If you have been reading System Trader Success for a while you’re probably familiar with how I develop trading systems. The very first step is to come up with a simple idea to act as the seed or core of your trading system. I call this your key concept. This key concept is a simple observation of market behavior. This observation does not need to be complex at all. In fact, they are often very simple. For example, here is a key concept: most opening gaps on the S&P market close if the gaps are less than 4 points. This key concept is very simple, and testable. It is from such observation that I’ll often start to build a trading […]
This article is going to be an extension of a previous article where we performed an intraday price study. We do this...
In this article I would like to perform an intraday price study to explore the intraday action of the market to determine...
In the October issue of Futures magazine author Jean Folger discusses an important aspect when selecting two or more...
Some trading systems have prolonged periods of winning or losing trades. Long winning streaks may be followed by a prolonged period of drawdown. Wouldn’t it be nice if you could minimize those long drawdown periods? Here is one tip that might help you do just that. Try applying a simple moving average to your trading system’s equity curve and use that as a signal on when to stop and restart trading your system. This technique just might radically change your trading system’s performance. How to do this? Well the moving average applied to your trading system’s equity curve creates a smoothed version of your trading system’s equity curve. You can now use this smoothed equity curve as a signal on when to stop or restart trading. For example, […]Read more ›
One of the most important aspects of algorithmic trading is the removal of trading strategies from live accounts when they fail. Knowing when a strategy fails is extremely important as it allows us to avoid taking loses and missing opportunities while giving us the chance to reallocate our capital to use strategies that might be better-performing under current market conditions. However most people do not have a truly rational plan for system failure and others consider failure in only a very limited scope that is actually better fit to hope than to a rational analysis of a trading strategy’s statistical characteristics. Within these posts I want to discuss with you what trading system failure means and how this failure can […]Read more ›
Let’s take a look at a simple moving average crossover system and see if we can improve it. Specifically, can we improve the moving average system’s performance by reducing the number of whipsaws during those dreaded range bound markets? Whipsaws occur when a market moves from a trending mode to a consolidation mode. During this consolidation mode the system gets whipsawed from long to short creating a string of losing trades. Long trades suddenly reverse hitting your stop. Likewise for short trades. These ‘false signals’ can destroy your equity curve. In this article I’m going to present two simple methods to improve the simple moving average crossover system. These ideas can easily be implemented into your trading systems and may provide […]Read more ›
— By Michael Harris, Price Action Lab About 11 years ago, I gave a presentation in a conference in New York City as an invited speaker. The audience was mostly comprised of inexperienced traders. A good part of my presentation was on the subject of risk of ruin and proper account capitalization. After I explained what consecutive losers are, how they contribute to drawdown and that getting 4, 5 or even 7 consecutive losers is normal in trading, I wrote down this simple formula that determines proper account capitalization: Trading account minimum capital = Amount risked per trade / Percent risk The amount risked per trade is usually determined by the stops. The percent risk determines what percentage of the account is risked on each trade. For example, if […]Read more ›
In this article I want to introduce you to the methods by which I myself identify profitable algorithmic trading strategies. Our goal today is to understand in detail how to find, evaluate and select such systems. I’ll explain how identifying strategies is as much about personal preference as it is about strategy performance, how to determine the type and quantity of historical data for testing, how to dispassionately evaluate a trading strategy and finally how to proceed towards the backtesting phase and strategy implementation. Identifying Your Own Personal Preferences for Trading In order to be a successful trader – either discretionally or algorithmically – it is necessary to ask yourself some honest questions. Trading provides you with the ability to […]Read more ›
When you see the performance of a trading system, how do you know it’s good? How do you know it’s the right system for you? Many people simply look at the net profit assuming the system with the more profit must be the better system. This is often far from a good idea. When comparing trading systems during the development process or when comparing systems before making a purchase, it is nice to have a few metrics on hand that will allow you to compare the system either to a hypothetical benchmark or against another system. There is no one single score you can use that will work for everyone since we all have unique risk tolerances and definitions on what we consider tradable. Likewise, not all scoring systems are equal or perform under all […]Read more ›