Commodities: The Top Asset Class of 2018 So Far
Is the commodity supercycle coming back from the dead?
For now, such a claim could perhaps be considered both bold and premature – but there does seem to be some compelling evidence that is mounting to back it up.
The Asset Quilt
According to the most recent “Asset Quilt of Total Returns” put together by Bank of America Merrill Lynch, commodities are the top returning asset class of 2018 so far. The chart, which shows the total returns of asset classes over the years, has commodities at an annualized return of 22.7% year-to-date.
Right behind it is gold, which sits at 11.6% on an annualized basis:
|Rank||Asset Class||Total Returns (2018*)|
|#3||Equities (Emerging Markets)||6.5%|
|#4||Equities (S&P 500)||6.3%|
|#5||Equities (Europe, Australasia, Far East)||5.9%|
|#6||Global Bonds (High Yield)||3.4%|
|#8||Global Bonds (Investment Grade)||-2.0%|
*These returns are annualized in order to compare them with past years
Interestingly, commodities haven’t been on top of BAML’s chart since the years 2000 and 2002, which were at the beginning of the last commodity supercycle.
A Deeper Dive
Here is how commodities have fared from 2000 to 2018, based on annual returns. If the commodity sector keeps the pace for the rest of 2018, this will be the best year for the asset class since 2003.
For various reasons, commodities have bounced back in the last three years.
The return of oil prices have helped to resurrect the sector. Ironically, the anticipated metal demand from renewable energy – which will be used to wean society off of fossil fuel consumption – is also a massive driver behind commodities right now.
Not only are base metals like copper, aluminum, and nickel essential for the “electrification of everything”, but lesser-known materials like lithium, cobalt, rare earths, vanadium, uranium, and graphite all play essential roles as well. They do everything from enabling lithium-ion batteries and vanadium flow batteries, to making possible the permanent magnets that generate electricity from wind turbines.
The environment for investing in commodities is the best since 2004-2008.
– Goldman Sachs, February 2018
Not surprisingly, here are how metal and energy commodities have performed since January 1, 2016:
|Commodity||Price Change (Since Jan 1, 2016)|
Some minor metals, like vanadium, have increased by over 400% in price in the last two years. That begs the question: how much room could there possibly be for price appreciation left?
As Frank Holmes of U.S. Global Investors described in a recent post, the last boom was so prolific that investing in an index tracking commodities (such as the S&P GSCI) in 2000 would have resulted in the equivalent of 10% annual returns for ten years.
He also shared this chart, which shows the ratio in value between commodities and the S&P 500:
In other words, commodities seem to be more undervalued than any time in the past 20 years, at least relative to equity indices such as the S&P 500.
Even if the above ratio comes back up to the median of 3.5, it’s clear that there could still be vast amounts of opportunity available in the sector for investors.
20 Common Metal Alloys and What They’re Made Of
You can’t find stainless steel, brass, sterling silver, or white gold on the periodic table. Learn about 20 common metal alloys, and what they are made from.
Every day, you’re likely to encounter metals that cannot be found anywhere on the periodic table.
You may play a brass instrument while wearing a white gold necklace – or maybe you cook with a cast iron skillet and store your leftovers in a stainless steel refrigerator.
It’s likely that you know these common metal alloys by name, and you can probably even imagine what they look and feel like. But do you know what base metals these alloys are made of, exactly?
Common Metal Alloys
Today’s infographic comes to us from Alan’s Factory Outlet, and it breaks down metal and non-metal components that go into popular metal alloys.
In total, 20 alloys are highlighted, and they range from household names (i.e. bronze, sterling silver) to lesser-known metals that are crucial for industrial purposes (i.e. solder, gunmetal, magnox).
Humans make metal alloys for various reasons.
Some alloys have long-standing historical significance. For example, electrum is a naturally-occurring alloy of gold and silver (with trace amounts of copper) that was used to make the very first metal coins in ancient history.
However, most of the common metal alloys on the above list are actually human inventions that are used to achieve practical purposes. Some were innovated by brilliant metallurgists, while others were discovered by fluke, but they’ve all had an ongoing impact on our species over time.
Alloys with an Impact
The Bronze Age (3,000 BC – 1,200 BC) is an important historical period that is rightfully named after one game-changing development: the ability to use bronze. This alloy, made from copper and tin, was extremely useful to our ancestors because it is much stronger and harder than its component metals.
Steel is another great example of an alloy that has changed the world. It is one of the most important and widely-used metals today. Without steel, modern civilization (skyscrapers, bridges, etc.) simply wouldn’t be possible.
