A trading system is simply a group of specific rules, or parameters, that determine entry and outout points for a given equity. These points, known as signals, are often marked on a chart in real time and prompt the immediate execution of a trade.
Trading systems have experienced major shifts during the past few years. Obviously trading is no longer something that happens only behind the doors of major financial institutions - trading has expanded into the mass market.
In the lastseveral years trading systems have experienced major shifts. Trading systems expanded into the mass market. Nowdays people want to trade themselves and consequently a need for proper educational engines for trading skill training has emerged.
And what is Trading Solutions?
Trading Solutions combine technical analysis with artificial intelligence (AI) technologies using natural networks and genetic algorithms to learn patterns from historical data and optimize system parameters.
Iguan Systems is one of the companies which suggests creating you major trading systems with great trading solutions.
Here are four distinct steps in trading system development that Iguan Systems suggests:
Developing the market model and the basic automated system — the basic automated system implements this model but does not incorporate stop losses or profit targets. The basic system is for the sole purpose of collecting data for statistical analysis used in the later development steps
Risk management — the initial stop loss (ISL). Using the data gathered in Step 1 and based on the statistical analysis of that data, we add an ISL to the trading strategy. We use optimization to find a stop loss parameter that suits our needs. We will use walk-forward analysis to test this version of the system.
Profit management — the profit target (PT). As in Step 2, we will use the statistical analysis of our data to incorporate a profit target into the system. Again, we will use optimization to find an appropriate profit target and then use walk-forward analysis to test this version of the system.
Money management — the trade size algorithm (TSA). This Step does not depend on the data collected in Step 1. Instead, we will incorporate the popular fixed-fraction trade size method to determine how many lots are allocated to each trade. Popular trade literature is replete with advice to restrict per-trade risk within a range from 1% to 3% of account equity. We will run our optimization using those percentages, and then once again use walk-forward analysis to test this version of the system.