Best Bias Strategy for Soybean - One of the Biggest Futures in the World

by Andrea Unger

Need More Help? Book Your FREE Strategy Session With Our Team Today!

We'll help you map out a plan to fix the problems in your trading and get you to the next level. Answer a few questions on our application and then choose a time that works for you.


The Soybean future listed on CME is one of the largest futures in the world, with over 200,000 contracts traded per day.

In this video, we explore the recurring intraday price movements that characterize this market and try to understand if it is possible to exploit them effectively with a simple bias strategy.

By watching this video, you'll learn:

- How to identify recurring trends in a session of the Soybean future 

- How to create simple rules to exploit these movements in MultiCharts or TradeStation

- How to test and evaluate the system (making sure that the bias you identify is not a product of overfitting)

If you are looking for new strategies to add to your portfolio, don't miss out on this video 😉




Hello everyone and welcome! 

I'm one of the coaches of Unger Academy and today, we're going to be talking about market recurring behaviors again and, more in particular, we're going to focus on the Soybean market. 

In this video, we're going to see the daily price movements that characterize this instrument and try to figure out whether it is possible to exploit them in our trading strategies.

Alright, so let's get on with our video and see how an average day looks like for this market in terms of price movements. I remind you that Soybean - the future on Soybean listed at CME - is one of the largest futures in the grains sector in the world. Just consider that the number of contracts traded per day exceeds 200,000. It's a lot.

The Bias

Now we're going to use this chart to go and find out what happens to the price of Soybean during a typical trading day.

Now we see that on average, from January 2010 to November 2021, there's a tendency for soybean’s price to rise starting from midnight, exchange time (so Chicago time) until around 4 am, so at this point here. And then we can see a long downward trend that starts after that time and goes on until the end of the trading day, which is around 13:15-13:20, as the closing time of this market is 13:20. The trading hours of this market have changed several times since 2010, but we are going to talk about it later on in this video.

However, we can see that around 13:15, the number of transactions touches a sort of minimum during the day. In fact, starting from this time of the day onwards, the price begins to rise and continues to do it until 4 am the following day.

The Strategy

At this point, if we go and code our strategy in PowerLanguage or EasyLanguage, we get something like this.

As you can see, we go short if we are close to 4 o'clock in the morning and we go long if we are close to 1:10 in the afternoon. Perhaps you might be asking yourself why I added these conditions instead of simply writing T=400 (which means 4:00 am) and T=1310 or 1315 (which means 1:10 and 1:15 in the afternoon). I did it to avoid finding ourselves in a situation in which the bars that close exactly at 4 am and at 1:10 pm should be missing from the chart. So this enables us to open the short positions at the next bar until 4:20 am and, in the same way, open the long trades between 1:10 and 1:20 pm in the afternoon.

Of course, we won't be able to scale in because we set a limit to trade only with one contract. So we have an open position 100% of the time. At 4 am, we go short, and at 1:10 pm, we go long.

Backtest and Results

Now let's check out the results using Soybean's chart with a timeframe of 10 minutes and historical data starting from January 2010. This is the curve we get. Now, you see it, this is an almost 45° curve, and it's very linear over time. The curve of the long trades is very positive. And that of the short trades is also good, even if there was a small retracement immediately after the outbreak of the Covid pandemic. This is mainly due to the huge rise of the Soybean market that took place during this period.

The average trade is only $43, which means that at the moment, it's not enough to cover the trading costs and still be able to take advantage of this market. The number of trades is very high: two per day.

Finally, I'd like to show you the returns made by this strategy year by year. As you can see, not only are they constant, but they are also positive, apart from the year 2020 when it made a very small profit. Nevertheless, this strategy seems to have what it takes to be particularly successful.

We could also analyze these characteristics by plotting the recurring behavior of this market, and this time we can try using different periods. For example, the red line refers to the period from January 2010 to December 2013. The yellow line refers to the period from 2014 to 2017, and so on.

By looking at these lines, we can observe that prices tend to move down from 4 am to 1 pm and move up from 1 pm to 4 am the next day.

Now take a look at this area, which is where the market closes. If you look at the green line, which refers to the period from January 2020 to November 2021, you see that the market was closed from 1:20 to 7:00 pm.

However, the closing times of this market haven’t stayed the same throughout the years that we are using for our backtest. In fact, if we were to consider only the first three years, the market would have opened at 5 pm instead of 7 pm as it does today.

Remember that when we look for recurring patterns and behaviors in the markets, we must take into account all the historical data available. This is why, during our backtest and analysis, we didn't use a default session but opted instead for a custom session that considers all days and all times. So the session we used covers 7 days a week, 24 hours a day, from 5:00 pm to 4:59 pm.

Further Checks and Conclusions

To make sure that the bias we've just found is not a product of overfitting, we can try and replicate the same strategy on another instrument that is very similar to this one. For example, we can use Soybean Oil, which can be considered as the Soybean market’s smaller brother.

So let's go and apply the same strategy also on the BO, which is the Soybean Oil, and the results would be more or less the same. In this case, the year 2020 is losing, but the equity line is still very good, and this confirms the fact that the bias we've just observed on Soybean, with a tendency to move down and up during different parts of the day, must be an intrinsic characteristic of the Soybean market.

And with that, our video is over!

And if you want to dive deeper into the world of systematic trading and learn something concrete about how to build these automated strategies, I invite you to go and check out our free webinar - we're going to leave you a link in the description of this video - and in this webinar, Andrea Unger, the only 4-time world trading champion, will show you the first steps to take to approach systematic trading.

Finally, I also invite you to leave a comment if there are some topics that you're interested in so we can focus on them in our next videos.

And with that, thank you for watching, and I will see you in our next video dedicated to trading tips and tricks.

Until then stay safe, bye-bye!


Need More Help? Book Your FREE Strategy Session With Our Team Today!

We’ll help you map out a plan to fix the problems in your trading and get you to the next level. Answer a few questions on our application and then choose a time that works for you.


Andrea Unger

Andrea Unger here and I help retail traders to improve their trading, scientifically. I went from being a cog in the machine in a multinational company to the only 4-Time World Trading Champion in a little more than 10 years.

I've been a professional trader since 2001 and in 2008 I became World Champion using just 4 automated trading systems. 

In 2015 I founded Unger Academy, where I teach my method of developing effecting trading strategies: a scientific, replicable and universal method, based on numbers and statistics, not hunches, which led me and my students to become Champions again and again.

Now I'm here to help you learn how to develop your own strategies, autonomously. This channel will help you improve your trading, know the markets better, and apply the scientific method to financial markets.

Becoming a trader is harder than you think, but if you have passion, will, and sufficient capital, you'll learn how to code and develop effective strategies, manage risk, and diversify a portfolio of trading systems to greatly improve your chances of becoming successful.