Is Asteroid Mining the Next Gold Rush?

Over the year’s I’ve read about a handful of space mining companies. As someone who’s participating in the existing mining ecosystem, there’s always a thought in my mind; could we get disrupted? It happens to everyone eventually, why not mining right now? Despite this thought, it’s impossible to not be skeptical about these sorts of propositions. I mean, mining companies struggle to generate economic returns on earth. How the heck could they pull off anything in space.

I understand the appeal that asteroid mining provides. For those of us that believe humanity’s exponential growth will outpace resource supplies, the unlimited resources of space provide a comforting proposition. I don’t disagree that there are massive resource supplies in space, which some proponents value in the quintillions! It’s worth highlighting, though, that there are a lot of “resources” on earth. The question isn’t how much there is. The question is what can be mined profitably.

I started getting into the weeds on this topic after reading an article recently published in the Journal of Mineral Economics titled “Mineral scarcity on Earth: are Asteroids the answer”. Funny enough, this twitter post jumped up on my feed at the same time. Seems to be a timely question…

What Would it Cost?

When thinking about the feasibility of space mining, we need to ask ourselves two questions: 1) what will is cost, and 2) what will it provide ($). It’s my opinion that no one truly knows how space mining would occur from an operational perspective. The reality is that the “technology to excavate and refine metals in situ in a near zero gravity setting”1 has not been invented yet. While this is the case, we know how metals are extracted on earth and there are a few interesting points that we can look into.

When I think about space mining, I think about a rocket getting fired into space with some mining equipment that gets dropped off on an asteroid. The mining equipment collects and concentrates the minerals. When a large enough payload is collected, the rocket transports the material back to earth. The first question we need to ask ourselves is, what would it cost to get a reasonable supply of mining equipment onto the asteroid or, much less, outside of Earth’s atmosphere.

Source: https://www.futuretimeline.net/data-trends/6.htm

This interesting chart shows how much it has costed through time to launch 1kg from earth into low earth orbit (LEO). LEO is not an asteroid. For our purposes, however, this cost can be used to illustrate what it would cost to get mining equipment into space.

The picture above is a CAT 930E haul truck. A fairly run-of-the-mill piece of equipment at an operational mine on Earth. Obviously, I don’t expect a haul truck to perform too well in a zero gravity environment. I’m using this example to cost out space mining as it is indicative of the huge amounts of physical resources that are used in mining. While this haul truck may be an egregious example in isolation, the reality is that mining operations (at least on earth) require drills, trucks, shovels, crushers, mills, and refining facilities. The true requirements to convert rock to metal are truly staggering

A 930E haul truck weighs 210 tonnes. As shown in the chart above, the Falcon Heavy can transport material to LEO for $950/kg. Nasa’s goal for 2040 appears to be $90/kg.

If we use the equivalent weight of 10 haul trucks as a proxy for the construction weight of a small mining operation, this would cost about US$2B for launches. Again this ignores the costs of actually getting this material to the asteroid, the equipment costs, space fabrication, etc. For simplicities’ sake, let’s say it costs 3x this amount to get the asteroid mine up and running ~$6B in CAPEX. Large mines on earth cost $1-$2B. For earthly profiteers to go to the hassle of getting to space there’s got to be some sweet metal up there!

What Will It Provide ($$$)?

Let’s ignore the price impact associated with “flooding” the earth with space metals and assume that existing metal prices remain constant. How much value could be on a single asteroid?

The paper that I referenced earlier highlighted grades for a potential asteroid. It is worth noting that the concentration of gold on an asteroid is very low (hardly economic if it was on earth). I imagine that the author’s asteroid prospecting experience is probably lacking so this information should be qualified with a big question mark regarding its validity. It’s interesting, however, that the example that was chosen highlighted that gold grades on asteroids are really unimpressive.

Source: “Mineral scarcity on Earth: are Asteroids the answer”

If we assume 100% recovery of the metals (which is impossible). The in-situ value of a tonne of asteroid rock would be approximately $1.4M. This is a lot! I mean, on Earth, a “good” open pit orebody would have an in-situ value of $100/tonne. This 1400x higher!

Unfortunately, however, I don’t think this cuts it. We haven’t really talked about operating costs or how this material would be making its way back to earth. It’s not like you can just push it into the atmosphere and it’s going to land at a refinery. Remember that cost to transport material into LEO works out to about $950,000 per tonne. If we assume that operating costs of a similar magnitude are required to blast, concentrate, load, and bring this material back to earth are required, then operating profits are reduced to $500,000 per tonne.

