Lead-Lag Live

Access the AI Revolution — How AGIX Gives Investors Pre-IPO Exposure to AI Unicorns

• Michael A. Gayed, CFA

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Join me live as I sit down with Derek Yan, Director at KraneShares, to explore how the AGIX ETF is reshaping AI investing by giving everyday investors exposure to private AI unicorns like Anthropic and xAI—companies powering the foundation models behind the next wave of enterprise AI.

In this expert-led discussion, Derek explains how AGIX combines public equities with late-stage private companies, the proprietary AI scoring system that drives stock selection, and why model companies are the epicenter of the AI value chain. We also cover AGIX’s performance to date, its dynamic quarterly rebalancing, and how it navigates valuation concerns in a fast-moving market.

In this webinar:

  • How AGIX gives investors rare access to private AI leaders like Anthropic and xAI
  • Why foundational model companies could capture the lion’s share of AI value
  • How the AI Score framework identifies true innovators vs. “AI pretenders”
  • Why enterprise AI could outgrow consumer AI in scale and profitability
  • How hybrid ETFs unlock private market access with daily liquidity

Lead-Lag Live Webinars give you exclusive access to deep-dive conversations with industry experts, portfolio managers, and strategists. Subscribe now to gain the insights you need to make smarter, more informed investment decisions.

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Speaker 1:

Thank you everyone for joining today's webinar. I mean, it's a quiet summer week, but there's a lot going on. Actually, nvidia just announced their earnings. There's a lot of earnings call recently on AI companies, especially the portfolio company of our AGIX ETF. So I mean, like just look at today's performance of this, it's doing very well.

Speaker 1:

So we are that's kind of like in the mind of everybody like we're now like in the third year of AI, right. So everybody's like either I own it or the third year of AI, right. So everybody is like either I own it or I have some way to get access to this. But we think this is like a multi-year opportunity and if you can get it right, you're probably going to have a good long-term result benefiting from the AI revolution. I would say so. With that, I think like a lot of people also like curious, like what are we talking about today? It's like private AI unicorn in an ETF. That is right. So we're kind of like pioneering in this kind of like the ETF industry, kind of like a pioneering in this kind of like the ETF industry.

Speaker 1:

Just to give a little background, craneshares we are 13,. We launched our firm on 2013. Now it's over like 12 years history matched $11 billion across our 30 plus ETFs, mostly listed on New York Stock Exchange and NASDAQ, so anyone can buy it. So that's kind of like our business setup. We are kind of want to be very innovative, bring high conviction ideas, hard to get access markets to our investors. So, like in history, we have been focused on a lot of categories, including a lot of China thematics, a lot of climate related alternatives and also opportunities globally. So AI is one of our latest focus. We launched the AGIX ETF about a year ago, on July 17, 2024. That's kind of like the second year when everybody's already like why did they use ChatGPT, getting used to, oh, bring AI as part of their life and work.

Speaker 1:

But we don't think, like most investors still is really lagging in terms of understanding the true power of AI and the potential of AI, or like how to really invest in AI. So that's why we partner with someone I call Aetna Capital Management. They are a bunch of AI native investors, engineers, who are like venture capitalists, being in the industry forever investing. They're early investors in companies like Anthropic XAI, proplacity you probably heard some of the names. Some are really leading financial, large-language model companies, foundational model companies like Anthrop XAI. Some are like AI native applications, like Proplasty, who claim to want to buy Chrome. If you watched news recently, those companies are really the companies driving this round of innovation.

Speaker 1:

So when we look at the market, there's some AI products mutual fund or ETS but none of them are backed by venture capital insights. Because if you're not really investing into those foundational model companies or AI native applications, you're not situation aware. You're not really. You're not like techie enough, right, you are traditional, like Wall Street guy or someone like me. Sit on New York. You're not really situation aware. So we have we need partners to talk to the foundational model company who know the future of next generation of models? Who knows how Agile AI gonna deploy? Which company gonna benefit? So all those insights, we translate that into an index called Selective Aetna Artificial General Intelligence Index. So does AJAX ETF gonna track that index Basically based on that AI score that's going to pick the we'll call it winners out of the whole AI. Every company is going to claim we're an AI company, but who's going to be the true AI companies, right? So that's a process we did for the public equity.

