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I’m excited to announce that we have launched the new SpreadCharts app today. I was looking forward to this moment for a long time. It took us more than a year of hard work to reach this point.
I’ve made a short video tutorial that will guide you through all the major features. You can also play this video directly in the app.
Here’s a quick summary of what’s new:
Cleaner and better-looking layout
You can assemble whatever combination of charts you wish, you’re no longer limited to our templates
Create many tabs with up to 5 charts in each of them
Analyze several charts for different underlyings in parallel, thanks to synchronization of the x-axis for compatible types of charts
Unified ticker input for both beginners and power users thanks to our intelligent ticker field
Create spreads and ratios out of continuous contracts (for example continuous contango)
Seamlessly switch between roll methodology by expiration or maximum OI for continuous contracts
Faster and more capable watchlist with the ability to segment the records with tags
My trades (still in beta) – powerful tool for portfolio management. Create multiple portfolios and track performance of your trades — automatic visualizations of balance, growth, drawdown.
…and many more improvements
Finally, I would like to thank our team for a great job. We’re also thankful to our premium subscribers because their contribution allowed us to develop the new app. Moreover, we decided to keep the app accessible for free to everyone, so there will be no barrier for beginners. Everyone can start analyzing the markets and learn the way to success using the best tools out there.
Grains are very calm since the autumn last year. This is not unusual after the American harvest. The weather ceases to have any influence on prices and unless some catastrophic weather hits South America. Demand and especially the exports are the only force left to move the market. However, the decrease in volatility over the last two months is unprecedented even in historical norms. There is basically nothing happening in these markets. Take a look yourself:
What has caused the volatility to dry up? There are three reasons from my point of view:
Short term agreement between the USA and China – these countries have been recently embroiled in a painful trade war. Fortunately, they have reached a short term ceasefire on the sidelines of the G20 summit in Argentina at the beginning of December. Especially the commitment by China to resume shipments of US soybeans was significant. However, the key message was the reduction in bilateral tensions, and the likelihood of further escalation has fallen sharply. That led to a decrease in volatility as grains have stopped reacting violently to every Trump’s tweet about China.
Christmas effect – the liquidity over the holidays dries up and trading range tightens. This holiday mood can sometimes stretch over the second half of December. Nevertheless, this effect is only transitory and the cause of no movement in grain prices since the beginning of the year lies somewhere else.
US government shutdown – this was the main reason for the drop in volatility since the beginning of the year in my opinion. The CFTC has stopped publishing new Commitments of Traders data. That affected many traders who lost an important piece of information about the state of the market. Rising uncertainty leads to an unwillingness to open larger positions in the market. Traders were basically holding back, and that surely dampened the price swings. Besides, we also lost the US Department of Agriculture reports. The crucial January WASDE report wasn’t published, so we lost a critical fundamental data.
Why do I think the volatility is coming back into grains and the price moves will become more significant?
Temporary ceasefire in the trade war will end on March 1st, 2019. The US and China should come to a more definitive agreement will then. But there is no actual evidence this is gonna happen. In any case, just the approaching deadline will make markets more nervous and the grains can become more sensitive to speculation about trade negotiations. Yesterday’s information that presidents of both countries are unlikely to meet till Mar 1st is a nice example and it sent grain prices immediately lower.
US government is open. We still don’t have the fresh COT data due to the reasons I have explained in the last article. But the USDA has dealt better with the situation and a crucial WASDE report will get published today. It will also contain the January data besides the scheduled February ones. You can find it here at 12pm Eastern time. We will finally have important information about supply and demand estimates after a long time. And this can cause a significant spike in the market. Keep this risk in mind if you hold a position not only in grains but also for example meats, cotton or sugar.
Everyone who trades commodities or futures on currencies, indices or volatility knows that there haven’t been published any new Commitments of Traders data from Dec 22nd, 2018 to Jan 25, 2019 due to the US government shutdown. We informed you in time about this on our twitter.
Don't look for new COT data in the app after today's close. The CFTC won't publish any new data until the US government shutdown is over.
COT data is a helpful tool for many traders, from small individual investors up to portfolio managers in hedge funds, banks or prop trading firms. All of us were undoubtedly excited about reopening of the federal government this week. This is true also for the CFTC, the federal regulator of futures markets and publisher of the Commitments of Traders report. Together with other people in the commodity business, I was expecting the agency to resume publishing fresh data and gradually release the old missing data over time. Well, we were all wrong.
