Foreign. And this is where the matching happens basically because when we take this new data put into our database, it finds a match that is as close to something it has seen before. And as this is historic traits, we do know the outcome of these particular trades. C1, C2 so this actually gives us like an indicator on when we have seen these patterns before. What happened to this particular trade. Imagine spending an hour with the world's greatest traders.
Imagine learning from their experiences, their successes and their failures. Imagine no more welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world so you can take your manager due diligence or investment career to the next level.
Before we begin today's conversation, remember to keep two things in all the discussion we'll have about investment performance is about the past and past performance does not guarantee or even infer anything about future performance. Also understand that there's a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their product before you make investment decisions.
Here's your host, veteran hedge fund manager Niels Kostrup Larson. Welcome to another episode in the Open Interest series on Top Traders Unplugged, hosted by Moritz Seibert. In life as well as in trading, maintaining a spirit of curiosity and open mindedness is key and this is precisely what the Open Interest series is all about.
Join Moritz as he engages in candid conversations with seasoned professionals from around the globe to uncover their insights, successes and failures, offering you a unique perspective on the investment landscape. So with no further ado, please enjoy the conversation. Hello and welcome to episode number 15 of the Open Interest series on Top Traders Unplugged. My name is Murit Siebert.
You know I love finding these specialist niche systematic trading funds and today I'll be speaking with Kalkulo Capital, a short term quantitative commodities hedge fund based in Copenhagen. Calculo was founded by Philip Engel Carlson in 2018 after he sold a power trading company, which he founded in 2008 to a competitive firm. Prior to getting involved in the European power markets, Philipp worked for Saxo Bank's commodities desk as their Global Product Manager for futures and options.
Joining Philip is his colleague Ola Hansen, who has been a member of Kalkulo's board of directors since 2022. Ole works for Saxo bank in Copenhagen and I reckon some of you will already be familiar with him through the widely published Saxo Weekly Commodity Update, which covers the most important developments in the global Commodity markets as well as through Ole's appearances on other podcasts. You know, I wanted to get Kalkulo on the Open Interest podcast for several reasons.
One, there aren't that many hedge funds around in Denmark to begin with, at least not to my knowledge. Second, because they are a systematic cta which instead of trading a broad set of markets, concentrates on commodities only. Third, because they are short term with holding periods of one to ten days per trade. And lastly, because they use machine learning techniques to generate trading signals to enter and exit their trades.
So with that as background, I think we'll have more than enough to speak about. So let me get started by saying hello to Filip and Ola. Welcome to both of you. It's great to have you here. Thank you very much for having us. Thank you. You're more than welcome. Ola, let's start with you. You have this detailed view and this detailed lens into the commodity markets. And I always like hearing your analysis and outlook for the major markets.
Can you give us a brief summary of how commodities have performed here today and everything that's been catching your eyes? Oh yeah, absolutely. And first of all, it is most certainly a very interesting times across markets, most certainly also in commodities. And we've seen that now for, for the past couple of years where the, where the interest has, has.
We've seen rising interest among our clients in Saxo bank and, and because simply basically there's, there's, there's a lot of different movements going on and what we saw last year was really quite a diversified market where we had some, some outliers, we had some like cocoa really jumping extremely to the extreme. And then at the other end we had some natural gas slumping in in the US So far this year we really off to a very strong start.
The, we're seeing all sectors footing in some, some pretty strong gains here. Well, they are very strong considering we only watch six, seven weeks into the, into the new year. I watch something like the Bloomberg Commodity Index which, which is broadly exposed to agricultural commodity, metals and energy and it's up nearly 10%. And that's most certainly a better result than what has been achieved in, in the stock market so far this, this year. And if I should pick out some, some themes.
Well there are, there, there are many and one, one occurring theme is, is, is obviously what, what, how the market addresses what's currently happening in the US where we, where we really have some significant changing signals coming from the new administration. The market is, is trying to deal with this as Le at one point said there are decades where nothing happens.
