or measuring the performance of trading systems, a tendency is to look for almost perfect improvement over time. We always want the performances to get better, stay in top shape, etc. In reality, such push can be harmful and can backfire.

Attached is an Excel spreadsheet showing the potential reason why and how to monitor trading performances using a relaxed condition that works well over the long term.

The Spreadsheet

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Studying Your Data Across All Bar Sizes

Have you ever wonder why you like to use 5-minute bars to trade something, and then, all of a sudden, switch into another time frame like 15-minute bar to monitor another instrument. Why we somehow have different level of comfortability with different time frames? Here is an interesting way to study an instrument to find out what time frame may be best for you.

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The 10 Year Challenge on Index Future Trading Systems


Going through a chart of the past 10 to 12 years in Emini S&P, I cannot help thinking if there is a trading model that can work well throughout the whole period of time with reasonable draw down and good performance year after year.

There was the great bull run from 1997 to 2000.

Then the bear market from 2000 to 2003.

The recovery rally from 2003 to 2005.

The slow grind from 2005 to 2006.

And then the huge volatility outbreak since middle of 2006 up til now.

Each period of time demonstrates difficulties for trading system designers to accommodate the specific characteristics of the time. Systems designed to fit a particular environment are not expected to function properly when there is an environment change.

Think of dip buying systems, and related trading styles in general developed back in 1997 to 1998. They all failed badly since year 2000.

Then in the bear time period, people started to develop the thinking that stock market can only go down. Once the recovery rally started, all trading styles and systems with bearish bias got crushed.

And then, fast forward to the current time period, trading systems designed to handle range bounded behaviour in the indices are again defeated by the market as daily trading range in the index futures are much less predictable.

But now, after going through all these phases, with historical data down to tick by tick resolution left behind. System designers can no longer stuck their heads into the sand and avoid testing their trading models against all these time periods.

The historical data for the past 10 to 12 years will be proven extremely valuable to all market participants as one can pretty much find the historical occurrences of all kinds of trading conditions. Systems that build on the anticipation of handling all these environments will surely enjoy a much longer life time comparing to ones that are optimized over a particular environment only.


Formula 301 – #7 Random Entry System

Unlike the previous tutorials that we focus on how to write a trading system, we are going to explore a special kind of trading systems – the ones that utilize randomization.

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Trading System 101 – Part 4 What Happen When My System Place A Market Order?

For many beginners, there is always confusion about the mechanism of order placement. I am going to provide more details about that in this article.

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Formula 301 – #2 Basic Controls

We are going to study another basic trading strategy, buy close and sell next open. At the same time, we will go over the basic options in NeoTicker for the control of trading systems.

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Formula 301 – #1 Trading System Concept and Our First System

In Formula 301, we are going to focus on writing trading systems with the indicator formula language. The assumption is that you know the basics of writing indicator with the formula language. I will present trading systems that illustrate the usage of specific trading system related writing techniques.

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Trading System 101 – Part 3 Practical Considerations

Many traders spent weeks, even months to create their perfect trading models. Happy with the results they see in their backtesting, and tracked the real-time performance for certain period of time, they are ready to take the leap of faith to trade their models live.

Could that be just a bit too early? Well, that depends on how prepared the person is. Unluckily, I have to say that many of these traders (rookie system designers) are getting their worst nightmares and rudest awakening.

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In Early Stage Of System Development, Avoid Position Sizing

Many beginners in trading system development like to play with position sizing scheme. It feels great when you get a great equity curve with spectacular performance by simply twisting what position sizing rules to use and experiment with various sizing parameter settings. I have some bad news for you – such system will not likely perform in real life.

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