According to the recent press release, the CFTC will publish the old data first. To be precise, the data that should have been published on Dec 28th, 2018 will be published this Friday, Feb 1st, 2019. The rest of the data will be gradually published in the coming weeks, starting with the oldest data. In order to catch up with the present timeline, the COT report will be published twice a week, on Tuesday and Friday, until all the old reports get released. If I calculate it correctly, we shall get the first fresh, undelayed issue of the COT data on Friday, Mar 8th. That’s more than a month away from now.
COT data aggregation is an automated process in these days for all the reporting subjects. I therefore wonder why it will take CFTC so long to release all the data. Maybe there are some law and regulatory aspects in the process we don’t know about. On the positive side, the delay of the COT data you can see on SpreadCharts will gradually decrease.
Although the lack of fresh COT data is unfortunate, it’s just one part from the analytical toolbox in the SpreadCharts app. We can find some great opportunities even without COT. Take grains for example. We opened a position in CBOT wheat bull spread this week.
The carrying charges analysis suggest that current running average will finish below 50% of the full carry and we get a storage rate cot for wheat. In that case, the rate would drop to the ground level of 0.165 cents per bushel per day. That can start pushing bull spreads higher which would turn our spread into profit. We analyzed this opportunity in detail in the latest issue of the Spread report.
Crude oil is undergoing a bounce, but should remain under pressure for the rest of 2019…this is what we have predicted in the last issue of the Spread report our premium subscribers received on the New Year’s Eve.
Oil has fallen sharply and has become short-term oversold. The price is however not yet super cheap when compared with the last few years. It is therefore likely that we will reach even lower prices in 2019. But there will be bounces on the way #CL_F$USO#OOTT#CrudeOilpic.twitter.com/9gQVp03pcJ
Today, I will take a closer look at the situation in crude oil and also mention natural gas briefly. I will describe the fundamental or rather geopolitical forces behind this outlook and outline the strategies suitable for this environment.
We may get strong relief rallies like the one we witness right now. Nevertheless, the market has fundamentally changed and we don’t expect the bull market to resume anytime soon. Our key prediction is that oil will stay in contango for most of 2019 as this is the best indicator reflecting conditions in the physical market.
I think so because of these reasons:
Political system in the US – although rising oil price contributes positively to the overall US economy, the drilling is concentrated mainly in just two states (Texas and North Dakota). Economies of these states heavily depend on crude prices and they profit from high price. On the other hand, the rest of the states benefit from low oil prices. President Trump desperately needs to be reelected in 2020 and would put a great effort into keeping the oil price low. The electoral system in the US is based on federalist principle where each state elects the appropriate number of electors out of the total 538 members of the Electoral College which then elects the President. The voting system varies among the states. Most of the states, however, employs the majority voting system, meaning that winner in such a state takes all the electors. Because of this, the so-called swing states, where both republicans and democrats are head-to-head, usually decide the outcome of the elections. While Texas and North Dakota are deep red states and Trump will likely win there anyway, people in the swing states are sensitive to the oil price and rising oil and gasoline prices would hurt Trump in these states.
Trump’s leverage on the Saudis – Saudi king Salman and especially his powerful son, crown prince Muhammad bin Salman built their domestic political influence on the close alliance with Donald Trump. Although the succession to the throne is clearly set, it doesn’t automatically secure position of the future king. The Allegiance Council of the senior members of all the royal family branches plays a big role in the confirmation of new king. The murder of Jamal Khashoggi in Turkey greatly weakened the position of the crown prince. Despite his control of the armed forces, he can no longer be absolutely certain someone wouldn’t attempt to steal the throne from him after his father dies. The greatest threat seems to come from the sons of the previous king Abdullah. The US support can play a key role in such a delicate situation. President Trump has so far embraced Muhammad bin Salman and this support won’t come cheap. He has publicly pressured the kingdom to pump enough oil to prevent prices from rising too high.
Slowing global economy – significant slowdown of the global economy would most likely be the event that will push the oil into a bear market. And this is exactly the scenario we witness right now. Although the developed economies are still doing well, the emerging markets are already decelerating. In fact, the emerging markets were responsible for most of the growth in oil consumption over the years. Their weakness has therefore profound impact on the crude oil market.
Rising production – USA is the world’s largest crude oil producer and has recently become a net exporter. That’s an unbelievable change compared to the fundamentals (and sentiment) just a decade ago. Moreover, production in Saudi Arabia and Russia has also gone higher over the months. And the situation in Iraq and Libya has stabilized.
