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The Copper market (HG) responds well to different approaches: trend-following, bias, mean-reverting ...
This video shows you how to create a bias strategy that takes advantage of this market's recurring intraday behaviors.
By watching the video, you'll learn:
- How to identify recurring trends in the session of Copper
- How to create simple rules to exploit them (a 4-line script is enough in MultiCharts or TradeStation)
- How to test and evaluate the system
Hey guys, welcome back!
Today we're going to be focusing on the specific characteristics of a market that belongs to the metals sector: Copper.
This market has several characteristics that we can exploit in our automated strategies, from trend-following to mean-reverting. And today, we're going to be focusing on the bias approach and build a trading system that takes advantage of the recurring behaviors in the session of Copper.
I'm one of the coaches of Unger Academy.
Intraday bias on Copper
So, here you can see an internet page. More precisely, this is from the intradayseasonals.com website and shows the intraday trends of the Copper market, which is the market we're focusing on today.
Here you can see the statistic trends of the Copper market over the years. Noe the period of reference for this chart- - you can see it here - goes from 2006 until today. Looking at this chart, we can notice a strong downtrend during the Monday session, which is also slightly related to the movements that take place on other metal markets. Tuesday and Wednesday, instead, seem to have a mean-reverting tendency, with prices that tend to return to average levels. Finally, we can see a small rise on Friday, although historically, this market has gone down rather than up.
Now, I'd like to point out an aspect of this market that I consider very interesting. I'm talking about Copper's tendency to rebound during the second half of the day. After the strong falls that occur in the morning - you can see it on Wednesday but also on Thursday, when perhaps it's a little dirtier, as well as on Friday, when it's also quite dirty, we see that downtrends are followed by a tendency to rebound, as shown by these cases.
But what time does this happen? On Wednesday, it seems that 8 am is a good time. 8 am exchange time, so Chicago time... No! New York time. Sorry. On Tuesday, too, we can see that the time is more or less the same, because in this case, the lowest point is touched at 7:30 am, according to these statistics that start in 2006. This statistic behavior is also confirmed on Monday as well as on Thursday when the market touches a low level around 8 am. And the same goes for Friday. So the cleanest days for this type of bias seem to be Monday, Tuesday, and Wednesday, whereas this bias tends to deteriorate slightly towards the end of the week.
Insights into the bias
But let's go into more detail and see if this bias... Or rather, how this bias has behaved over the years to figure out if it's a stable and recurring idea that we can exploit in our systems. So to see if it's solid or if, instead, it's a random tendency, a sort of spurious correlation, something that derives merely from chance.
In this chart, you can see some different curves, and each of these curves refers to a different period. Let's take a look at the key. The blue curve goes from January 2010 until October 2021, so almost till today. We can consider this curve as cumulative since it includes the entire historical period that we are taking into account. Then in orange, yellow, and green, we have three other equity lines, and each of them is calculated only on historical intervals of 3 years. So the orange curve goes from 2010 to 2013. The yellow curve goes from 2014 to 2017. And finally, the green curve is from 2018 to 2021.
By looking at these curves, we can immediately notice that the various lines - those that refer to limited historical periods, so the three-year curves - are not so distant from the average, which is the thicker curve in blue.
So what could be the meaning of this? This suggests that there can be years when this bias works better, such as... I don't know... let's say from 2010 to 2013, when the short side actually would have worked far better than the hypothetical average. And in this case, even the worst result, which is the yellow curve, would have been very close to it. So it does seem that this behavior could be quite stable both on the short and long sides.
Strategy and backtest
At this point, what we can do as systematic traders is to build a trading system based on the information that we've just collected. And we can do it in just four lines of code. Here, in the first two lines, you can see the entry conditions for the long trades. So if the time is greater than or equal to 8 in the morning, which as we have just seen can represent a turning point for the market when we can expect a rebound to take place, and it's less than 8:15 am (we use this condition to limit entries to this specific time window), then we will buy the next bar at market. I mean it's that simple.
Now, what time will we close long trades? At 10:15 pm we will close at the next bar, and then we will sell the newly bought contract at 8 am. On the short side, we enter at 1:00 am, and then, between 1:00 and 1:15, we close the positions just before entering long. So a quarter of an hour before eight, we use the "buytocover" command and close the short position and then go long again at 8 am, in this infinite cycle that exploits the bias of the Copper market.
Let's go and see how this very simple strategy would have worked in recent years. There are no conditions that filter the trades, so we’re going to see all the different scenarios. The system will go short every day at 1 am and then go long at 8 am. This applies every day, and in all cases, and in fact, as you can see, there's a constant number of trades that take place every day, and this number is two. So you see it, the strategy is actually doing what we want it to do. The long trades are opened at 8:05 am, which is the first bar after our reference time for the long entries, which is 8 in the morning. Then these long trades are closed at 10:20 pm, and after that, the system goes short at 1:05 am, which is the bar after 1 am. Then we close the position with the "buytocover" command at 7:50 in the morning, so 10 minutes before we go long again.
From 2008 to today, this strategy would have performed quite well. Let me show you the short side first. As you can see, it seems that it has deteriorated a little bit in the last part of the backtest. Perhaps this can be due to the sharp rise we have seen in the entire commodity sector, Copper included, over the last few months. The market went through a long uptrend, and this has obviously created some problems to the short side of our strategy, as we can see here.
On the other hand, the long side was able to take advantage of this last period. Anyway, we can see that all in all, both sides work pretty well and are in line with what we have observed in the previous charts.
This is the overall equity curve of the strategy. As we have seen before, you can see that it seems to be pretty constant over the entire historical period.
If we look at the annual returns represented as a histogram, we can see that between 2008 and 2013 or 2012, let's say, the results are much more significant. The profits are higher. Market volatility was also very different. And then from 2013 until today, the profits have been significantly lower, but the system was still in gain. So we could say that perhaps the bias has faded a little bit over the last few years, but in any case, it has always been able to perform pretty well.
Obviously, here there are about 500 trades per year. As you know, there are about 250 trading days in one year, so if we make two trades a day, we get these 500 trades.
Let's go and check out the average trade of this strategy, which, as mentioned, at the moment is extremely basic since the only conditions depend on the times of the day. Here you can see that the system makes an extremely high number of trades, and consequently, the average trade is somewhat limited. I remind everyone that the tick, so the value of one tick on the Copper market, is $12.50. This means that $60 is slightly more than 4 ticks, and so it may not be enough if we consider slippage costs on this market.
So at the moment, this certainly is the sore point of this strategy. A strategy that, as mentioned, is still very basic. So this means that we could decide to limit the short entries only to the days when the short bias is actually stronger and do the same for the long side. So simply limit the long entries only to the days of the week when this bias is stronger.
As always, the possibilities are endless. You could also add a stop loss, add some patterns, and additional conditions to increase the average trade and further refine this trading system. But I leave it to you so that you can deepen your knowledge and create those new strategies.
We really hope this video has helped you.
Don't forget to leave us a Like. And if you have any questions for us, write them in the comments! And if they are interesting, hey, we'll make videos based on them.
Also, in the description of this video, we're going to leave you a link to a completely free webinar made by the 4-time world trading champion Andrea Unger who explains the steps he took to become an independent trader.
'Till we see you again, goodbye everyone!
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.BOOK YOUR FREE STRATEGY SESSION NOW >>
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.