A (3:19)

Yeah, that's an excellent question because just by observing the trading profits of some of the public source information around the merchants in Geneva, they're creating a lot of value with trading activities. And, and we can observe that there are still many industrial players who are not tapping into this value pool. So what we decided to do for the paper was we ran a survey of 4 or 500 sort of C level executives and we sort of head on asked them why are you not utilizing these tools and this mindset of trading if there's so much value? And that sort of supported a lot of the, let's say, daily empirical evidence we have from our client work is that, you know, first of all there is, you know, quite a lot of misconceptions around what trading is. And the boards often associate trading purely with risk taking. The, you know, the boards often don't like the complexity that you might get from trading as well as the boards generally dislike, you know, paying traders as much as you might need to pay them to properly incentivize them. So the first reason is really around sort of misconceptions around trading. You know, what it is, what does it take to do it. And that sort of was the number one coded reason just to jump in.

B (4:52)

There saying on that one, is it, and you and I have had this discussion off air a couple of times, is it that they, there's a lack of understanding and we recognize that it's very, you know, it is very complex. Or is it also kind of that headline risk as well? It's that, you know, there's sort of see these significant losses, you know, the perception, I guess, the perception versus the reality. Did you in any way divine what was triggering that sort of, I guess, lack of board approval or engagement in it?

A (5:27)

Yeah, it is a little bit, you know, misconception in a sense that we, you know, we, we still have on the back of our heads very long events. For example, Enron is still brought up by some, some participants and, and there's just, you know, misconceptions around what trading is. And you know, if you look at the sort of trading profits versus for example upstream profits, oftentimes trading profits are even more stable than upstream. So there is just a misconception on what it is. And similarly there is also some capability gaps in the boards. They just simply don't understand what trading is and what it isn't. So we are seeing this sort of gap in terms of, you know, what, what sort of profit distribution you get, what is the level of risk you're taking, how do you control that risk and sort of how do you manage a trading business versus a traditional industrial operation.

B (6:28)

And this is despite, I guess there is agreement on the uplift to EBITDA that can be created by this. Right. It's not necessarily a question of what it could contribute, it's more one of the perceived risks and other challenges.

A (6:43)

That's right. So we also asked the question head on, sort of how much do you think there is uplift in your particular business from trading and commercial optimization? And the sort of middle of the line answer was between 2 and 3 percentage points of EBITDA or return on assets in more the financial services. And that's a very big uplift for many, especially conversion businesses. So it's not a question about sort of is there value? I think most actually would agree there is and some are even willing to go for it, but they just simply don't have the permission to go. So that's one of the sort of motivations for my research as well, is to bring to light a little bit what, what these activities are, what they are not, and how much there could be value and hopefully, you know, educate the industry a little bit, you know how to look at this in a correct way.

B (7:42)

Yeah. Okay. So going back to that survey of C suite executives, so first there was this lack of board approval and that denotes a skills gap to a degree within the boards themselves, which we'll come on to. What were the other sort of top 10 two or the. The other two of the top three.

A (7:59)

Yeah. So there are also quite a fair number of people who don't believe there is, you know, enough trading opportunities in the market or that the trading opportunities are too rare. And this was quite interesting because, you know, in similar industries, some people saw very frequently opportunities versus some saw very infrequently opportunities. So that might hint to some people more looking for those opportunities and some people less actively looking for them. And obviously in industries like energy and banking, you see more of those across the line versus in less obvious industries like real estate, you see more of a spread between the respondents. But that came as number two is that the trading opportunities are too rare to justify keeping a trading team in house. And that's an interesting finding on its own that might be True in some cases, but I would argue that quite often that's a misconception as well. There are much more trading opportunities than most people think.

B (9:10)

And I realize we probably should have done this right at the outset, but did you come to a common definition of what you meant by trading?

A (9:17)

We did actually. We gave plenty of examples on what it could be and, and what it isn't described. We, we sort of formed it during, in a couple of ways. We, we sort of started with the time frame definition. So we, we split sort of short, medium and long term. We said that sort of trading is usually focused on short to medium term optimization. Definition of short to medium term, you know, depends a little bit by industry but you know, classically, you know, it is anything up to let's say two to three years forward. So that sort of forward optimization horizon is what we're, what we're talking about and it is about sort of, you know, in and out type of position. So you know, hedging is, is not a trading activity in our, in our language. But if you are optimizing your, your commercial, commercial position that that would be considered trading.