And in the weeks where decades happen and it almost feels like the last few weeks has been in something like that because there really is a lot going on. But I think we all watch the precious metals market where we are seeing very strong gains not only last year, but also this year in precious metals. And precious metals is why should you buy something? What I think Mr. Buffett called it a dead asset.
It doesn't yield anything, it doesn't give you any interest, no coupon, it costs money to store and you're constantly worried someone's going to come and steal it from you. But nevertheless, we've seen strong demand for precious metals and that really is just an expression of a world that is not in balance. We have an uncertain world and that's on several fronts. And that is the reason why we're seeing investors moving into precious metals.
Not only central banks who have been buying for the past three years in order to diversify their holdings away from US dollar based assets, but also private individuals worry about what's seeing, what they're seeing in the world right now. And not only the geopolitical risk, but also I think the fiscal debt worries. That basically comes with the rising debt burdens we're seeing around the world.
And not only, well, I'll say almost, not least in the US right now, but I think we have a long term bullish outlook for commodities. And there are several key themes that I think will drive this. We're seeing the deglobalization where production is being moved closer to home. That unlikely. That will require quite a lot of commodities. It will also potentially drive up prices for some.
We have the increased spending on defense coming through in Europe now in a big way that will require quite a lot of of anything from steel to rare earth minerals to the more technical side of things. We have the whole decarbonization which is ongoing. Even though perhaps Trump is trying to put a span in the works. Then the outlook for future demand towards clean energy is ongoing.
And maybe we just call it the energy transition because the energy transition is also a question of we're moving towards increased use of power. And it's not only towards electrical vehicles, it's also towards data centers, it's towards cooling in countries where climate change means higher temperatures. And that leads back to metals that will support that process. Copper and aluminum obviously springs to mind. Lithium, cobalt and nickel are also there and we see even sea silver.
And then the de dollarization I mentioned with central banks moving away from from the, from the dollar that's supporting gold. We have the disc fiscal and debt stability risks. And then finally we've got demographics. We are basically an aging population in large parts of the world where with a lot of money but also increasing the pressure on the younger generation to look after us.
But also the, the money that we have saved in over decades that's that will be spent and that's also adding to, to consumption. And then also we still have urbanization undergoing especially in emerging markets that will also underpin the demand. And into all this there are some concerns about supply. We are seeing that already on the mining sector where, where some of the these projects that can take many many years.
And while we try to, to, to to make smart decisions at Kakulu on a, on a one week basis and in, in at my work in probably slightly longer than that, then the mining companies they have to look 10 to 12 years out and try to gauge what the price would be out there. And that's really, that's really holding back some some investment idea investments and that potentially could lead us to this, to this potential shortfall in in over time in some metals. So that's what we're focusing on.
But just right now Coco was a big one last year. This year it has to be, we have to say it's coffee. If you look at the soft simply because these are exposed to production or to production from relatively small geographic geographical areas making them much more exposed to any weather developments. We're seeing that West Africa with cocoa. We're seeing that now in Brazil for coffee. So that is really moving up.
And then we talked about before we started natural gas is, is actually on the move and now we're up 30% this year. It's after having seen a large drop last year and I think that's probably one of the ones where I have a longer term quite a bullish view because us US exports of gas is rising. US demand for gas as well is also rising and that will over time underpin prices. So that was just not brief. But there's a lot going on and. Europe's demand for LNG is rising.
So to put some numbers on it, Net Gas Henry Hub Net gas is up about 30% this year year to date. Most of that came in the last couple of days given a colder weather outlook for the States. Coincidentally today is the 20th of February. We got kicked out of a short Henry Hub position which we've had on for more than two years.
