The current electronic marketplace is a dynamic, complex arena where infinite possibilities exist at any given time. It is commonplace for individuals new to the financial markets, and to trading in general, to become overwhelmed with both the speed and magnitude of market fluctuations. In an attempt to manage the volatility that is present during the trading of financial instruments, individuals are often inclined to develop a systematic approach of viewing the financial markets.
What Is System Trading?
A "trading system" is defined as being a definitive set of rules that automatically identifies market entry and exit points, without human discretionary intervention. Accordingly, "system trading" is the application of the trading system's guidelines as the sole method by which a trader identifies and executes a trade. As all facets of the marketplace have become computerised, the scope of system trading has greatly expanded.
A System Trader's "Edge"
The goal of any trading system is to create an "edge," or a long-term positive expectancy for the trader. An edge is the perceived value present within a given trade that has been created by the trading system. Without a valid edge, the trading system ceases to be viable.
The guiding principles of a trading system can be grounded in nearly any discipline. A trading system can be rooted deep in technical analysis or based on traditional fundamental analysis. Some trading systems are based solely on price action and momentum, while others incorporate algorithms derived from intricate mathematics. The trader's imagination and technological capabilities act as the only limitations regarding the creation of a trading system.
A concrete set of rules is required for a trading system to exist. Many tactics are used in the crafting of a system's rules, and ultimately, the validity of these rules serves as the foundation for the entire trading approach.
Historical data backtesting is one of the most commonly used aspects of system development. Backtesting is defined as being the process of applying a trading strategy or analytical method to historical data in order to see how accurately the strategy or method would have predicted actual results.
Although it is a valuable tool in the development of a viable trading system, backtesting is susceptible to many pitfalls. Historical bias, backfitting of data and the absence of accurate historical data are just a few ways a backtesting study's results can become inaccurate.
Another popular way by which system developers test a trading method's validity is called walk forward optimisation. This is more complex than backtesting, but at its core, it is simply testing a trading method's validity over random historical data sets given variable timeframes. While backtesting is prone to producing obsolete results, walk forward optimisation aims to simulate future performance.
System development was once a discipline only available to large institutional investors and fund managers. However, as information systems technology advanced, the availability of data and software became affordable and available to the retail trader. Many electronic trading platforms offer system development options included in the client's software package. MetaTrader 4, NinjaTrader and Trading Station are a few platforms that offer the retail trader products useful in system development. Read more about them here.
Applications Of System Trading
Technology and system trading go hand in hand, and often function as one in today's electronic marketplace. Automated trading, algorithmic trading and high frequency trading are all examples of system dependent trading methodologies that have become prevalent in the global marketplace.
Automated trading is an approach to the markets where individual trades are placed and managed exclusively by computers. The computers are programmed according to the rules of a trading system and execute the system automatically. For instance, upon recognition of a trade setup defined by the programmed trading system's guidelines, the computer behaves as a human trader would. It automatically places market entry orders, stop loss orders and profit targets according to the trading system's guidelines. Often, automated trading systems are guided by complex algorithms, hence the term "algorithmic trading."
High frequency trading is the practice of trading large volumes via automation directed by algorithms. Essentially, high frequency trading is the basic application of a trading system. However, the trading occurs in speeds measured in milliseconds and volumes measured in thousands. It is estimated that nearly 50% of all equities traded in the United States can be attributed to high frequency trading systems.
Whether a market participant is a small retail trader, or a large institutional investor, the practice of system trading undoubtedly represents a substantial portion of trading operations. System trading provides a structured view of the marketplace and serves as an essential element in any automated, algorithmic or high frequency trading approach.
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