Because of the unique characteristics of different currency pairs, many quantitative Forex strategies are designed with a specific currency pair in mind. While this can produce many profitable trading strategies, there are also advantages to developing strategies that can be traded across multiple currency pairs. This introduces an element of diversification that can provide an additional level of downside protection.

Daniel Fernandez recently published a system that he designed to trade on each of the four Forex majors. His goal was to find a system that would have produced a 20 year track record of profitable trading on EUR/USD, GBP/USD, USD/JPY, and USD/CHF.

forex majors

Daniel uses a data mining approach to develop a strategy for trading the four Forex majors.

In order to construct his system, Daniel used his data mining software to define entry and exit signals that would have produced a profitable trading strategy on each of the four currency pairs over the past 20 years. What he comes up with is a combination of three price-based rules that form the foundation of his Forex Majors strategy. 

Daniel’s Forex Majors Strategy

Daniel’s Forex Majors strategy is very simple in that it always has a position, either long or short, in each of the four currency pairs that it trades. It bases all of its trades on daily charts.

The strategy goes long when the following three conditions are met:

  • Close[9] > Close[10]
  • Open[158] > Low[130]
  • Close[156] > Close[173]

The strategy goes short when the following three conditions are met:

  • Close[9] < Close[10]
  • Open[158] < Low[130]
  • Close[156] < Close[173]

As you can see, the strategy is basically an optimized trend following strategy. This makes sense, because Daniel states at the beginning of his article that long-term trend following strategies are generally the best strategies for trading multiple markets.

One additional rule that Daniel’s strategy makes use of is an ATR-based stop-lossThe fixed stop-loss is set at 180% of the 20-day ATR. If the stop-loss is triggered, the strategy remains out of the market until a signal is generated in the opposite direction. Testing indicates that re-entering on a signal in the same direction negatively affected performance.

Backtesting Performance

The backtesting results that Daniel included in his post show that the strategy was quite profitable. It produced a win ratio of 45%, a profit factor of 1.38, and a reward to risk ratio of 1.68. Daniel’s biggest concern about the strategy was that the maximum drawdown period represented a very long time.

According to Daniel’s numbers, the mean annual return was 9.67%. This consisted of 16 profitable years, 4 losing years, and one year that basically broke even. The best year was a return of 37.76%, and the worst year was a loss of 20.2%.

Daniel notes that this system would not represent a good standalone strategy because of its returns relative to maximum drawdowns. However, he suggests that it could be an interesting piece of a larger, multi-system strategy.


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