It's been a great trade for us Natural Gas prices in the US have been falling quite a bit in recent years and that rally over the past couple of days has put us out of the position. And like you say, cocoa is down about 12%, coffee is up 30% this year, gold is up 15% this year already we're not even 60 days into the new year and gold is up 15%. I think you've mentioned the index is up about 10%. So quite a solid start for commodities. What do you think Ola? Copper.
I always think Dr. Copper is interesting from a macroeconomic perspective as well. It didn't perform very well in recent months, but this year already I think it's up 15 or even a bit more than 15%. What's driving that? Well, several things I think first of all foremost the fact that China hasn't been slapped with terrorists just yet. That's probably one thing. But also I think the general threat of terrorists has created quite a few shenanigans in the New York Comex markets.
And the copper is obviously one. High grade copper is obviously one of those. So we're seeing right now that futures prices for gold, silver, copper, platinum, they have all been elevated relatively to international spot prices, especially those we see in London. And that is due to the worries that a lot of these metals has to be imported.
And suddenly if you have to pay in tariffs to get the metals into the US that obviously upsets your whole calculation if you're short hedging against physical positions elsewhere. And that's where we often see the futures market being used because with depth of liquidity and round the club trading it is the favorite place go to place where investors and physical traders they offset their risk in the futures market. But obviously short position doesn't work if you actually need delivery.
And there's terrorists and we saw that actually just last Friday. If we look at the price based on London metals, at one point the New York spiked to $1,000 premium over new York. That has since reverted a bit lower. But it just highlights a lot of uncertainty. We've seen massive amount of silver and gold being shipped to New York in the past couple of weeks simply because if you have access to physicals and you can sell the future against it, you are earning a handsome return.
And the question will obviously be what happens when these spreads normalizes? Then there's a lot of physical gold sitting in the US with no end user. Will that then go back into the market or will we continue to see selling hedging hedge selling against it which potentially could have a small Negative impact on prices, but a lot of things going on in that market.
But copper, I think just generally it is a market where the demand in China has held up phenomenally well, even though the construction sector has gone into reverse. And as we highlighted the. Right now we're seeing that with the data centers and the extra amount for electricity, copper is not only an EV story and a data center story, it's also being able to transmit all this power that's going to be needed.
That's why a company like Siemens Energy is up what 300% in the last year because that's really probably where a lot of the gains are being made. Bit like the Nvidia that it's potentially in like the gold digging days. It wasn't a gold miner or gold digger who made the money, it was the guy who supplied the shovels. And that's what we're seeing right now also in the power space that those that are building these transcendors and making transmission possible there, they're very busy.
I picked up that the cash and carry bases on gold is something like 10% annualized on COMEX. Yep. And it, it's probably even stronger right now in silver because there's no last resort lending of last resort in the, in the silver market because if you are, if you have a, if you're short gold in London market you can go to the bank of England and, and lease gold from, from them. There's not no such holdings of silver.
So that's why silver has been been the trick hard hit also or squeezed also because a lot of that comes from Mexico and we're still unclear about. And there's probably more higher risk that tariffs would be added to silver than to gold being a monetary, you almost say monetary currency. So Philip, with all these super interesting things and the knowledge that Olay has just outlined here, does any of that impact what Kalkulu is doing on a day to day basis and how you trade?
Yeah. Moritz, first of all just thank you for having us here at your show. As a regular listener myself, I really enjoy being here. So thank you so much. And of course the impact on commodities worldwide do of course impact Calculo, but as you mentioned we are focused on the very short end. So we have a holding period of as you said like one to 10 days. It's more like two to five days actually. And this allow us to capture on these imbalances as Ole mentions in his commodity research here.
And what we do is really capturing the alpha and then ride this alpha movement and then we use the AI to navigate our exits even better. So for us it's capturing the alpha moves and then use AI to get an exit on our positions. Great, let's go step by step. I mean, one of the first things that jumped to my mind that I'd like to ask you is why did you end up focusing only on the commodity markets?