B (10:16)

Yeah, and, and I know the paper talks about that, you know, and this is kind of the Craig Perrong, you know, commodity trading in transforming commodities in time form.

A (10:26)

That's right.

B (10:26)

And geographies and, and you talk about that complexity arising from geography, product qualities which is form and also obviously time. So you know, in its basics and we'll, I guess when we talk about other sectors we can get into some sharper definitions but this is, you know, your, your Baux site might be more, more in one region than another and do you have the capacity to, to, to, to move it there or do you have the capacity to sell locally and buy over the, you know, to do those, you know, to do the third party trading bits as well, etc.

A (10:57)

That's right.

B (10:58)

Okay, so, and the final, so C suite saying lack of board approval, the opportunities are too infrequent, which is interesting as you say. That's again, it might be down to this perception rather than reality. How are you trying to discover those opportunities? And you know, it's also to say that when we're going to move on to chips as an example, when those opportunities do come along, you know, after 10 years of steady state, they can be absolutely either enormous to capture or incredibly deleterious not to.

A (11:28)

Absolutely.

B (11:29)

And then the final one is that sort of lack of talent. Can you talk a bit about that? That's obviously key to HC Group as.

A (11:36)

Well, yeah, it is. The third indeed is lack of talent. And that sort of coincides with point number two, to be honest, because, you know, a lot of the executives that we've interviewed said that, you know, yes, we have periods when we would really benefit from having trading capabilities but we see that periodic need coming every few years. So we don't want to have a, or we cannot even incentivize to have, you know, in house trading team for, you know, to use them only after a couple of years. So there is a sort of balance of, you know, how often do you need that capability and should you have it in house for only those infrequent periods? Our perspective is that, you know, there are more frequent, you know, optimization opportunities. But of course, you know, you might have certain periods when you make more than, more than, you know, more than the others. So those are a little bit linked. But it is true that, you know, the talent is quite rare. You know, there are not many companies that are systematically, you know, building that capability and you know, it's an incredibly sought after talent. So industrial companies are struggling to find those people and hire those people. And sometimes it comes down to location, sometimes it comes down to incentives, sometimes it comes down to culture. But that seems to be one of the common trouble that especially industrial companies are having. It's difficult to recruit and, and, and retain these sort of people.

B (13:23)

Yeah, yeah. I could do an entire thesis on just beyond outside of actual financial incentive, you know, what, how organizations can, you know, have successfully attracted these people or not.

A (13:33)

Right.

B (13:33)

The backdrop to that of course is that this sector is cyclical by nature in terms of those opportunities and these are very expensive teams to maintain. And this is kind of a bit of the point of the paper as well. Right. Whilst you know, there is a perception that there could be more opportunity out there, they actually, you know, was set up to capture it and look for it. Generally speaking, these are expensive to set up. They can typically in, in very sort of normal boring years, for want of a better term, be, be costly to maintain. And it's in those, in sort of those non linear events you mentioned in the paper, they, they can make themselves valuable times 30 and even save the company and so forth. We saw that in Covid. But part of that challenge there is as a rare trader and all we should say it's not just trading, it's the risk management teams that sit around them, it's the finance teams that sit around them, it's the legal and compliance teams. Each of those skill sets is rare. The technology teams now increasingly they want to go to places that see trading as strategic and core and are still going to be doing it in 10 years. And many have had periods of their career where they've joined an organization that subsequently got out of it because of a perceived lack of opportunity. Right. So you know, that's right. It's a challenge. We don't have time to focus there other than to say you should definitely use HC Group if you're thinking about building one of these teams. We have plenty of experience in IT and plug over the two. It is about barriers to entry though, and the big barriers to entry that you highlight in the paper and your respondents do, you know, in a draw out too. I think it's, it comes down to this bucket of talent and, and the incentive structures around that. And I think there is a bit of mis. I don't think necessarily, I think the potential for compensation can be high, but it isn't all about compensation and we do plenty of compensation studies via talent intelligence, you know, where structure perhaps matters more than just quantum. And there's, there's ways, ways and means of doing that. And you also need to understand that this is going to sit differently to your, your other divisions or however you structure it. That, yeah, you're, you do. These people are going to be paid higher. Right. Your, your accountant in trading is paid 30 to 40% more than your accountant in normal business operations. And that's, that's a tough nut to crack. The other one is specialized systems. Can you just talk to that a little bit? Sort of the, the expense of setting up a ctrm, you know, that again, as you say, may or may not make you money by having it in place for a number of years.