Speaker 1:

But when you look at investment, there's something missing. How can you say you're investing AI, this round of gen AI, without investing into some critical companies in the model space or the AI native application space, because they're private? But even they're private, we're talking about like multi-billion or hundred billion dollar valuation companies. If they IPO today, they could be part of the fund. So the idea is like let's do a hybrid ETF that we can not only invest in a public listed company but also the pre-IPO company in the ETF directly because they know the companies. So with their introduction we connected with the company like Anthropic, xai, Proplacity, and we actually invested into Anthropic and XAI currently in the ETF. So that makes the fund quite unique to providing access to the opportunity that's really critical for this round of Gen AI.

Speaker 1:

So with that we launched Ajax and then I mean we see this is everybody's thinking, oh, this is thematic, this is not a theme, it's going to be all hype bubble then over. Well, when we look at AI, well, there's a lot of themes, right, like just short term, but AI fundamentally is more like a structural growth compared to a lot of other themes. Because just look at like this year, right, like S&P was up like 10, 11%. Actually 60% of that return contributed by AI names. So without AI S&P is only like 3% 4%. We have seen that trend like over the last two years.

Speaker 1:

But if you're going back way over you can see each time there's a technology breakthrough or new technology wave you're going to have a bunch of companies that's driving the whole return of the equity market or the broad benchmarks like S&P 500 or NASDAQ 100. You, starting from like the mainframe, then to the PC, with the PC you build out a whole internet industry. Like then you have all the data Now putting the cloud and SaaS opportunities driving the returns over the last decade. Those structural growths are really sustainable. There will be ups and downs but if you happen to own those subsectors of the equity market you are likely to outperform the broad market equity return. And we believe the AI just started. Right Now we are in the third year.

Speaker 1:

Think about the early adoption. Just like currently most people know chat, gpt. That's only consumer facing, that's a consumer opportunity. But if you look at like history, like what SaaS did and cloud did to really change the way that enterprise across American and the whole world actually operate, you realize that's a trillion plus opportunity and you probably realize that, like that trillion dollar opportunity is much bigger compared to kind of like the early internet and PC opportunity.

Speaker 1:

Kind of like the early internet and PC opportunity and also internet and PC opportunity is bigger than the mainframe because each technology breakthrough is based on the previous breakthrough, previous wave. You are building the multiple layers, right? You know the first layer. You have the hardwares and the softwares and internet built upon that. It's going to be bigger because it's leveraging that and we have seen that for AI. This is a super cycle that is based on all the previous technology breakthrough, so it's going to bring a much larger opportunity going forward for multiple years and we're now only three years from the start of AI and that makes us believe like we should own some like early opportunity, right, who's really disrupting this? Everybody saw NVIDIA but like who's really using the technology to really bring the foundational model to power? All the computing of the AI applications, the cloud computing and all the adoptions is really the foundational model companies. So that's why we think having access early is important.

Speaker 1:

So we are currently like a shareholder of XAI and Anthropic. Agx, on behalf of GreenShare Trust, sit on the cap table. We added Anthropic on March 5th 2025 through their series E round of financing and XAI on July 18th through their tender offer. So those are really our addition, our investment in the private this year that become like making those two companies become part of the ETF holdings.