I mean you could get more diversification by trading additional markets such as bonds and equities and currencies, some of the financials, but you don't do that for a reason. It's a feature and not a bug. You only trade the commodities. Why is that? That's true. First of all, my heart is for commodities. But that is not the only reason for this limitation.
In the, in the space we do trade in the supply demand constraints on these particular instruments is what we actually centered our strategy about. So the, for instance when we're seeing a supply constraint due to a weather pattern regional event that creates fear into the market, this fear sparks price movements. And these movements is actually what we want to capture in our trend following model.
This is not directly something you can do in the equity market or in the interest rate market, but it's really comes very natural into the supply demand constraints on the commodities. Why this strategy works particularly well in these environments. Do you focus on a subset of the commodities? Because you just mentioned weather dependencies. For instance, gold would not be weather dependent, but you know, coffee and cocoa are.
Or are you trading across the board all the commodity markets or everything that is liquid enough for your definition? You kind of answered the question yourself. We only do trade the liquid stuff. So we are in the four major asset classes or groups you can call like metals, agricultural, softs and energies. And we focus on where the liquidity is the highest good because that also supplements our strategy quite well.
We don't trade some of the smaller commodities, even though I know that some of the other CTA funds you as well, I think participates in the orange juice market for instance. That has been a quite a good trade for a lot of the CTA funds. But we do tend to focus on the liquid stuff where we can also grow our fund quite, quite a bit. So yeah, so we are the major commodities basically, right?
I mean clearly you're trading way more short term than, than we do with two to five days, I think you've mentioned. I mean the orange juice position for us has been going on for way more than two years. So you know, we don't really need to tap into the liquidity of that market on a daily basis. But with your trading frequency you're absolutely much more sensitive to that. Then coming back to the supply demand imbalances, I mean it is represented by price at the end of the day.
What is your definition of a, you know, imbalance and how do you spot that? Like what triggers this? Basically we use only price patterns as our entry. We do lean towards very classical CTA mythology because I'm a very strong believer of a. Of the CTA fund and the core around the CTA funds modern day trading. We do need to modify the very classical the way that the CTA evolved and started.
So while we use like a very opportunistic entry signals, very classical CTA style breakouts predominantly we only use the entry as, as, as the first part of the trade. The real advanced stuff actually comes in after we have the trade on the books. And that is our risk management. One of our core fundamentals is that we do want to deliver a very low volatility access to the commodity markets.
So why we do love commodities, Commodities can be volatile and, and through the use of AI we can sort out a lot of the volatility and create a more lineary return profile. Right. So breakout to the upside or to the downside that would trigger the position. You've mentioned Philip, a couple of minutes ago, weather dependency. So you're not using weather forecasts as an input in your trading signals. It is really price based. And price pattern based I think is what I understood.
So search sequence of price events materializing or the price making a new high. And like a trend following trader you would then get long once that, you know, high has been made. That is true in regards to the weather pattern. It really comes into the price. Let's say we have a hurricane threatening the oil rigs, gas rigs in the, in the Gulf of Mexico or Gulf of America, what we call it these days.
That is actually what we are looking at because this threat from the hurricane will trigger a price movement that we can benefit from. And after this initial risk premium being put into the market, the market will look at the hurricane development, the speed the, the classification and when it goes landfall and at what strengths it goes landfall at.
And this period when we actually in this limbo, it gives us a lot of underlying signals that we can use in our machine learning regard to the momentum, candlestick recognition patterns and so forth that we use to classify and use our past history on the TRA and the trace we have already made to see if we can predict the upcoming movement of these particular commodities. So quite often we do participate in these movements where the market stabilizes a bit and trade sideways.
And this is often enough for us to exit the position capturing the alpha and then look for a new signal into the same trend if it continues up. For instance, is this a fully systematic process? Like do your systems pick up that there is a hurricane potentially materializing say in September or October and it automatically filters through to your machine learning environment?