We, however, we need to think about transporting this material to smelters and refining the metal. If we assume that 90% of this material is payable (after smelting costs) and a further 20% is costed as part of transportation, the net revenue per tonne falls to US$350,000.

To produce US$1B in free cash flow per annum the operation would need to transport 2,800 tonnes of material back to earth per year. Maybe this is possible. Who knows? Even it was, this would produce an annual return of 15%; not too stellar given the risks.

Takeaways

After looking through the numbers:

– It appears that the economics associated with space mining are pretty poor, even after assuming some very low capital numbers

– Even if space mining was economic, the gold grades on an asteroid really aren’t compelling when compared to the grades on earth

Given these points the prospects of “gold raining down like sand” appear pretty poor. Good luck!

References: 1) Mineral scarcity on Earth: are Asteroids the answer, Dahl et al

Skin in the game

The worst problem in mining is the industry’s expertise in destroying capital. Investors hold their breath during commissioning as they await the inevitable bad news pertaining to capital overruns, recovery shortfalls, or grade issues. I’ve become increasingly cynical over the years with a baseline assumption that all projects will underperform. The question is not if, but by how much these investments will disappoint.

Sure, there are the odd examples of success. In general, however, projects that have been built in the past ten years have disappointed.

Take a look at each of the following charts; underperformance in grade, underperformance in throughput, underperformance in production. The results are remarkably consistent. Why is this the case?

It’s a problem of incentives, no feedback loops, and a lack of skin-in-the-game. These “independent” 43-101 technical reports are often anything but. Feasibility study managers or coordinators organize and pay-the-bills of the various consultants that support the reports. Each component is an isolated silo. 

A modeler can produce an estimate with a robust global estimate but a riskier high-grade distribution. The mine planner, ignoring the concept of model risk, will maximize the NPV by accelerating mining to get this higher-risk ore into the mill quicker. On paper the additional capital required to mine in this fashion is justified. In reality, the high-grade may get mixed with other material rendering the strategy useless. Individually, each of these experts are maximizing the project’s value within their domain. Collectively, each of these experts are driving the project to economic failure.

This scenario is repeated again and again. Study managers are incentivized by producing a project with the highest IRR possible. Independent consultants want to please the manager. We know where this leads to.

For this system to evolve it needs feedback. Unfortunately, the time period between feasibility study, construction, design, and evaluation can take 5+ years (in a good case). The individuals that are leading these reports and teams aren’t sticking around to learn from these mistakes. Even if they did, a seasoned leader might get 3-5 of these examples in their career. There just aren’t any detailed case studies to learn from these mistakes. This seems like a big shortfall for our industry. 

Looking For Torque in the Gold Space, Think Again

In a recent Sprott Money podcast, Eric Sprott discussed the merits of investing in high-cost producers during gold bull markets (https://www.sprottmoney.com/Blog/when-you-contemplate-negative-interest-rates-i-would-rather-own-gold.html). The intuition is simple, a high-cost producer may only produce $100/oz of cash at a $1,200/oz gold price. When prices jump to $1,300/oz, net income effectively doubles; why wouldn’t the share price jump with it? The math does not lie, but I thought it would be worthwhile to investigate the validity of this statement in the context of current market performance.

YTD, gold prices are up approximately 5% or $60/oz. That is a sizeable amount, enough to produce a material increase in profits for high-cost gold producers.

Let us take a look at Detour Gold as an example. In 2018, the company produced 610,000 oz of gold at an all-in-sustaining cost of $1,158/oz (https://www.detourgold.com/investors/news/press-release-details/2019/Detour-Gold-Reports-Fourth-Quarter-and-Year-End-2018-Financial-Results/default.aspx). With this production, cost, and a realized price of $1,268/oz, they produced adjusted net earnings of US$64.2M. At today’s gold prices, using last year’s production costs, we could expect earnings to increase by 65%. This statement is a simplification of reality as production costs are inherently variable as is production. The underlying notion, however, that low-cost producers have more leverage to the gold price is true (a small increase in gold prices can make these miners much more profitable).

So given the increase in gold prices, my hypothesis is that we should see a positive correlation between production costs and 2019 returns. Well, let us see what the data shows.

This YTD price return tornado shows some promising results. I see high-cost producers like Detour in the green, but there are many similar peers that are in the red.