A (16:10)

Yeah, it is true and it's growing in importance actually because, you know, if you look at trading business, you are churning, you know, power is an extreme example, right. You might have a million trades, you know, every few months. The sort of volume of transactions is just completely different from say a traditional manufacturing business where you might be selling two years forward all your production volume to a single client. So the sort of amount of reactivity, amount of precision, amount of sort of pure processing power from an IT system is just very different from a traditional industrial landscape. And that's a unique task. Type of talent you need as well is the tech talent to keep that system running and responding very quickly to changing market needs. If you need to add a product, if you need to add a sort of feature in your product, your IT team needs to work at a very different clock speed from your sort of, let's say corporate IT that's more handling the sort of ERP type of landscape. So it is a very specialized IT setup, a very specialized team of tech people. And what's interesting this year more in our sort of client work is that we're seeing more and more need for increased efficiency, increased automation, increased sort of preciseness and increased level of utilizing all the optionality in the physical and financial value chains because the margins have been a little bit more pressured this year. So the relevance of technology is increasing this year quite a fair bit.

B (18:03)

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A (18:08)

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B (18:14)

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A (18:19)

Experts with to investment and infrastructure funds, law firms and corporates. Enco Insights leverages HC Group's 20 years.

B (18:29)

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A (18:31)

Give clients the expertise they need when the stakes are high and insight matters. Learn more@encoinsights.com yeah, if you think about.

B (18:41)

We think about technology, there's the cost saving element to it, that automation that ultimately replacing people and the sort of capturing opportunity element to it. Well both those factors grew over the last four years as trading results are great. The last year and a half they've been more challenging. So there's definitely that swing towards can we reap the benefits of all this investment in technology to minimize costs. It seems to me that you can plot sort of talking about that barriers to entry more broadly. Those barriers to entry change in as more and more that dark value in a sector is captured.

A (19:19)

Right.

B (19:19)

And correct me if I'm wrong on this, but it would seem to me that you take the AGS market, it's dominated by a small number of incumbents. Same with physical oil trading. Frankly you need massive system, there's massive systems, massive footprints of assets. These are very transparent markets. They're you know, in case of ags all on exchanges, you know the, the barriers to entry against the incumbents there is incredibly difficult. Right. And even those, those AGS trading houses, they don't really expect to make great results in normal years but they're there for those non linear years as you point out. And, and you can kind of plot that barrier to entry just staying within the energy and commodity sector. Down to you talk about in the paper like in power. Some of those is where we've had, we saw a slew of FTR financial transmission rights traders come in at a decade ago now we're seeing traders come in around best. It seems there that there's these lower barriers to entry and we are seeing new entrants come in and it's a way into the sector.

A (20:18)

Yeah, that's right. I mean it's physical oil trading is, is extremely difficult to get into. You you know the, the ticket to enter the game is, is, is very expensive. So, so there is sort of natural protection of the, of the industry. But you know, so, so that sort of in contrast to power where you don't have such a big ticket to enter, especially now with renewable power, we're seeing a lot of sort of leasing of the positions in batteries and renewables and that sort of opened the door for more startup like traders to come in and start trading those positions and optimizing and to be honest, starting with the blank sheet of paper on how do you run a trading business with more technology led approach. So some of these companies could be characterized more by tech companies than traders. They just utilize the sort of tech platform to trade very efficiently. And that's a very different way of approaching trading than classical sort of getting big assets, few star traders and start taking positions. These guys are more optimizers and sort of very efficient. You know, tech players that are, that are sort of playing in that sort of physical power game in Europe but increasingly in the U.S. as well.

B (21:43)

In the U.S. yeah, I was going to say, you know, Hyperion, our sister firm is doing a lot of work with those organizations on both sides.

A (21:49)

That's right.

B (21:51)

You know that technology comment there as well. There is a certain amount of, if you are a large chemicals company, refiner, whatever it might be, that's, you know, the pressure is now very loud and the board are now or the activist investor is pushing you to get into trading to capture this dark value or at least, you know, manage those downside risks. There is some sense with the new technology suite available that you can take a different approach. You don't need those banks of star traders. You can focus first on better understanding, capturing the information that you, you are generating through your assets and going down that kind of technology optimization route initially than necessarily having to, you know, have the kind of the. Yeah, like I said, the trading floor and whoops and yells and so forth.