Or is, is it a discretionary input where you need, where you need to nut your system and tell the system hey, there's a hurricane potentially materializing. You should have a look at this data. No, it's all price recognition patterns. So we only use prices input. There's no manual input in regards to selecting signals. It all be handled by our proprietary trading platform. So we don't use any, any weather patterns or any manual or writing in the signal selection process. Got it, Got it.
And just coming back to the entry signals, you're not forcing your system to be long and short at all times. You can be flat as well, right? If there's nothing going on, then you don't have a position in whatever market doesn't interest the system. Exactly, yeah, spot on. So basically as we only want to participate in in real alpha periods, we can be flat and we can be on a partly long allocation or partly short allocation or combination.
So we don't have any mandatory allocation towards individual markets or sectors or groups or directional. We can be in anywhere the market is. Basically let's then move a step forward. Now you have a position, it's been triggered, let's say a long position has been triggered by a breakout to the upside and the expectation is now that you're in that trade for two to five days.
Is the logic a trend following logic in the sense that you would hold onto the position until an exit is elected or hit by price, which is on a reversal you're never getting out on the top. Or you have more different exit techniques where you're taking profits. Basically you can divide our mythology into two groups where we have the, the systematic approach, where we do very classical cta, we enter into a trade, we put in our stops, we use trailing stops as well.
But this is only one part of the trading strategy. As such, because our majority of our trades actually is not held onto the trading stops, we use the machine learning exits which takes out, I would say 80, 75, 80% of our trades is handled via the machine learning exits. So basically what happens is that on a daily basis we Collect a lot of data concerning the individual trade we have in our books.
This could be candlestick pattern recognition, momentum, angle on momentum and other indicators as like that is part of explaining the current movement on or the current short term trend. We then use this data pattern that we have collected on the individual trade on the day we go into our massive massive database where we can see if we can find a similar pattern as we have collected on the day for this particular trade.
And this is where the matching happens basically because when we take this new data put into our database, it finds a match that is as close to something it has seen before. And as this is historic trades, we do know the outcome of these particular trades. T +1, T +2. So this actually gives us like an indicator on when we have seen these patterns before what happened to this particular trig. And this is basically what we use. And then we classify them as keep or eliminate.
And if it's eliminate then we take them off the books and look for new entries. Basically. Are you streaming tick data to your systems or is it batched into 15 or 30 minute bars? Or I assume that you're using more frequent data than a daily open, high, low close for what it is that you do. We use various time frames, but when we do it on the close in regards to the machine learning, we actually put emphasis into the daily bars and the daily data.
Because as I mentioned before, we do believe in the CTA mythology, We do like trends and all that. So we just classify the trends differently than a traditional CTA. So while classical CTAs are in trends for the long term, for the long time, in the long run we try to capture bits and pieces of these existing trends, trying to vet out any counter moves along the way.
Doing that allows us to maybe not benefit from the entire trend, but we do capture part of the trend and we vet out the volatility allowing us to create a much smoother ride than than the longer term trend followers. And all the entries entry signals are pure trend following signals. Or do you also combine mean reversion and other type of methods and strategies into the mix? We use trend following strategies to enter. The markets trend only. Okay, so.
So let's have a little bit of a chat about machine learning and we're not using it. I'm definitely not the best person to speak about it because I don't have much experience with it. But how does it work? Like how do you prevent the machine to learn from the noise which is a prevalent factor in the markets? I mean there's also a lot of silly things that a machine can learn. You want it to learn the good things.
I sometimes joke that a clever machine will probably learn to buy the breakout and become a trend following trader long term. But I may be wrong. So how do you make sure you understand what's happening in the black box? Or is there even a need for you to understand? Or could you just say well we don't care, we just want to make money, it's fine as well. That's a very good question actually.
And keep in mind that we do not use machine learning techniques for the entry and that actually answers your concern because when you use machine learning for the entry signals then you actually put great emphasis into guessing where the market is is moving. And I'm not a strong believer in in that part actually. So I do believe that trends have strength. So running along a trend is in my opinion a very strong part of this environment that we're in.
