EUR/USD Backtested – Technical Indicators and Random Entry

Last Updated on November 28, 2022 by Mark Ursell

Random Entry

This article is the second in a series investigating how effective random entry can be in a trading strategy. In this article, I am looking at combining a random entry factor with technical indicators to see if it makes the system more reliable.

You can read the previous article here: Backtesting a EUR/USD Trading Strategy Using an ATR Trailing Stop.

Market and Timeframe

As in the previous article, I am using the EUR/USD forex pair. The EUR/USD is the most widely traded currency pair and has the lowest transaction costs. The EUR/USD represents the balance of strength between the eurozone, the world’s largest single currency zone and the US, the world’s largest economy. Between them, they represent almost half of the entire world economy.

Historically, the EUR/USD has been a good market for traders. The pair has often trended as differences in economic growth rates and monetary policy move the two currencies in different directions.

The backtests use the 4-hour timeframe and I am testing 10,000 periods, between 2006 and 2012.

Exit Signal

Trades are exited using a trailing stop. The trailing stop uses a multiple of the ATR. This allows the trailing stop to react dynamically to market conditions. When the market is volatile, the trailing stop is larger and when the market is quiet, the trailing stop is smaller.

Simulations

The simulations look at 4 scenarios:

• “With the trend” – long trades only entered above the 34-period SMA, short trades only below. This is a very simple definition of a trend but, I was expecting this to achieve a small improvement in the results.
• “Against the trend” – long trades only entered below the 34 SMA, short trades only above. I expected this scenario to make the results worse.
• “When the market is calm” – trades entered randomly in both directions when the market is within Bollinger Bands of 1 standard deviation. If the market is trading within 1 standard deviation of the average, it has plenty of room to move in either direction. I expected this scenario to be an improvement over the purely random entry scenario.
• “When the market is not at extremes” – trades entered randomly in both directions when the market is within Bollinger Bands of 2 standard deviations. Whenever the market is outside the Bollinger Bands, it is at an extreme price compared to the recent past. I was hoping to see a small improvement over the purely random entry scenario.

For each of these scenarios, I have tested an ATR trailing stop using a multiplier of 1, 2, 3 and 4.

Each scenario has been tested 4 times.

Video

You can check out the accompanying video on YouTube.

Results

The results of the tests broadly met my expectations. The 1 ATR and 3 ATR scenarios were again the most profitable and I will focus on these.

For the 1 ATR trailing stop both the “with the trend” and “when the market is calm” scenarios showed a small but noticeable improvement in the percentage of winning tests. However, both of these scenarios showed a small decrease in the overall average profit.

For the 3 ATR trailing stop, the 34 period SMA did not improve the profitability. However, the “when the market is calm” scenario showed a decent increase in a number of profitable simulations.

Conclusions and Future Tests

The results are encouraging to me and show that random entry and technical indicators can be combined to create more effective trading strategies. The evidence in these tests suggests that technical indicators can make the random entry signals more reliable. Despite this, there are no strategies in this test that I would consider actively trading.

However, I am very interested in how the trailing stop is helping to keep the majority of the strategies profitable. I am also interested in how I can use a random factor in future simulated backtests and possibly in live trading.