This chart is much more useful. It plots 2019 YTD price returns against 2018 AISC per oz. The relationship, however, is the exact opposite of what I would expect. The lower the cost the producer, in general, the better they have done this year.

Before you start challenging this chart, I will acknowledge a few caveats. First, this is the GDX peer group. The silver price has been hammered this year, and some poor performing companies (Hecla) have a large exposure to the silver metal. There are also notable idiosyncratic factors that have resulted in poor (St. Barbara Feasibility study disappointment) and better than average performance.

The underlying premise, however, that high-cost producer will outperform in a rising gold environment appears to be less certain than the underlying logic would propose.

So how should you think about this information in the context of your investment framework? To start, the data suggests that jumping into high-cost producers does not make sense at the moment. Perhaps the gold price needs to consolidate before market participants rerate these companies. The data suggest that less risky, lower cost producers, may be the first to benefit (in terms of stock price) during a bull market.

In this case, Kirkland Lake stands out as the obvious choice; being the lowest cost producer in the GDX index.

Capital Allocators

Intuitively I’ve known that the gold mining industry doesn’t allocate capital well. I’ve touched on some of the return performance of royalty companies in the past. Their low return royalty model looks angelic compared to other actors. As I browse through company balance sheets I note the scars of the past (dramatically negative retained earnings). I’ve never really looked at this information in much detail. I know Kinross made some bad bets, I know Barrick lost its track with Pascua Lama. The full magnitude of the capital destruction, however, was way worse than I thought it would be.

Take a look at this snapshot. In 2013, this group -which is by no means comprehensive- wrote off over $24B in 2013.

Over this same time period, the group destroyed $70B worth of capital. Barrick alone tallied $30B.

If we look how much was written off, compared to these company’s current enterprise value the data shows the Kinross leads the pack. Between 2005 and 2018 the company wrote off $12B, which is 50% more than the current valuation…

Interesting stuff. Terrifying really. There are, however, a handful of companies that did pretty well during this time period. All of the streamers kept write-down % under 10%. Kirkland Lake was one of the only companies that survived the period without an issue.

Nevada Net Proceeds Tax and Open Pit Optimization

“Pit Optimization” is a mysterious catch-all term used by mining engineers, financiers, and geologists. You input a bunch of economic variables into various Black-Box algorithms and with a click of a button, and 20-30 minutes, out spits a pit shell that is “optimized.” From this shell, you can tell the world how much metal is economic and then run some mine plans to figure out the economic reality for the project. My interest in digging into this topic a bit deeper was spurred by the realization that experienced industry leaders were treating the Nevada Net Proceeds Tax differently.

What is Whittle? What is Lerchs-Grossman?

Lerch-Grossman is the name of a modeling approach for solving open-pit optimization. It was developed in 1965 and implemented in the 1980’s by Jeff Whittle. The algorithm uses block dependencies to determine which blocks must be mined out as a group (i.e. if you mine G you must mine B, C, and D). The graphical relationship between blocks is determined by slope parameters (i.e. if you are using a very shallow slope than mining G may necessitate the mining of A through E).

Figure 1: Dependency Example (source: CONSTRUCTION ECONOMIC ORE BODY MODELS FOR OPEN PIT OPTIMIZATION, D. Whittle)

I like to think about optimization in a backwards fashion. Flip the topography upside down and whatever falls out is the optimized pit. Instead of gravity, you have revenue, this is the force propelling the ore out of the ground. In the opposite direction, let’s call it friction, we have costs; forces that go against the revenue generated by the ore. Like any physics equation, the fundamental forces need to be correct and well thought out.

With this explanation in mind, let’s think about a tricky situation. Below you’ll see excerpts from two technical reports. Both open-pit mines located in Nevada. One accounts for the State’s Net Proceeds Tax, one does not. So who is right here?

Well, the calculation of the net proceeds tax looks like you can deduct just about every expense that occurs during mining so the tax is more of a net profit royalty. Thinking about the flipped topo, the net proceeds tax only applies to blocks that actually generate a profit. So, as my beautiful the drawing shows, the tax applies after the blocks have “fallen out.” The tax applies to a component of the profit, so there is no way that there can be enough force to push the blocks back up. Therefore, I just can’t see why the Net Proceeds Tax would be included in the determination of the ultimate resource. Looks like Mine 2 has it right.  