Every prediction has its risks and there is always an alternative scenario. My base case scenario can be threatened by:
War in the Middle East – any conflict in this part of the world would likely push the oil price much higher, as we have seen several times in the history. The greatest risk lies in the escalation between Israel an Hezbollah or the Iranian proxies in Syria. The second Lebanon war showed us how a miscalculation can lead to a full-blown war. Both Israel and Hezbollah publicly state they’re not interested in the war right now. On the other hand, they admit the war is not a matter of if but when.
Massive stimulus to the global economy – a 180° turn in the FED policy would be necessary. Just slowing down the pace of rate hikes wouldn’t be enough. I’m talking about reversing the rate outlook and ending the quantitative tightening. Such an aggressive change in the FED policy is very unlikely, especially in the short term. Another way would be a loose fiscal policy. However, there doesn’t seem to be enough political will in the US to pass another stimulus like Trump’s tax cut.
The administration is unlikely to get it through Congress after the Democrats have taken control of the House. Such obstacles don’t exist in China. Nevertheless, the current path of gradually loosening monetary policy is a safer bet. Fiscal stimulus is unlikely due to the reduced marginal utility of any new debt which is common in heavily indebted economies.
Seasonality analysis is a great tool. Many people, however, use it incorrectly. Their approach is too dogmatic as they time their trades with a daily precision, based on the seasonal average curves. Albeit useful, seasonality gives us only a limited knowledge about the current state of the market. It only shows us past trend over some period in time. We described the caveats of seasonality in this article.
Regarding the seasonality analysis, I prefer more of a Bayesian approach. That’s the reason why we have uncertainty estimates of the seasonal averages on SpreadCharts. I consider these color channels inseparable from the averages themselves. They tell us how reliable the averages truly are. A nicely trending averages may be just a lucky coincidence in the data.
Nevertheless, I wasn’t really satisfied with the mean absolute deviation (MAD) we used to calculate uncertainties. While the algorithm itself is fine and robust, the selection of the underlying data (individual years) ignored different fundamental valuation of each year. I.e. the contract can trade at higher price level just due to the different fundamentals. It has nothing to do with seasonal effects.
Therefore, I devised a new way how to calculate the color channels. A 50-day rolling 2nd standard deviation is calculated for each year. Mean of the previous 5 and 15 years makes the half-width of the channel. And that’s all. Very simple, yet powerful way how to get rid of the different price level over the years, while keeping the overall variance preserved.
This is how it looks for popular bear spread in corn (ZCN19-ZCZ18):
In the last part of the commodity spread trading series, we started with seasonality. Every spread trader should know why it exists, but also know its advantages and disadvantages. At the end of the previous lesson I wrote the sentence: “But the seasonality itself is not enough for me!” Today I will explain why this is the case and how my trading system puts more weight on other analyses.
When seasonality fails
We already know the main thing behind seasonality are the weather cycles. Yes, the longer-term weather changes throughout the year are very similar each year. But can we rely on it with our money? I think we can not. As you know, the weather is mostly unpredictable in the short term. We can experience normal weather for 10 years only for the 11th year to be totally different. This may be due to oceanographic phenomena known as El Niño or La Niña for example. They have the power to cause major changes in temperatures and also affect rainfall in important agricultural areas in key parts of the year. These phenomena can have adverse impact on crops and turn the seasonal normals upside down.
One typical example was the drought in 2012, which caused a sharp rise in grain prices. Do you think seasonality played a role there? Unfortunately, no. The following chart with detailed seasonality of the well-known and popular bear spread on corn July – December is the proof. Notice the grey curve that looks like it doesn’t belong to the chart. That’s the 2012 year when the spread has fallen off the cliff, contrary to otherwise reliable seasonal trend during that part of the year. If a trader relied only on seasonality while having bad risk management, he suffered a lot.
Nothing works forever
Many of my students and my colleagues used to trade just with seasonality analysis. It was working perfectly for a few years. All they had to do was just to follow some seasonal signals. They had become overconfident and convinced that trading is easy, and it will be forever so. Then came an abnormal year when seasonality suddenly ceased to work, and their losses were often huge . They were stubbornly sticking with their open positions, trusting seasonality and expecting a turnover. They were saying, “Seasonality must eventually prevail.”