We only use machine learning as a risk of mythology and this actually changed the picture quite a bit because if you use machine learning as a risk of mythology, basically let's say if we go back to the hurricane example we used before. Market has risen quite rapidly due to a hurricane threat. After the first initial risk premium being put into the market, the market stabilizes. Everybody's watching the weather reports the path of the hurricane and all that stuff.
So the market stabilizes and trades sideways. Maybe even some of the traders take profit on the initial move. So it might maybe even like trace back a bit. As a short term trader our system reads the short term trends towards the long trend. So these movements and the actions around this stabilizing period is enough for us to get valid data into getting signals on how to take when to take off this position.
So we log in the first part of this risk premium, take the profits and then look for a new signal. So when the market either collapses because the hurricane didn't hit or hit the the oil rigs and cause lot of dis destruction and the trend continues, we can actually re enter into the same trend that we captured the first alpha move on and get the second leg of this particular trade.
So we actually it only uses it as a risk off element which changes the picture quite a bit compared to trying to build a fully AI model that tries to predict the price targets. Yeah. So it's all happening post entry. Once you have a position on in the materials Philip that you kindly shared with me ahead of the call they mentioned adaptive execution is the adaptive execution piece what you mean with getting out of the position and essentially taking it off off using machine learning techniques?
Or does it also mean that you have a more smart, clever way of executing your trades in the market using alos given that you are short term? You know, I reckon that you have some sensitivity toward that. Sure, both. So we, we both use advanced ALOS to get into the market. But the adaptive stuff is also very, very much in meant as the exit period as well. We also use like a time of the exits as a parameter as well where we try to get our exits in liquid periods predominantly.
So of course our stops are executed as it happens, but our machine learning exits actually timed towards the most liquid time in the US because remember that these machine learning classifications are not firm predictions that the market will collapse or go against your current position. It's just a flag saying be aware there's a potential correction ahead of you. And this is why we take more in the liquid periods. Right. Creating a segue to OLA here.
Ola, I'm sure looks at all the commodity forward curves, whether they're in contango or equitation and seasonal and all that. Does this information trigger anything at Kalkulu or are you maybe even trading spreads which you know, you can do in the commodity markets? We're not showing spreads as is. No. Okay, but Ola, you have all this information about the forward curves. You have this view into the commodity markets. But I also know that you're an investor in Kalkulo.
What has triggered your choice to you know, put your money into a quantitative long short commodity strategy as opposed to one that is fundamentally driven where you know, we just spoke about copper and cocoa and coffee and all the views that you can have on these markets. Well, I, I have it as, as, as part of a general exposure because I, I like commodities. I, I've been involved with commodities for, for more than 20 years.
And, and it's, it's really where I, I, I feel that as I have an edge but obviously I known this the Kakul for many years and I have been involved for a number of years. Probably what attracted me into an investment originally was simply the low volatility and returns. The correlation between returns and the low volatility really quite appealed to me. And then there's also simply to have a different approach instead of just a long only.
And, and, and when you look at, when you look back and we look at some of the performances, it's actually interesting to see that the, the Bloomberg commodity index that I do that I do follow obviously on a daily basis that the performances difference is not great. But the road travel to get to where we are today is massively different.
And that's why I prefer this kind of strategy because just looking at the Bloomberg commodity since in the last five years we've had three we had several drawdowns.
We had the two biggest one was a 77 months drawdown between 15 and 20 where it fell 38% then we had a 33 month drawdown up until now we still haven't reached the top in 2022 but the initial drop off in this latest correction which we're now trying to reverse was 22% and that is really these kind of drawdowns is, is what you have to have to accept in order to get this long term return which then ultimately end up being not being significantly different to what what Kula has has, has presented
with a, with a much lower volatility. So that's really what what what attracted me into it. And I think also also what I have noticed is on, on some of the months where we've had the, we haven't had many but I think we're probably going to get more in the future where we had to have bad months for equities we quite often find that there's actually some positive months coming in through the commodities. So also just generally lowering the overall volatility across your investments.