Figure 2: NNPT Calc, Source: https://nevadataxpayers.org/wp-content/uploads/2016/10/minerals-tax-2007-08.pdf

In playing devil’s advocate, I wonder if the tax should be used in the determination of interim pit phases? Imagine you have two phases, one high profit, one low profit. Does this change your thinking? It still shouldn’t matter. As long as the second phase is above breakeven, it should be mined.

Ok, so for now, I think the case is closed. NNPT and NPI royalties should not be included as cost factors in open pit optimization.

Polaris North – Canarc Resources

I was thinking about investment frameworks today. I’ve never explicitly laid out my own process. If I had to I’d say the following points are the most important in my framework (mining related):

  • The project has to score well (decent grade, IRR, preferably in a good jurisdiction, tried and tested mining method, simple process). There can be complexity but the simpler the better.
  • Value has to be a concern. There’s so much uncertainty in junior investing. We need to get 3-10x payoffs on the winners to offset the inevitable losses.
  • Momentum. This one is tougher. I’m not sure where I stand on this. Revaluations happen fast.
  • Increasing base. This can mean production, resource, reserve. Not picky.
  • Preservation of ownership percentage. I get that dilution is going to occur. I’d just like to get under as many warrants and options as possible.

I was looking at some valuations today, single asset development projects.

One that jumped out at me was New Polaris. I’d not heard of Carnac resources until today. They released a technical report on New Polaris in March.

Valuation: They have an enterprise value of ~$9 million. The post-tax NPV5% is ~$210 million; works out to a EV/NPV value of less than 5%. Well this is interesting.

Now obviously production, if ever, is far out. Within the comparable peer group, however, these guys are cheap.

This is an example of the asymmetric returns that I like. What’s the worst that can happen? You lose 100%. What’s the upside here?

Now I’m not a chartist but there looks like there could be a tide change.

On the warrant and option from there’s not too much that is below the current stock price of $0.065/share.

So, this project is cheap. Has some momentum indicators and there’s not a lot of drag on the option/warrant front.

They have ~2M in cash and spent about the same last year. Not the worst cash balance out there but not the best.

Carnac has a mixed bag of miscellaneous projects. The only one that really stands out is New Polaris. ~10 g/t, historic mine, challenging infrastructure, challenging metallurgy (probably). Does not check the box as a simple project.

Overall, I think this is pretty interesting. Will watch.

One Reason Why Miners Always Disappoint

I think it’s fair to say that we’ve all grown accustomed to miners overpromising and underdelivering. Whenever a new project is coming online there is a palpable uneasiness that is detectable in analysts, management, and investors. Will the project hit the guidance throughput? Mining Rate? Recovery?

I don’t want to group all projects into the underdeliver bucket but there is certainly a large percentage that not only fail to deliver on ramp-up projections but also in ultimate capacity. The chart below shows actual vs. projected mining rates for a large project that was recently constructed. Now I get that management can be overly optimistic and ramp-ups can be challenging. You’ll notice that the year 1 tonnage is way off of the projection but, by year 2 and 3, the company has closed much of the gap. What I’m more interested in is the levelling off of production and the inability to ever achieve expectations regarding ultimate mining rates.

Management will often highlight specific variables that are performing worse than expected. Shovel downs are decreasing availability. Pioneering is impacting productivity. A large weather storm reduced operating time. These are all possibilities. What I’m interested in, however, is why production falls short of budget when all variables are as expected.

But how can this be? How can production be less than expected when all inputs are as expected? Well, I think that the companies contracted out to perform mining studies underestimate volatility’s role in determining production rates.

Let’s look at a simple example:

The capacity table shows one shovel that is paired with three trucks. You’ll notice that truck and shovel capacity is fairly balanced, both around 25K tons mined per shift. You could expand the time period to encompass a year and this is how most feasibility studies determine equipment requirements. Now they would use variable parameters for each of these factors based on the specific conditions in the mine during the period (haul distance) and planned maintenance.

Ok, nothing wrong here, right?

Wrong!

These assumptions grossly underestimate the influence randomness within each variable. Fluctuations in, say, availability have asymmetric impacts on the production of the mine. -10% one day and +10% the next does not average out to zero impact on the mine. It averages something less.

This histogram of shift-by-shift availability reflects the average that is shown in the table (77%). This histogram reflects the outcome of 730 simulations (1 year’s worth of shifts) of another probability density function that is based on actual data.