These traders often did not even know what they were doing. They did not know what drives inter-delivery spreads or what it means to hold bear or bull spread (especially with regard to risk). They didn’t understand contango or backwardation effect, etc. However, if you have gone through this commodity series from the beginning, you have a big advantage. Spreads are pretty much understandable, and they give you a more in-depth look into the markets. That’s why beautiful seasonal curves won’t seduce you anymore.
Seasonality as a rear-view mirror
I often compare seasonality to the rear-view mirrors in a car. No doubt they are very important when driving. We can see what is behind us, whether some car is overtaking us, etc. Without the mirrors, we cannot drive safely. But can you imagine driving only by the rear-view mirrors, for example with a darkened windshield? I don’t think so! You need to know what’s ahead of you, what obstacles to avoid, whether you can speed up or rather slow down. It works the same in trading. We need to see the current state of the market! Keep following indicators that tell us what’s ahead of us. Trading based just on the fact that something worked in the past is not enough!
Seasonality is like a look into the past. It can tell us how a given futures contract or spread tends to behave in a certain period. But it won’t tell us what’s happening right now. Entering or exiting the positions using just seasonality does not lead to stable results in the long term.
What if a market changes?
In addition to weather, there may also be some fundamental long-term change on the market, whether on the supply or demand side. Here are just a few examples:
– new mining technology / producing method of a particular commodity -> higher supply (e.g. fracking in crude oil and natural gas)
– the emergence of a new industry that increases the demand for a particular commodity (biofuels industry increases demand for corn)
– a new more resistant breed, a method of processing, etc. (genetically modified plants, resistant to diseases)
Seasonality gives us zero information about the changes that are happening on the market. For this reason, we have to work with other analyzes. These include, for example, COT analysis, market structure analysis, analysis of carrying charges, and others. We also need to understand how spreads work. Why to choose a specific strategy, what are the advantages and disadvantages, what to watch out for, etc. You already know many of these things, and I will write about many others.
At the end of this article, just for curiosity, I attach seasonal analysis of one bear spread in crude oil, particularly between February and January. You may notice a perfect rising trend. Despite that, one year is clearly out of sync…
After thirteen parts of the spread series, we have the perfect base for trading commodity spreads. Now we can go to the specific analyzes I use to select the right trade. In the last part, I have offered a glimpse into seasonality and today I will focus just on this topic. There is no doubt that seasonality is an indispensable part of spread trading. What may surprise you is that I, however, consider it just a secondary factor in selecting my trades. Let’s explain why.
Seasonality and weather
Seasonality is a widespread phenomenon we encounter in our everyday lives. A typical example is the temperature change during the year that affects all of us. Let’s demonstrate this for example on home heating. Our heating costs are logically the highest in winter as it is the coldest part of the year. We expect temperatures to gradually rise during springtime. Our heating costs will therefore decrease. In the summer the temperatures are the highest, and we do not have to heat our homes at all. In the autumn, however, a colder period begins again, and expenses start to increase again. This cycle repeats every year. These temperature trends are not working with daily precision. Sometimes the winter can be very mild, or there can be freezing temperatures in spring. Nevertheless, it holds true in the long term.
Seasonality and tomatoes
My favorite example is tomatoes, more precisely their prices. You have certainly noticed that tomatoes are the most expensive in the winter. It’s obvious because they don’t grow in winter on the northern hemisphere (with exception of greenhouses). The vast majority of tomatoes is imported, which is also reflected in their price. On the contrary, in the spring, when the local producers begin to supply more vegetables to supermarkets, prices tend to fall gradually. The price is the lowest during summer as there is plenty of tomatoes everywhere. This repeats every year. Of course, I talk only about change and price direction, not the exact price levels.
Seasonality and commodities
The same effect is observable in most commodities you can trade on the exchange. The more commodity is supplied to the market, the lower is the price. Conversely, when there is a less commodity on the market (or demand exceeds supply), the price goes up. This is the essence of price trends and at the same time a basis for understanding seasonality. To be precise, seasonality is the result of uneven distribution of supply and demand over time.
A typical example of supply fluctuations during the year can be seen in grains. In the previous article I wrote about corn. The cyclic waves were clearly visible in the term structure chart, which is caused by a new crop hitting the market after harvest each year. On the demand side, a typical example is natural gas or heating oil. The natural gas term structure can be seen in the following chart. Repeating waves are evident at first glance. Note that the market expects the highest prices in the winter months due to increased heating demand.
