Automated Trading Software :
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Introduction to Automated Trading Systems
The preceding section of this tutorial looked at the elements that make up a trading system and discussed the advantages and disadvantages of using such a system in a live trading environment. In this section, we build on that knowledge by examining which markets are especially well-suited to system trading. We will then take a more in-depth look at the different genres of trading systems.
Trading in Different Markets
Equity Markets
The equity market is probably the most common market to trade in, especially among novices. In this arena, big players such as Warren Buffett and Merrill Lynch dominate, and traditional value and growth investing strategies are by far the most common. Nevertheless, many institutions have invested significantly in the design, development and implementation of trading systems. Individual investors are joining this trend, though slowly.
Here are some key factors to keep in mind when using trading systems in equity markets:
- The large amount of equities available allows traders to test systems on many different types of equities - everything from extremely volatile over-the-counter (OTC) stocks to non-volatile blue chips.
- The effectiveness of trading systems can be limited by the low liquidity of some equities, especially OTC and pink sheet issues.
- Commissions can eat into profits generated by successful trades, and can increase losses. OTC and pink sheet equities often incur additional commission fees.
- The main trading systems used are those that look for value - that is, systems that use different parameters to determine whether a security is undervalued compared to its past performance, its peers, or the market in general.
Foreign Exchange Markets
The foreign exchange market, or forex, is the largest and most liquid market in the world. The world's governments, banks and other large institutions trade trillions of dollars on the forex market every day. The majority of institutional traders on the forex rely on trading systems. The same goes for individuals on the forex, but some trade based on economic reports or interest payouts.
Here are some key factors to keep in mind when using trading systems in the forex market:
- The liquidity in this market - due to the huge volume - makes trading systems more accurate and effective.
- There are no commissions in this market, only spreads. Therefore, it's much easier to make many transactions without increasing costs.
- Compared to the amount of equities or commodities available, the number of currencies to trade is limited. But because of the availability of 'exotic currency pairs' - that is, currencies from smaller countries - the range in terms of volatility is not necessarily limited.
- The main trading systems used in forex are those that follow trends (a popular saying in the market is "the trend is your friend"), or systems that buy or sell on breakouts. This is because economic indicators often cause large price movements at one time.
Futures
Equity, forex, and commodity markets all offer futures trading. This is a popular vehicle for system trading because of the higher amount of leverage available and the increased liquidity and volatility. However, these factors can cut both ways: they can either amplify your gains or amplify your losses. For this reason, the use of futures is usually reserved for advanced individual and institutional system traders. This is because trading systems capable of capitalizing on the futures market require much greater customization, use more advanced indicators and take much longer to develop.
So, Which is Best?
It's up to the individual investor to decide which market is best suited to system trading - each has its own advantages and disadvantages. Most people are more familiar with the equity markets, and this familiarity makes developing a trading system easier. However, forex is commonly thought to be the superior platform to run trading systems - especially among more experienced traders. Moreover, if a trader decides to capitalize on increased leverage and volatility, the futures alternative is always open. Ultimately, the choice lies in the hands of the system developer.
Types of Trading Systems
Trend-Following Systems
The most common method of system trading is the trend-following system. In its most fundamental form, this system simply waits for a significant price movement, then buys or sells in that direction. This type of system banks on the hope that these price movements will maintain the trend.
Moving Average Systems
Frequently used in technical analysis, a moving average is an indicator that simply shows the average price of a stock over a period of time. The essence of trends is derived from this measurement. The most common way of determining entry and exit is a crossover. The logic behind this is simple: a new trend is established when price falls above or below its historic price average (trend). Here is a chart that plots both the price (blue line) and the 20-day MA (red line) of IBM:
Breakout Systems
The fundamental concept behind this type of system is similar to that of a moving average system. The idea is that when a new high or low is established, the price movement is most likely to continue in the direction of the breakout. One indicator that can be used in determining breakouts is a simple Bollinger band overlay. Bollinger bands show averages of high and low prices, and breakouts occur when price meets the edges of the bands. Here is a chart that plots price (blue line) and Bollinger bands (gray lines) of Microsoft:
Disadvantages of Trend-Following Systems:
- Empirical Decision-Making Required - When determining trends, there is always an empirical element to consider: the duration of the historic trend. For example, the moving average could be for the past 20 days or for the past five years, so the developer must determine which one is best for the system. Other factors to be determined are the average highs and lows in breakout systems.
- Lagging Nature - Moving averages and breakout systems will always be lagging. In other words, they can never hit the exact top or bottom of a trend. This inevitably results in a forfeiture of potential profits, which can sometimes be significant.
- Whipsaw Effect - Among the market forces that are harmful to the success of trend-following systems, this is one of the most common. The whipsaw effect occurs when the moving average generates a false signal - that is, when the average drops just into range, then suddenly reverses direction. This can lead to massive losses unless effective stop-losses and risk management techniques are employed.
- Sideways Markets - Trend-following systems are, by nature, capable of making money only in markets that actually do trend. However, markets also move sideways, staying within a certain range for an extended period of time.
- Extreme Volatility May Occur - Occasionally, trend-following systems may experience some extreme volatility, but the trader must stick with his or her system. The inability to do so will result in assured failure.
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Countertrend Systems
Basically, the goal with the countertrend system is to buy at the lowest low and sell at the highest high. The main difference between this and the trend-following system is that the countertrend system is not self-correcting. In other words, there is no set time to exit positions, and this results in an unlimited downside potential.
Types of Countertrend Systems
Many different types of systems are considered countertrend systems. The idea here is to buy when momentum in one direction starts fading. This is most often calculated using oscillators. For example, a signal can be generated when stochastics or other relative strength indicators fall below certain points. There are other types of countertrend trading systems, but all of them share the same fundamental goal - to buy low and sell high.
Disadvantages of Countertrend Following Systems:
- Empirical Decision-Making Required - For example, one of the factors the system developer must decide on is the points at which the relative strength indicators fade.
- Extreme Volatility May Occur - These systems may also experience some extreme volatility, and an inability to stick with the system despite this volatility will result in assured failure.
- Unlimited Downside - As previously mentioned, there is unlimited downside potential because the system is not self-correcting (there is no set time to exit positions).
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:
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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.
Software and System Trading
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
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
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.
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