A (22:43)

Yeah, no, that's sort of one of the sort of arguments that we're starting to sort of form up from other research is, you know, even if you don't want to be a big trader, at least sort of look at your own supply chain and make sure that you're capturing all of the information in the chain and, and, and feeding that to your commercial teams and feeding that to your procurement teams and, and, and your operations. So you're at least sort of capturing all the, all the information you have and go after all the arbitrage out there in the market. You don't necessarily need to have a big trading team and go full blast. But that opens up a lot of value that's, you know, I would say almost risk free because you're just sort of utilizing a lot of the optionality you already have in your supply chain and a lot of the information you have. So that's something I would recommend to any industrial player to really assess because a lot of them come with a lot of proprietary information, a lot of flexibility in their, in their operations that they're just not using today, which is.

B (23:49)

Now much more discoverable. Right. You can just set a set of a bot off to crawl through data, you know, and I do think that's massively unlocking. And we ourselves and we've had, you know, various leaders on the podcast. I mean, Daryl Schofield, you know, spoke about this four years ago in a refining episode. We did. Right. I think there's lots of opportunity. Doug hall talks about this, you know, that is just emergent at the moment and, and I think could be transformative to those, you know, barriers to entry. Eventually your moat will silt up if you don't keep ahead of the game. But anyway, right. I want to get to part three of the conversation about how we, you know, trading can come to real estate and pharmaceuticals and all those other sectors because I find that fascinating. But let's just talk about the current environment for energy trading. The incumbents, the last, you know, this case, we were having this podcast a year and a half ago. You know, the case you've made is very strong and you can just see how those organizations have weathered Covid Russia's invasion of Ukraine that had trading capabilities. Right. They're still around for the, you know, and, and they have made extraordinary profits, albeit with some liquidity crises thrown in the, you know, the last year and a half, you know, we've. The world has surprisingly, given all the events that's happened as well, somewhat normalized in terms of volatility. You know, markets do what markets do and become more efficient. Can you, you know, how, how is. How what's gone on in the last year or so and how has that reinforced or changed the thesis above?

A (25:25)

Yeah, it's been an, it's been an interesting, interesting period the last year. I would say it's a little bit of a hangover after a couple of crazy years coming down from a very, very high level of profitability in the trading business to, let's say, more normal years. I would say we've also seen that there was a big shift of hedge funds coming into the commodity space pretty big time in, in 23 and 24. We saw some, you know, blood on the floor actually this year with, with some positions being, you know, getting pretty sour. So let's see what, what's left after end of, end of this year. But, you know, it's clear that, you know, we're heading into, at least so far, seem to be heading into more, more sort of stable, let's say normal, you know, long cycle year. Which means that, you know, we are back to some of the, let's say more typical topics around this industry, which is sort of, you know, where do you find efficiency, where do you find, you know, further value in our, in our supply chains? Uncover new flexibilities, new optionalities. And you know, quite frankly, you know, people were looking less interested in efficiency and automation. Now that's back on the table and that's sort of normal as part of this cycle. And I think there is, let's say, a growing gap now between the players who've modernized themselves over the last couple of years versus the ones who haven't. And we run a benchmark on, let's say, the tech maturity of commodities traders. And we're seeing that sort of spread widening over the last few years. And it's going to be interesting to see how those, let's say more and more modern, more efficient players are going to fare in the next few years, given that we'll likely see more pressure on the margins.

B (27:32)

That's fascinating. Let's talk about that tech gap. Is that comparing apples for apples? Right. So physical traders, merchants or the trading arms of Apple, an oil major. And, and you see a gap there where they, they are more or less advanced, technologically speaking. And can you define what you mean by technology and then what that the results that gap drives?

A (27:53)

Sure. So, so yes, we've tried to sort of normalize, you know, the technology definition. And, and we're mostly looking at sort of physical traders that often do have a big, big financial trading, you know, business as well. But we're sort of looking at the overall landscape. How do you sort of draw data, how do you manage data, how do you sort of capture trades, how automated is your trade life cycle what sort of tooling do you build on top of your systems? How do you manage risk? Do you have a global value at risk system? Do you have sort of real time position management? So there is sort of very, let's say defined set of questions and definitions that we have and we give you a scoring between one and four for each of those areas and then we sort of give an overall score where you are. And what you're seeing is that, you know, some of the very, you know, forward looking LNG players, for example, are approaching what we call a level 2 advancement which is already very, very advanced. You have good grasp of your data. You have holistic optimization models on the short term as well as the medium term. You have very solid data foundation on your contracts. You're able to squeeze all the optionality. So we're seeing especially some of the LNG players pushing very far from some of the less advanced ones. Power and gas is very advanced as it has been for some years in Europe and oil is somewhat behind the rest.