While nobody knows exactly who invented steel, the alloy has a widely-known cousin that was likely invented in somewhat accidental circumstances.
In 1912, English metallurgist Harry Brearley had been tasked with finding a more erosion-resistant steel for a small arms manufacturer, trying many variations of alloys with none seeming to be suitable. However, in his scrap metal heap – where almost all of the metals he tried were rusting – there was one gun barrel that remained astonishingly untouched.
The metal alloy – now known to the world as stainless steel – was a step forward in creating a corrosion-resistant steel that is now used in many applications ranging from medical uses to heavy industry.
How AI and Big Data Will Unlock the Next Wave of Mineral Discoveries
Mineral exploration produces massive amounts of data. With AI, geologists can produce geological insights from this data to make the next discovery.
How AI and Big Data Will Unlock the Next Mineral Discovery
Emerging technologies such as artificial intelligence (AI) and machine learning are rapidly proving their value across many industries.
Today’s infographic comes from GoldSpot Discoveries, and it shows that when this tech is applied to massive geological data sets, that there is growing potential to unlock the next wave of mineral discoveries.
Mineral Exploration: Fortunes Go to the Few
Discovering new sources of minerals, such as copper, gold, or even cobalt, can be notoriously difficult but also very rewarding. According to Goldspot, the chance of finding a new deposit is around 0.5%, with odds improving to 5% if exploration takes place near a known resource.
On the whole, mineral exploration has not been a winning prospect if you compare the total dollar spend and the actual value of the resulting discoveries.
Measuring Discovery Performance by Region (2005 to 2014)
|Region||Exploration Spend||Estimated Value of Discoveries||Value/Spend ratio|
|Australia||$13 billion||$13 billion||0.97|
|Canada||$25 billion||$19 billion||0.77|
|USA||$10 billion||$5 billion||0.48|
|Latin America||$33 billion||$19 billion||0.57|
|Pacific/SE Asia||$8 billion||$4 billion||0.49|
|Africa||$20 billion||$23 billion||1.19|
|Western Europe||$4 billion||$2 billion||0.42|
|Rest of World||$27 billion||$8 billion||0.32|
|Total||$140 billion||$93 billion||0.57|
Figures in 2014 dollars. (Source: MinEx Consulting, March 2015)
Aside from the geographic insights, on the surface this data reveals that mineral exploration does not pay for itself. That said, there are still significant discoveries worth billions of dollars – it’s just the returns go inordinately to a few small players that make big finds.
Much of the money spent on exploration may not have produced the next great discovery, but you can be sure it created massive volumes of data that could be used for further refining of exploration models.
So, What is the Problem?
Every exploration failure or success produces geological insights. The mineral exploration process is the source of massive amounts of data in the form of soil samples, chip samples, geochemistry, drill results, and assay results. Each drill hole is a tiny snapshot into the processes that form the earth.
A single drill hole can create 200 megabytes of data and when there are many drill holes coupled with other types of information, an exploration project can produce terabytes of data. If you wanted to compare your one project to hundreds of others to find the best insights, the amount of data becomes dizzying.
All these data points are clues that can be used to find new mineral deposits, but to sort through them is too much for even an entire team of capable geologists.
Luckily, using today’s technology, this data can now be used to train computers to spot the areas showing similar patterns to past discoveries.
The true power of AI will be in its ability to empower technically trained professionals to make decisions in an increasingly complex and data-driven world.
Professor Ajay Agrawal, a noted academic in AI and founder of the University of Toronto’s Creative Destruction Lab, categorizes human activities into five categories:
- Data collection
- Information retrieval
He concludes that machines should do the first three and that humans – such as geologists, doctors, lawyers, investment bankers and others – should make the judgment calls and take the actions based on predictive capabilities of AI.
The mineral exploration industry presents a good example of how AI and big data can help technical professionals make discoveries faster, with less money, using a wide variety of data inputs created.
Opportunity Generator and the AI-friendly Future
AI can take the large amounts of data from many different projects in order to spot the right opportunities to further explore, building on decades of geological data from projects around the world.
The right technology can help reduce the risk inherent in exploration and lead to more mineral discoveries on budget, rewarding those that deployed their data most effectively. Companies that are able to harness this power will tip the scales in their favor.
As a result, mineral exploration is no longer so much an art of interpretation – but instead, it becomes closer to a pure science, giving geologists a whole-field perspective of all the data.
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