No savvy trader would trade a system with a real account and risk real money without first observing its behavior on paper. A trading simulator is a software application or component that allows the user to simulate, using historical stock market data, a trading account that is traded with a user-specified set of trading rules. The user’s trading rules are written into a small program that automates a rigorous “paper-trading” process on a substantial amount of historical data. In this way, the trading simulator allows the trader to gain insight into how the system might perform when traded in a real account. The 'raison d'etre' of a trading simulator is that it makes it possible to efficiently back-test, or paper-trade, a system to determine whether the system works and, if so, how well.
Types of Simulators
There are two major forms of trading simulators. One form is the integrated, easy-to-use software application that provides some basic historical analysis and simulation along with data collection and charting. The other form is the specialized software component or class library that can be incorporated into user-written
software to provide system testing and evaluation functionality. Software components and class libraries offer open architecture, advanced features, and high levels of performance, but require programming expertise and such additional elements as graphics, report generation, and data management to be useful. Integrated applications packages, although generally offering less powerful simulation and testing capabilities, are much more accessible to the novice.
Reliability of Simulators
Ocerall, trading simulators vary in their reliability and trustworthiness. No complex software, and that includes stock market
trading simulation software, is completely bug-free. This is true even for reputable vendors with great products. Other problems pertain to the assumptions made regarding ambiguous situations in which any of several orders could be executed in any of several sequences during a bar. Some of these items, e.g., the so-called bouncing tick (Ruggiero, 1998), can make it seem like the best system ever had been discovered when, in fact, it could bankrupt any trader. It seems better that a simulator makes worst-case assumptions in ambiguous situations: this way, when actual trading begins, there is greater likelihood of having a pleasant, rather than an unpleasant, surprise.
All of this boils down to the fact that when choosing a simulator, select one that has been carefully debugged, that has a proven track record of reliability, and in which the assumptions and handling of ambiguous situations are explicitly stated. In addition, learn the simulator’s quirks and how to work around them.
Do your research on specific
stock trading simulators before attemping to use one.
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