The preceding section on designing a trading system examines the different types of markets in which to trade, and takes a look at the two basic genres of trading systems: trend-following and countertrend systems. These two strategies form the foundation on which all trading systems are built, and the markets provide the medium. In this second section on designing a trading system, we break down the two genres into individual components, examine the empirical decision-making process and, finally, take a look at how software has revolutionized system trading.
Basic Trading System Components
As mentioned in the introduction, trading systems are constructed using parameters - the groups of specific rules that generate entry and exit points for any given equity. Both trend-following and countertrend trading systems adhere to four basic principles that govern the construction of any trading system. These principles are also the essential characteristics of an effective system:
- The system must make money - This is easy to say, but hard to do. Maximizing the percent return should be your primary objective while designing a trading system.
- The system must be able to limit risks - It's difficult to use a system that fluctuates between extreme highs and lows; not only does it inhibit your ability to liquidate, but it can also be psychologically taxing. Furthermore, by limiting risks, you are able to decrease the effect of a "bad entry" (for example, going long during a downward fluctuation).
- The system's parameters must be stable and feasible - Trading systems cannot rely on coincidence or luck! The system designer can fulfill this principle of stability by broadening the parameters and not optimizing too much in an effort to increase his or her chances of success. The feasibility of parameters, including 'slippage', is discussed in the second section of this tutorial. Again, it is very important to take slippage into account when designing a system.
- The system's timeframe must be stable and feasible - For a system's timeframe to be successful, coincidence and luck should not play a factor. Feasibility must also be considered in this instance. If timeframes are set too close together, the resulting amount of trading frequency may not be possible due to software limitations and/or market-side limitations.
Empirical Decision Making
A trading system requires the designer to make some empirical decisions that directly affect the system's performance - if there was no need for this decision making, everyone would be rich. Here are some basic factors that system designers must decide on and some guidelines:
- What time period should I use? All equities can be analyzed from multiple perspectives of time periods, ranging from one minute to one decade (or more). Deciding which time period to test can drastically affect the performance of the system. More reliable results generally come from longer time periods, while short periods can be misleading when judging real market conditions. However, this does not mean that only extremely long price periods should be used. It is important to keep in mind that the longer the time period, the longer it may take for profit to be realized. Observe the following example of Microsoft's long term, a period of more than 20 years, compared to its short term, a period of a few weeks:
We can clearly see that the short term is not an accurate representation of the long term, and vice versa. As a general rule of thumb, five to 10 years is a good target for medium- to long-term system traders, and six months to five years is a reasonable range for short-term traders. Again, it depends on when you plan to liquidate.
- What price series should I use? Most equities are charted on an unbroken price series - that is, the charts are continuous. When trading futures and some other equities, however, there is an option to use actual contract data instead of continuity. Futures contracts themselves only last a few months, and system backtesting often requires a year or more of data; therefore, system traders often utilize continuous futures, which are a series of contracts combined to create a continuous stream of data. As a general rule of thumb, long-term traders should stick to continuous futures, while short-term traders should use actual contract data.
- What parameters and settings should I use? We explore this further in subsequent sections that address the construction of a trading system. Basically, parameters are selected by "guessing-and-checking," or producing "blind" simulations, or presetting a group of parameters, and then using the average to determine performance.
Again, many of these factors can be influenced by desired liquidity, time until liquidation, risk and a multitude of other factors, so it is important to take the time to decide which works best for you.
The evolution of the computer is perhaps the greatest driving force behind system trading. Originally, computers were just used to crunch the numbers; eventually they acquired the capacity to conduct simulations, generate signals in real-time, and even place trades for the trader! Some software is designed simply as a platform from which a system developer can build a system; other software uses neural networks to "learn" from the markets and enhance itself. Some software is installed on the user's hard drive; other software is provided only online. Here are a few of the basic programs used by system developers:
Client-side software must be installed on the user's computer. It is often connected to the internet and is able to obtain real-time data (including prices, news, etc.). Note: some companies charge you not only for the software, but also for the data. These applications typically allow the user to specify the time period, types of parameters, and more. One of the most crucial features, however, gives the user the ability to program a system. This is done using a simple programming language (often specific to the application used) with which you can set up rules to generate buy and sell signals - these then appear directly on the chart. Here is an example of a client-side application called MetaTrader:
Server-side software is installed on a remote server. Often, these applications return signals that are displayed to the public by means of a webpage (or a subscriber base). This eliminates the need for any client-side software other than a web browser. Furthermore, the user pays a small subscription fee as opposed to buying a program and paying for a data subscription. Finally, the user does not have to develop the system, only receive generated signals. But you should remember that this kind of software is often susceptible to scams, while the client-side software is not. (For more on this, see Trading Systems Coding.)
Now you have a basic understanding of trading systems: you know what they are, the different types of systems that exist, the factors to keep in mind while designing them, and the software used to make system trading easier on you. Next, we will examine how to actually construct a trading system and put it into use!
Trading Systems: Constructing A System
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