Speaker 1:

So looking at like the access right, a lot of people think like if I want access to this private companies, I have to like be a credit investor, I have to pay two and 20 to the private and VC funds and lock up for 10 years. So that's very traditional ways to invest into the private companies and there's some interval funds right. So it's like between the traditional and the mutual fund you lock up with like worry, uncertainty of like when you're going to, what's the exposure you're going to have with the quarterly liquidity. Then, like the hybrid ETF, what we do is really in between the interval fund and traditional ETF. So think about traditional ETF you have daily liquidity but no private. But we have daily liquidity and we sell in private. So that I think the number one question that people ask how do you rally those? Those are private companies. So just like and actually we are kind of like one of the first firm doing that in the ETF world, but there's many companies that have been doing that, like Fidelity, barron's and Tiro. They have been putting private companies in the mutual fund space. So we're just bringing that best practice to the ETF industry.

Speaker 1:

Etf, at the end of the day, is a 48 fund, so that makes like something. Well, people should do that. But like, why is not? Well, there's, it's not necessary, right? What's the rationale to invest into the private vehicle when you have good returns on the public, right, as a fact? Right, the private investment is really different by the year you put your money. They call it vintage. So, like early times, like when you're putting in some like private companies, but then the old IPO happening in 2021, once you have like a lockup expired, you probably like companies like a very poor performance. So that's really hurting people. Or they're now thinking about like private companies. They have to consider a lot of things when they go public. Right, there's tariff. There's, like the president's trade and other like policies, uncertainties, macro. Why bother? Right, I just want to do business. Well, I just want to grow my business Anthropic. I think their annual recurring revenue was like about $1 billion last year, july I think it's now approaching like $4 to $5 billion. So that type of growth is like amazing, but like, if they're like a public company, they're going to go through the April Liberation Day and everything like that. So that's kind of like the.

Speaker 1:

I think that's why a lot of companies, especially even companies like with variation of hundreds billions, they're choosing to stay in the private longer. So that's why I like investors to if you missed out those opportunities, you probably missed out a lot for the private side, because once they become IPOs, it's really hard to get access. Actually, looking at like now, just recently, I think like, look at the Circle, figma, right, corby those IPO markets have been really coming back. So, like, if you think about, like the potentially this cycle of the private market especially what we did is really late-stage pre-IPO companies like Antarctic and XAIAI and potentially in the future, as well as similar companies is really capturing like this trend, right, the good companies tend to be in a private market longer, so you need to really get access.

Speaker 1:

So, having talked about the fair value, right, like, we are daily liquidity. So that's why we have a just similar to what the practice that BlackRock sorry Vanguard, fidelity, ethereum and Barron's doing. They have a fair value committee. We do the same. So we have a daily fair value committee to give a fair value to those private holdings committee. To give a fair value to those private holdings, so that's reflecting in the NAV and the NAV not as a value of the ETF, so that investor is really getting a fair value of those assets and that's providing daily liquidity. And our AP is going to facilitate that. The public equity is going to be in-coin transaction and the private is going to be cash transaction creation and redemption for the ETF. So that's the mechanism of this fund. So you know, that makes the funnel unique because you have access to some companies. Probably you don't get access anywhere, right?

Speaker 1:

So, anthropic, for people who are not familiar with that, they have a consumer-facing app called Cloud. It's a competitor with the ChatGPT backed by OpenAI. We think OpenAI is great because OpenAI is like kind of like the most popular consumer app in the Gen AI space. Everybody's like, if a consumer, you're going to use ChachiBT because it's famous, everybody knows it. But actually if you're enterprise, things are a little bit different For, like, I think, current stage of adoption, most enterprises are using AI for, say, coding, right.

Speaker 1:

So the highest adoption rate of company type is actually technology companies. So technology companies are using AI to read the automatic code and forming all kinds of workflow from the back end to the front end. That workflow automation can be really integrated with the autonomous decision maker of AI and agents. So those agentic AI solutions really now widely adopt in the technology space and that's kind of like the fastest growing adoptions in the technology space and that's kind of like the fastest growing adoptions in the AI currently. And who's capturing that? Actually, we think Anthropic has the potential to really become a leader in that. If you happen to be a software engineer or you know someone who's a software engineer who code every day, they're probably using uh like cursor, uh or um the cloud code coding, um cruiser is also using cloud technology. So like eventually, um, those like apis, those traffic, those revenues, uh, gonna be passed through to the anthropics api, going to be pathed through to the Anthropix API. So that's kind of like the revenue making they're doing.