B (29:41)

Yeah, I mean, okay, so you could argue that LNG is sort of, much more sort of fertile ground to be technologized for want of better term again. But you know, in the fact that you've kind of got a lot of no, you know, known quantities, known variables and port depth, ship availability, all this stuff and you can feed it all into a big algo and will kind of make sense and just in the nature of how that market operates at least more so than kind of the crazy world of I don't know, diesel or, you know, or much more complex systems.

A (30:17)

Yeah, that's right. I mean it's in lng, you know, it's, it's basically coming to a level where if you don't have these sort of tooling, you are, you're being left behind. And we are seeing some of the players not reacting, you know, fast enough and they're now, now sort of trying to scramble to get there. And so lng, very obvious one I think in oil we are seeing quite a lot of development as well. It's a lot more complex, but we're seeing tooling being made on, on product trading, on blending arbitrage, on, on, on refinery optimization. We're taking more, more sort of real time views on risk. Overall we are seeing advancement. So, so oil is more complex. It is, it is a little bit behind, but we're seeing quite a, quite a fair bit of movement actually with the more advanced players as well.

B (31:12)

Yeah, I know. You know, and going back to our earlier comments, on talent and cost. Right. I mean, a, a good CIO as an information officer, you know, are very valuable players at the moment. Right. And you know, some of them are beginning checks akin to what you would expect for a head of trading to secure them. Because these are the people have the leadership capability to actually make, you know, start these transformations. And we've, we've talked about this on the podcast a few times. But you know, these are three to five year transformations at the very least. Right. I mean, these are complex to do, but just so, so that's fascinating. What about the hedge funds where, you know, the sort of the, the thesis here is of course, that they are light years ahead in terms of technology and the ability to scrape and capture and transform and all this information, you know, by and large, or you know, a certain suite of them have had a really tough time. You know, some have been obviously done very well. I would argue that typically those that are sort of had a long tenure in commodities and have leaders who are very familiar with commodities, but it seems that, yeah, that they've had a tougher time.

A (32:22)

That's right. And, and majority of the hedge funds are, you know, only in the, in the financial part of the, of the commodities. Right. So, so they are more doing this sort of macro type of trading either as part of their overall asset portfolio or then they are trying to figure out, let's say, the supply demand of commodities and take positions in commodities. And in 22 to 24, we sort of had a world where you could do a lot of that and take quite weighted positions on the supply demand. This year you could argue that it's been a bit, you know, less good volatility, partly driven by, you know, politics. And we've seen some hedge funds have sort of fundamentally correct positions, but being, being sort of squeezed out because of, of, of the events we had, especially in the spring. So it is a different environment and, and the risk taking has been a lot more difficult this year. And that's the reason why some of the hedge funds are suffering in commodities. But then on the other hand, you have the players who are more in the physical game who are actually still faring very well. And that's one of the trends we are seeing, is that a lot of the value is in understanding the physical and translating that into the paper. And that's what more and more of the hedge funds are trying to do. Hello, I'm David Hunt, founder and managing director at Hyperion Search. Founded over a decade ago, Hyperion Search has helped organizations from major Utilities to startups recruit their leadership teams and key individual contributors to accelerate both their growth and the energy transition. Our three main verticals are renewable power, energy storage and E mobility. The energy transition and the talent that delivers it has been our passion since day one. To find out more, visit hyperionsearch.com or listen to my Leaders in Clean Tech podcast available on all platforms.

B (34:32)

Yes. Yeah, we've seen hedge funds get into the physical buy physical assets. That's in power, gas, oil. You know again that brings with it another level of capital commitment and tackling those barriers to entry. Can you, I guess just going back to that comment about obviously just for the context of listeners, you know, how big do you guys think the sort of the pressure on margins has been this last year and 20, 20, 24 and 25 compared to previous years. Can you give us some quantum around that? And, and how significant do you see that the pressure on cost going forwards or this could all, you know, because the backdrop to this is always, you know, commodities has three good years in 10. So are we in for a sort of seven tough years or actually is there a view that. Well, so I'm compounding my questions but firstly how significant is the cost pressure? And then secondly, is there still a sense out there that actually we're in a bit of a different phase of the global order and volatility is likely. Those opportunities, those non linear opportunities are likely to come more swiftly, more frequently and of greater magnitude over the next decade. We're not in business as normal.