These availability values were used to calculate shift production for an entire year. The chart below shows the mine’s production as a function of shovel availability. You’ll notice that tons mined per shift increases linearly as shovel availability is increased -the mine is shovel limited-. Once availability exceeds 70%, however, the mine is limited by truck capacity.

This is the root of the issue. Mine production falls short when shovel availability is lower than average and cannot sufficiently increase production when availability is higher than average. This asymmetry makes it effectively impossible for feasibility parameters to be achieved.

Average simulated production is barely over 20K tons per shift. A far cry (-18.5%) from the 25K tons per shift that would be predicted by the study. Coincidentally, this is the same delta between actual and planned tonnage in Y5 of the earlier chart.

Mines are fragile. They are hurt by volatility and cannot make up production on the positive side because rates are capped by a new bottleneck. It’s my opinion that this static mindset, when it comes to production scheduling, is the root cause of lots of the industry’s issues.

So what do we take away from this very simplified example?

Well, it pays to have buffer (excess) capacity. Miners with small equipment fleets are the most susceptible to volatile operating parameters as they don’t have other units to average out the shift-by-shift outcomes. In general, a static approach to forecasting will overestimate long term production.

Beta and Price to NAV

So I woke up this morning thinking about gold producer price to NAV5% discounts/premiums. I’ve struggled to understand the intuition behind being priced at a premium to NAV5% as this implies that the appropriate discount rate for the stream of cash flows is less than 5%. How can this be given that gold mining is inherently risky. Arguably more so than the typical business in the S&P 500.

Well there are a couple of explanations for this pricing behavior:

  • Analyst NAV assessments underestimate the future stream of cash flows
    • This is possible but I doubt this is the answer as any future resource conversion is going to occur so far in to the future that it would be discounted to oblivion
  • Analysts use a flat price deck when creating the NAV forecasts
    • You could make the case that a nominal price deck should be used but this change would be offset by the use of a nominal discount rate; probably not the answer.
  • NAV5% is not the correct discount rate to be used for specific gold producers.
    • I think this is the underlying logic driving the price to NAV logic.

In the gold space, small companies typically trade at a discount to their NAV. Generally, discount to NAV is negatively correlated with size; smaller company, larger discount. The intuition behind this equilibrium makes sense as larger companies are more diversified (operationally and jurisdictionally). Senior producers generally trade at a premium to NAV and streaming companies trade at an even higher premium.

Being priced at a premium is a challenging concept to understand. At the extreme, this can imply that the purchase of the security will provide cash flows that are less than the purchase price. This is very similar to negative interest rates. Unlike negative interest rates, however, the pricing of these securities is not manipulated by quantitative easing and central banks. The “rational” investor is doing the pricing.

So how can a discount rate of zero (or negative) be justified. The capital asset pricing model states that the equity risk premium is the risk free rate + beta * equity risk premium. The current T-bill rate is around 1% so this implies that the beta of these investments must be zero or slightly negative. This train of thought led me to start looking into beta and the correlation of gold to the broader economy.

So what is beta? I like to think of it as a leverage factor for stock returns. A beta of 1.25 means that the stock will move 125% of the move of the general market. Beta can also be thought of as “risk” factor. A high beta implies high risk -higher volatility- and investors will require a higher rate of return for an investment in the security.

If we look at the beta of monthly returns from 1973 to the end of 2018 we see that gold has exhibited a negative beta with respect to the S&P500. Conversely, copper, oil, and silver have positive betas. These relationships make sense as these other commodities are more related to economic growth and, in turn, the S&P500.

The beta values are misleading as they understate gold’s performance relative the S&P500 during times of instability.

Because, as you’ll see in this chart, gold generally hovers around a beta of zero during periods of relative calm and spikes in other occasions (2008).

This chart that gold acts as insurance during calamity, increasing in value by more than the S&P falls.

Is Grade King? Post 2

This post is a continuation of yesterday’s dive into the relationship between company-wide grade and cash flow from operations. Spoiler alert, there was no relationship. This fact isn’t surprising given the multitude of other factors that impact a company’s cash flow from operations.

I decided to get a little more granular and look at this relationship on an asset basis.

The chart shows that increased production correlates with lower AISC, an expected result given economies of scale. Large scale project require large capex and, as such, require low operating costs to provide attractive rates of return. This makes sense. 

If we compare AISC for open pit operations vs. processed grades we see the trend that we were looking for! Increased grades results in lower AISC. Finally.

Similarly with UG operations, higher grade and lower opex.

Hope you find this interesting.