Speaker 1:

As I said, the revenue has been growing very fast. It was just $1 billion annual revenue last year. Now it's almost 4, 5x. So that's really a competitive edge, I think, in the enterprise world. And so that's really a competitive edge, I think, in the enterprise world and we believe enterprise AI is bigger than consumer. At least like next two to three years, the enterprise is going to be the main kind of expander on AI. They're going to spend a lot of money. Think about, like those technology companies, they're like trillion dollar in valuation. The tech industry is the humongous. So the amount of money going to be spent to automate things is going to be people are not going to see in history, right. So we call that kind of like the AI revolution in the enterprise world. So I think this trend is way bigger than the SaaS and cloud. So if that's going to happen, the company is going to provide that solution to enterprise. It's going to be critical.

Speaker 1:

We've seen some companies we own, some companies in the public space, like ServiceNow, like Patenteer, who really providing the either contacts layer, or some like the automation, like the automation layer in between between, like Anthropic and OpenAI and XAI, those financial models and their final use cases and application adoptions on the enterprise side. But we do think those foundational model companies is going to take a large part of the revenue across the data chain. For the XAI we invest about like 1.5 million, I think, in July. So XAI is really a company we think is very special because of Elon and Elon's ecosystem right. So Elon on Tesla Robotech, ciatan is driving SpaceX owns Neuralink. It's going to do humanoid robotics. So all those things are going to rely on AI and data. So we feel like Elon's ecosystem is quite unique. They are unique in access. They have access to the social media data, they have access to the chips, they have access to the social media data, they have access to the chips, they have access to all those kind of like travel data, driving data, humanoid data going forward. So all this data becomes so valuable for XAI going forward. That's why, even though I think recently, like XAI's GROK4 model become the most intelligent model because they have, like, a lot of chips and a good algorithm as well. So that makes XAI a very exciting challenge actually to open an anthropic. We're going to see Elon's going to bring XAI to a unique position within his ecosystem. So with those two companies, we built a portfolio actually around those foundational model companies.

Speaker 1:

If you think about the stack of the AI ecosystem, you rely on foundational model to really taking input, generate output or building AI agents. Then you need an infrastructure right. The infrastructure is really the cloud, the data, all the data preparation, the contacts, everything that's supporting the model, the computing. Then within that infrastructure, you need hardware companies NVIDIA, of course, then other energy-related memories and manufacturing. Then you have AI applications that are going to use AI that's going to either consumer side or enterprise side. So we have, as I said, we build this framework based on the insights of the AI researchers and winter capitalists, who's really at the forefront of the AI investment in the private space. So their connections and their knowledge on the ecosystem is way better than me and many other like kind like buy-side analysts.

Speaker 1:

So I would think like this is framework that's going to really dynamically capturing like who's going to be really benefit from either disruption of the AI models or the disruption in the business model for a lot of companies, even the companies that we all know, like Google's, like AMD's. Those companies somehow are going to be disrupted. So how do you evaluate those impact? And that's very dynamic every quarter. So we have this process to really identify the company is going to be in the portfolio, the weight. The process is really like rule-based right. So we have a universe of 2,000 to 3,000 companies. It's like the AI industries like that's really broad right.

Speaker 1:

So that then the critical part is the AI score. You can have the relevance and readiness of the company. So, based on the insights of AI engineers and we're going to weight the companies based on the score and also the free-for-market cap, the index is rebalanced quarterly with some capping on either categories or single companies. With that process we can really identify companies as really relevant and ready for AI. So for relevance is looking at like things like their revenue contribution from the AI product. How's their current product progress, because I think a lot of companies really developing and fine tuning their product. So you have to check their progress and their readiness. So future revenue visibility if they can really make money from AI or they just like spend a lot of money and not able to make money and how's their business model when AI is going to disrupt it, when AI is going to make their business model weaker or stronger, right.