A (35:43)

Yeah, I think, I think. Well, one could argue that, you know there is, and this is something worth another debate but, but you know, what is the sort of worth of you know, trying to forecast the future versus you know, preparing for volatility? And we had big debate about this internally as well in one of our summits and, and, and because you know it's, it's becoming extremely difficult to give any sort of view on where the world is heading in the next 10 years. So the best you can do is prepare to be flexible and provide that sort of cushioning and that sort of cushioning has been what's created the trading profits in the last years. Now one could argue that we have more or less cushioning needs in the coming years. You know, geopolitically anything could happen. And you know, like the war in Ukraine, you know, we were doing a, a study on, on gas flows the same week when the, when the war started and everything went belly up and we had to re, re study the whole thing. Right. So you never know. But what seems to be happening is we have, you know, stabilization of the margins to a more normal level. I would expect us to reach sort of 20, 20, 21 type of levels. And you know, we had a lot of buildup of trading capability in the last few years, for example, in the Middle East. So you know, we could argue that the same pie is being distributed to more players, which means that, you know, the cost pressure is higher than it was before. And that's sort of what we're hearing now in the market is there is a lot more interest on, on automation, on squeezing of value better from the assets. So I would expect to see more pressure in the coming years than we've had before.

B (37:42)

We are seeing as a search firm a focus on. There is definitely sort of a more. It's not sort of the wild abandoned years of a couple of years ago, to be honest with you. For the most part we support physical organizations building and strengthening trading capabilities and that that trend has not stopped. I think the narrative here of the need for this is still there and is growing. I think it's probably some of the froth is out of the market, particularly from some of the hedge funds that have come in which you know, has had a knock on impact on compensation. You know, I think for the. To answer the second question, if I had to bet, I think that we are probably not in a normal period where we can, we'll expect five years of low volatility. I think it might be true in certain commodities. But one of the things that seems to be changing is the pendulum is swinging back from a sort of laissez faire free markets world to one of increasing government intervention. And so the actual ability of markets to respond I think is going to be degraded which in turn is going to cause I think sort of that non linear events and volatility to stick around, albeit maybe not at quite the crazy pace it has been the last five years.

A (38:59)

Yeah, no, that's definitely true. And one thing we tracked in the survey as well and now we are doing further research on different sort of sectors and the sort of role of regulation is one that sort of keeps increasing the more we look into different industries and that's creating a lot of uncertainty, but also also a lot of opportunities. So I would tend to agree that probably the sort of level of margins is going to stabilize higher than it was some time ago, but probably not at the crazy levels. We had 22, 23 and partially in 24.

B (39:37)

And as you say, right. I mean all of These markets started with deregulation and we'll see sort of where regulation takes us particularly I think in places like Europe, where there's a, there's a fair few eyeballs on kind of the profitability of some of these energy companies versus sort of people's bills as they, as they come into their households. Okay, let's, let's move on to I guess the, where this thesis of having the capacity to trade a product rather than just it go through your, you know, you buy it and it goes through your own proprietary supply chain. In your paper you have a dark value potential matrix by sector, by industry. And again, I'll put links in the show notes and people can go look at it. But you know, sort of the, on the right hand side of this matrix you've got high potential of capturing dark value through, through risk management. And above the line are, you know, energy and utilities and so forth. Below that is a number of interesting sectors like travel and real estate and transportation, capital goods. Can you give us some sense of how you created this matrix, what you consider dark value to be? And then let's dig into some examples.