For natural gas, we notice cyclical patterns in demand, while for corn it’s in supply. Both are influenced by one thing – climate. Various influences can cause seasonal patterns. But the weather is the most important one. That’s why seasonality works so well. Because it is based on natural cycles. However, you need to be very careful about the right way how to understand it. Seasonality works well over a long period of time. Moreover, the seasonal effect is not precise. It doesn’t kick in on the exact calculated day. Sometimes it may not even show up at all. It is not guaranteed that tomatoes will be the cheapest tomorrow or that the first snow will come on December 1st.
When you start analyzing seasonality, it is very important to realize this fact. Many traders, however, use seasonality solely and have the whole trading system based on it. Many different procedures and methods have been developed to optimize the entry or exit from the trades. But the seasonality itself is not enough for me!
What can you expect next time?
Next time, we will continue to explore the seasonality. It is simple to use, but there are a few other things I would like to tell you. For example, what charts should you watch and how to work with them.
In today’s article, I would like to sum up everything we have discussed so far. We will delve into the very popular corn market and take a look at the spreads we can trade here. We will find out which combinations of spreads will be the best in our case.
When you analyze some market, it is a good idea to start by looking at the market from a certain distance. This is where contango histogram comes very useful. It can quickly show us what type of market we’re dealing with. The first chart shows the contango distribution between the first and second expiration month and the second chart between the second and third month.
I think it is immediately clear that the market has been in contango over the last 3 years. We can get this information straight from the table in the top left corner. In such a market, the bear spreads are usually the right strategy (the reason was described in the previous article).
What spread combination to select?
You already know that there are many ways how to combine different expirations in interdelivery spread trading. However, when considering the success rate and the overall risk, the right expiration selection do matter. Here’s where the term structure charts is of great importance to us.
The term structure can tell us valuable information about the market, which we would otherwise only get through a detailed study of supply and demand. It’s because supply and demand trends are ultimately reflected in the shape of the curve. Thanks to this, we can observe a variety of ripples, switches to backwardation, etc., which tend to repeat over the years.
At first glance, there are two peaks where the curve is noticeably cut off. Specifically, it is July. September contracts are already at a lower price. The reason is simple. Corn harvest begins in September. The market, therefore, expects increased bid, which logically pulls the prices down. Term structure clearly highlights which contracts belong to the same crop. They are December up to July of the following year.
Why not September? This contract is generally not very popular due to the risk of mixing two crops. It is not certain whether the September contract will fall into the old crop. However, in December it is certain that it already belongs to the new crop. Moreover, we also know that July still belongs to the old crop because there is still no chance that harvest begins at this time. I’m talking about the US corn, of course.
When I summarize this, we will mainly trade bear spreads in corn. As we have already explained, bear spreads profit from contango, which we can observe mostly within a single crop. That’s another logical point. The price is usually the lowest after the harvest when a lot of new corn lands on the market. Gradually, as time goes by, corn supplies are shrinking, and therefore the market expects higher prices. Of course, let’s not forget the storage costs, which also play a role here.
We trade bear spreads in such a situation when we do not expect any big surprises in the market that would cause a spike in commodity price. We want a normal market (i.e. contango), falling commodity price, or movement roughly sideways.
The most popular and most liquid bear spread in corn is July next year – December (currently ZCN19-ZCZ18). That’s the widest possible spread within a single crop. From the price/carry ratio analysis, there is a clear rising tendency of spread at first glance.
This increasing tendency can also be seen on the seasonal averages.
Of course, there are many possible combinations of spreads within a single crop. For example, March next year – December (currently ZCH19-ZCZ18) or July next year – March (ZCN19-ZCH19). These are narrower spreads with a lower risk.
Today I delved more into seasonality. It is undoubtedly an inseparable part of trading commodity spreads. However, it is crucial to use seasonality correctly. And we’ll look at it next time.
You may think that this is not possible when you are reading the headline of this article. Something that does not move cannot make you money. However, it is indeed possible, when it comes to interdelivery spreads. Of course, it is necessary to fully understand the principle of spread behavior as well as the structure of the market.
If you have well understood the previous parts of our spread series, you may already know where I am heading to. In the article about spot price, I have revealed the principle of spread movement. Let’s remind us a part of it.
The spot price is the price of the commodity with immediate delivery. The term structure acts as a magnet. Therefore, it attracts the closer contracts more. This means that when the spot price rises, usually the nearest contracts are rising more than the others. When the spot price falls, the closer contracts are falling more than the others.