I mean commodities don't have the equity drift or anything like that. I really think there are markets that you should be trading long and short and when you look at the BCOM index, well first off all of these indices, the first generation of these indices they're equity and metals heavy and then there's all the smart variations that are more diversified and they distribute liquidity across the curve more.
But I think COCO for instance because it's a relatively small market is not a BCom member probably for the last two years. They wish they had it in there it would have made a difference. But luckily you can say this year last year it was the natural gas which is member that draw dragged it down and cocoa which was was not involved. And this year it's, it's there's now coffee that is both coffee and natural gas. That's that's putting but putting higher.
But yeah no doubt that some of the others last year had a very good year but also meant that there was a massive re rebalancing in in the, when the, when the January came because the the percentage share of or exposure to cocoa out of the total was uh. Had gone quite extreme because of the, the big gains we saw last year. So, so yeah, there are, there are, there are different ways. I also watch ETFs where they try to be smart on the role. It hasn't been.
I don't find them having been particularly successful. They haven't really outperformed the main total return in the indices. So even though we are in a situation that you mentioned contanguant backwardation where we generally are starting to see a positive role yield coming into the markets. Except. And the biggest option is obviously where you just have had your profitable short in natural gas. Because.
Because the contango structure basically means this is a market that even though we're seeing sometimes seeing big rises over time, you're actually making money. You have been making money being short simply on the roll from a low to a high contract every month. Well that's part of it. We're not rolling every month. We're aware of seasonalities. But yes, for sure we did benefit from the generally upward sloped forward curve there. Philip, I think you wanted to jump in and say something.
Yeah, that's right. Just to supplement Ola's comments here. One of the things that we actually also have seen in the Calculo fund is that we over the past seven years almost since inception has actually delivered equity like returns at two thirds of the volatility of the broad stock indices. This is also just one of the selling points for Kalkulo strategy being a low volatility strategy and non correlated, non cyclic.
So actually allows a lot of our investors and we see that a lot when we, when we meet our clients that we can actually offer something different to them that they can get from other asset classes. We are liquid, we're not correlated and stuff. So it's really an add on from for many of our clients in this space. Sure. One question I'd have Philip Benjola is you're domiciled in Denmark and I think you're the only fund that I know that is domiciled in Denmark. How did that come about?
I mean it is not known as a hedge fund land. Neither is Germany for sure. But you know people go to Cayman or Luxembourg Island. You're in Denmark. Why that? First of all we are Danish. Sure, that is one thing. But yeah you're definitely right. I think we might have broader audience in a different country than Denmark but sometimes having the space on your own is also an advantage.
So we are probably the only pure commodity fund in Denmark and it's our job to educate and to get the word out there. And anything that's on the horizon for you guys in terms of how you're looking to grow your business and develop it, maybe become more international. Definitely. We have explored the options of doing like a US setup because strategies like the Kulo strategy would really thrive in the US I believe.
So this definitely one of our things on the agenda to look abroad to see if we can actually expand our client network in more commodity knowledgeable areas as well. Would you also trade SMAs or are you purely focused on managing funds? We'd be looking into both, actually. We wouldn't rule out SMAs that would require a US license for that, of course, but definitely it's all in the pipeline. Excellent guys. Thanks very much for coming onto the podcast. I really enjoyed it.
I hope our listeners will find the conversation valuable and interesting as well. As usual, we'll include the most important points of today's discussion in our show notes. And also, as usual, you shouldn't hesitate to contact us if you have any questions. Our email is infooptraders unplugged.com so thanks again for listening. And until next time on Top Traders Unplugged. Thanks for listening to Top Traders Unplugged.
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