A (40:53)

Yeah, so you know, the dark value is sort of difficult to quantify by design because it is sort of value that we can't directly observe. And that's sort of the, the sort of, why we named it dark value is that sort of like dark energy and dark matter in physics you can sort of try to observe the effects but you can't directly see it. That's sort of the inefficiency of not optimizing and not trading actively in these markets. So what we did was a couple of things. We straight on asked in the survey from the participants, how much do you believe there is, you know, value on the table? And we did a sort of macroeconomic analysis where we sort of found six drivers of dark value. And those are linked to sort of the complexity of the industry and the fragility of the industry. And the thesis is that if you are very complex, either geographically quality wise or sort of storability wise, and if you are an industry that are difficult to reconfigure fast and there is very few buffers, you are more prone to have a lot of dark value because a shock, for instance, affects you more because you are fragile and you are complex. Whereas if you are simple and very sort of sturdy industry, you should have less dark value. And we found sort of, you know, good, good estimate estimators for, for those, for those drivers and we, we sort of quantified and compared against both the, the survey results as well as, as our known sort of trading profits per certain industries and were able to calibrate that. So, so it was a mix of, of of a few calibrations and but we're fairly happy with. You can read more of the methodology in the paper itself. And then on the sort of capture rate we made a measure of sort of maturity of the industry. So how many traders there are in the industry, how much ecosystem there is around trading, how transparent are the prices are there for example PRAs active in the market. So try to gauge and then then sort of calibrate again with our non trading results for example in energy. So it was a lot of calibration back and forth. But we are fairly happy with the results. I think now looking, you know more in certain of the sectors, I think we were probably even underestimating the value because the inefficiencies are very big in some of these. But that was sort of roughly how we did it. It was a combination of macro analysis and the survey results calibrated with non trading results.

B (43:53)

We spoke off air about obviously the chips example and actually that you know lots of the sort of the crisis we saw in Covid where an $80,000 car, $100,000 car couldn't get built because it was missing a 10 cent chip. And but the, the chip itself had been sort of customized but not really. And actually they, they were very fungible and could have been traded. So that's one example. But I guess can we lean in on well, chemicals and real estate. Perhaps you can give us some examples there about what the, how much you think that DART value is there and kind of what that industry could look like if they started trading.

A (44:30)

Yeah, it's, I mean chemicals is a good example because it's sort of in the fringe of a classical sort of commodity and more of a specialist product. And what we're seeing is the industry is actually struggling at the moment with profitability so they're looking for new streams of value and thus the whole trading and optimization becomes a very big topic. And we're seeing that in our client work. It's more about sort of understanding the value of your product, understanding the alternatives, you know, of your customer. And it is about creating sort of liquidity for your products either through sort of brokerage or through auction mechanisms or through open markets. So it's about sort of creating, you know, liquid open markets for these products. Sometimes it means even standardization more so foregoing some of the premium you might have. But in return, getting much more flexibility in terms of placing your products in the market. And that's true for chemicals, but true for semiconductors, for example, as well. So you might be foregoing some of the sort of classical premiums, but you might be gaining a lot more from the sort of trading and optionality management of your supply chain and product mix.

B (46:06)

So this is, this is rather than sort of putting a brand name on your pretty generic chemical and you know, and your customer trusting that they'll pay a bit more because they trust in its quality or whatever it might be, you forgo that. But then suddenly you can buy and sell third party chemicals of the same, you know, exactly like you would a barrel of oil. Right. You know, and this whole system becomes more robust and you're capturing more value even while you're giving up your sort of brand, sort of registered trademark name.

A (46:38)

That's right, that's right. And that's a tricky discussion. Like, I think one of my favorite examples is where these two worlds clash is coffee. Because green coffee is almost like a commodity, right? You have commodity futures on two grades of coffee, but it's a consumer branded product. So you might have immense margins on the consumer side and then you have a couple of percentage trading margin on the commodity side. So how do you balance the two? And that's one of the tricky questions in some of these industries. But in chemicals it's getting easier because the industry sort of profit margins are very, very low. So all of a sudden that sort of 3, 4, 5% trading margin becomes extremely interesting as an upside.

B (47:30)

Yeah, yeah. And we've definitely, definitely seen that. What about real estate?

A (47:33)

