The iQuant FX trading strategy
We believe that a good trading strategy is more than just a curve fitted backtest. Since it is your portfolio that is at stake, it is important to know about the background of a strategy. Although the fully automated execution of our iQuant strategy reduces the psychological factor one is exposed to when trading the markets to a minimum – it is still necessary to “believe” in the strategy. This is why we want you to know about the features of our strategy as much as possible.
Since we want you to have an unbiased look at what our iQuant strategy can do for you, we use Darwinex as a third party tool to verify our performance. This way we ensure maximum transparency while you can be sure that the performance you see, is the performance you get. By clicking on one of the charts you will be able to follow a link to our Darwinex profile where you can find an in depth analysis of our trading system.
Although our iQuant strategy appears to be one single strategy it actually consists of three strategies that are traded in several different exchange pairs. The first strategy uses a volatility filter and a pattern recognition technique to capture small to medium break-out movements. The second and third strategy enters the market when a trend retracement takes place and trades the continuation of the underlying trend. Each strategy identifies its entry and exit points by applying different trend filters and a price oscillator. This way the performance of our iQuant strategy is much more resilient as if trading only one strategy in a single exchange currency.
Our experience taught us that a trading strategy is only as reliable as its money management. It is a fact that no strategy can trade without losses. For this reason it is not only important to maximize the profits but also to reduce the losses. This is why we designed iQuant with a sophisticated money management that is build on the assumption that any reliable risk model is based on experience. That simply means that our iQuant strategy avoids the times it fails to model the market and thereby decreases the effects of drawdowns on the performance.