Good. But what if the spot price does not move up or down? In other words, the market moves nowhere.
As I have already written, the spot price is the price of some commodity with immediate delivery. No storage costs are therefore included here. In the normal market, when nothing special happens, the more distant contracts are more expensive (the market is in contango). Storage costs play a role here.
However, if the spot price does not move, contracts must gradually move closer to the term structure, i.e. they converge to the spot price. The closer we are to the expiration, the lower are the storage costs associated with each contract. Therefore, the difference between the spot price and the futures price gradually shrinks.
Do you remember the connection with the magnet? The nearest contracts are pulled to the spot price fastest. And by the way, we’re still talking about contango here. Therefore, the spreads between contracts are widening over time without the spot price moving in any direction.
What spread we should choose?
Bear spread or bull spread? Imagine a situation where the market is in contango and the spot price moves in a narrow price range over a few weeks or months. At this time, a closer contract (let’s say, December contract for corn) gradually converges to the spot price. However, it converges faster than a more distant contract (for example, a March contract for the following year).
Does it remind you something? If not, return to this part. When we expect a closer contract to decline faster than a more distant one, we are choosing the bear spread strategy. This means that we sell the near contract and we buy the more distant one for hedging purposes. In our example, it is the ZCH19-ZCZ18 spread in corn.
If the contango is strong enough, the spread can even rise despite the slightly rising price of the underlying commodity. Which is unusual, because bull spreads should profit in such a situation. Nice example is often coffee. This market is in contango majority of the time, we can see it on the contango histogram.
On the next chart, you can see an example when bear spread has gone higher (blue curve), while the price of the underlying (coffee futures) also grew quite significantly (purple curve).
These unusual movements of bear or bull spreads are a good indicator also for futures traders. Term structure behavior often tells us what’s going on “behind the curtain”. In other words, structural changes in the market often lead the price itself. It can help us better predict future price movements of the underlying asset.
Next time, we’ll finally take a look at the long-promised topic – choosing the right combination of contracts in a particular market situation.
We have learned a lot in the past ten parts of our series about commodity spreads. We already understand what spreads are, how to trade them, and how to build your own strategy based on the current market situation. Great! Today I am going to explain a slightly more advanced thing that I use very often in my trading – contango histogram.
Small glossary at the beginning
When we talk about contango in general, we can think about both contango and backwardation. Contango generally refers to the market structure and it is calculated, similar to bear spreads, as the difference between the price of the more distant contract and the closer contract divided by the price of the closer contract. For example, for the first two expiration months, it is calculated as (F2-F1) / F1. Consequently, the contango is positive when the more distant contract (F2) is more expensive than the closer one (F1). Such a state of the market is commonly referred to as contango.
The opposite situation is a negative contango, for example, when the F2-F1 difference is negative. The first expiration month is therefore more expensive compared to the more distant one. This state of the market is referred to as backwardation.
And now we can start with the contango histogram. Horizontal axis represents a contango rate. First, we need to find a zero bar that is represented by the lighter blue color. To the right of the zero, the market was in contango and on the left from zero in backwardation. The vertical axis of the chart then represents the frequency in days. It is very straightforward. The value of each column on the vertical axis tells us how many times the the selected combination of contracts has been at a certain state of contango over some period of time. This means that the higher the column is, the more often the market was in the given state. And vice versa.
The following chart shows the contango histogram for corn, namely the combination between the first two expiration months over the past 15 years.
Thus, the Contango histogram shows the distribution of the contango for the last year, 5 years, 15 years, etc. It is an excellent tool because it is evident at first glance in which state the market has been the most often. And that’s very useful information for us as spread traders.
However, the vertical color line is very important here. It simply highlights the current contango rate. Thanks to it, we can compare the current state of the market with historical data. At first glance, we can see if the market is in the normal state and there is nothing exceptional, or whether the market is in an extreme situation.
This is not all what SpreadCharts application offers when we speak about histogram. In the top left corner, you’ll also find the frequency of the positive contango for the selected combination of contracts and time period. For example, the following chart shows a soybean histogram. And we can see here that between the second and the third expiration month, the market was in contango in 63.1% of the time over the past five years. The rest of the time the market was logically in backwardation.
We have already explained how to correctly assemble a spread. However, one question remains, and it’s how to choose between various available expiration months in a particular situation? Sometimes we have fewer options, sometimes more, but we always have a choice. We’ll look into this next time.