Real estate, that's an interesting one. We're now doing a deep dive on real estate, looking at it from a sort of, with trader's eyes. And one of the first analysis we did was we looked at like, what is the transaction cost of a real estate deal versus a transaction cost of a physical oil transaction or a government bond transaction? And we looked at sort of real estate deals across the world and the finding was that even in the most efficient markets, we are somewhere in the range of 5 to 8% of, you know, cost to transact. And if you compare that to a, you know, buying of a government bond or, or, or cryptocurrency, which are fractions of a percent, it's a very, very inefficient market. And, and we've seen transaction costs of up to 15, 20% of the deal in certain parts of the world. So that leads into a market that's you know, mostly a long term market. So your, your holding periods are fairly long. There is often very little short term liquidity. And what that means is in terms of sort of economic turmoil, we see prices, you know, very quickly, you know, declining very, very, you know, substantially. And because there isn't a lot of short term capital around, it's, it's sometimes know, difficult to even find anyone to buy distressed assets. And, and that creates a lot of inefficiency and short term volatility. And this is one of the reasons why we're seeing, you know, private equity now getting more interested in real estate. We are also seeing private credit, you know, funding coming into the industry because we've been lacking this sort of short term optimization. And that's from a trader's perspective, very interesting balance to start thinking about and trading around. And another example is that there isn't a proper forward curve for real estate. So doing a valuation of a, let's say 10 year lease is extremely difficult. You have to make a lot of assumptions on, you know, interest rates, on quality of the tenant, on the cash flow projection, on sort of inflation, on the costs. So it is an extremely difficult market to price and the data is very scarce. So by sort of professionally managing your data inputs, having good valuation models, having good risk models, timing your sort of entries and exits in the market and having a little bit of dry powder in capital seems to be quite an interesting play.

B (50:40)

Yeah, talk to those people who bought houses in 2009. The other one, just a couple of pieces left. Obviously we've covered rare earths on this podcast multiple times. There's guys like Benchmark that are set PRA and you know, trying to provide that price signaling to the market so they can be traded. There's also powerful incumbents that and an IP sophistication there that makes some of this, the processing challenging. One of the other things I liked picked out was the sort of cloud compute as a commodity and you know, and the opportunities there. Can you talk a little bit about that?

A (51:18)

Yeah. Cloud computing is an interesting one. We obviously have a massive buildup of data center capacity around the world. And two interesting aspects to that is, you know, one is it sort of is the capacity used where the sort of opportunity cost is the highest meaning, you know, is the capacity always used according to the highest need. And the other interesting aspect is the sort of use of computing capacity where power prices are the lowest. And this means sort of, you know, should you optimize a little bit how you utilize your capacity based on the power price of the day and both of these sort of aspects are not yet fully there, partly because we are, you know, running the capacity at very high rate. And, and, and oftentimes the data center power purchases are made on a, on a sort of very fixed power price. But if we have a buildup of capacity now coming up and we are seeing, you know, at some point, you know, periods of over capacity that could trigger a market mechanism to trade around, you know, around the capacity and then the factors will be, you know, who's willing to pay most for the capacity and where the power price is the, is the lowest. And that sort of optimization could take place and provide, you know, quite interesting opportunities for traders to come in and arbitrage between countries based on power price and sort of customer demand based on the level of, you know, purchase power they have on the capacity. So that's an interesting one. That's more of a thought experiment for now, but we probably will see some of this playing out in the next years.

B (53:13)

Well, you know, the paper also knows, just coming full circle back to talent, of course, that, you know, in some ways the, the, the commodity traders of today, you know, could find and you know, and actually we've seen this, right. They, they, they, a great trader in their personal lives is also trading things like real estate and all other manner of things where they see inefficiencies. Right. Sort of the training is, is, is, is deep. But you know, this does provide a, the talent sink for this kind of mindset sits within energy and commodities today. And it is precisely that talent sink that the other sectors are going to have to lean on to build these capabilities.

A (53:53)

Absolutely. I think that's the way it is. It is in energy, commodities to a degree in hedge funds, but more on the sort of financial side. And we are seeing very few companies actually having proper training programs for graduates in commodities trading. So it is a rare pool of talent and thus sort of, you know, it will be a pretty tough fight for the top guys.

B (54:22)

Yeah, yeah. And in fact, to that point, our Talent Intelligence group has been actually sporting organizations this year and actually standing up graduate training programs because, you know, it's just vital for, for sustainability of your platform, you know. And one of the challenges, of course, is how do you attract the best and the brightest grads and get them trained up in a world where, you know, people don't want to join the energy and commodities sector. Right. Because there's very little knowledge about the opportunities within it. But also this perception of, you know, it's not as environmentally sound as going to a technology company, which I would argue is. Is otherwise. But anyway, well, anti. It's been a real joy having you on. I'll put links to the show notes. Links to the paper, sorry, in the show notes so people can read it at their leisure. It's a great read and, you know, hopefully we can have you back on again in a year or so and, and see where the research has taken you.

A (55:15)

Absolutely. Thanks a lot for having me.

B (55:23)

Thank you for listening. To find out more about HC Group, our global offices and our expertise in search within the commodities sector, please visit www.hcgroup.