Speaker 1:

So we want to really build a systematic framework, holistic framework actually for investors to really capture this long-term AI trend. But not worry, oh, I'm picking the wrong name or I'm like just betting all my money on one company. So like a basic approach is what we think is the best for long-term, very diversified and relevant approach to really capture this long-term trend. And we are kind of like we're diversified in terms like allocation as well. We diversified across all the AI stack from hardware to infrastructure models to application. You can see the subsector, sub themes within each category, each stat, and this weight is also based on the AI score. So it's dynamic, right. So I think this weighting has been changing. I remember, like back in when we launched the company a year ago, a lot of weight is in hardware Then. I think now a lot of like application infrastructure companies now becoming more crucial. Then they get a lot of the benefit and the weight is more towards that.

Speaker 1:

So, going forward, it's going to be this trend is very similar, right, I think, previous technology breakthrough. You have the value migrating from hardware to infrastructure applications. You have to see that in AI as well. But I think there will be some back and forth based on the latest dynamics and models and how the AI research thinks. So we have this quarterly process really dynamic, allocating between the three stats and the performance is showing that the AGS has really outperformed major growth or technology index since we launched the fund on July 17, 2024. You can see that we are like about 30%. I think this data is outdated. It's as of like July 25th but as of today. We're like 38%. So that's something I think investors should compare themselves on Bloomberg or Yahoo or any, or Cranesharescom slash Ajax. You can see the performance of the fund compared to NASDAQ 100, technology Sector Index, s&p 500, or Semiconductor Index. You can see there's some major performance out there because the framework we talked about and because we think this is a long-term trend to really identify the company can truly benefit from AI to capture this structural growth going forward.

Speaker 1:

And AI is volatile because I would think just like any previous technology breakthrough, any technology if you think about Nvidia, amazon, google and Microsoft in the history, you have some meaningful drawdown. So that's kind of like I want to remind everyone who's want to invest in technology and AI specifically, you should be careful if you're not really risk tolerant. So we think like AI at least has like a similar volatility compared to NASDAQ or technology sector Just seems like semiconductor is more volatile. It's more like cyclical, but just generally technology has more volatility. But if you look at like AGX risk adjusted return, risk-adjusted return is not really it's not actually taking a lot more risk compared to like technology sector is less volatile than semiconductors. So that makes actually AI. If you have a long-term horizon and you have a good risk tolerance, it's a good long-term investment to really growth the capital. So with that I think I talked a lot, but happy to take questions. I've seen some like Q&A questions. So before I do that, I just want to thank Michael and everybody again to join this discussion.

Speaker 1:

For AGIX, we are ATF. We list the fund on NASDAQ and the latest information is available on cranesharescom slash AGIX and if anyone want to know more about coinshares, please check our website. We have several articles, webinars and, I think, white papers on the AGIX fund. It's kind of like our latest innovation. So there's a lot of questions, people asking like oh, how do you do private investment in ETF? How do you do that? So we have a white paper actually on our website how to really unlock private markets with a hybrid ETF so you can check that you're more interested in into the mechanism of the fund. So with that, yeah, I'm going to go through some like a disclosure thing, have to take some questions or we can chat more about the AI, okay.

Speaker 1:

So the first question is I'm at OZEAC. I do not have access to this ETF? How do I get it? So if you are like a financial advisor at a platform, you definitely can request it and we can contact the platform really to onboard the ETF. So so far, we just launched the phone on year. So I think a lot of platforms require one year track records. We just we just passed that, so we are onboarding this fund to many platforms that currently. So, yeah, that's, it's great, like you're interesting. So let's, let's, let's do follow-ups and if you have more questions, you can email us at info at craneinsurerscom. We can do a lot more follow-up discussions and we can talk to your platform to really make sure, like this platform, this ETF is available on your platform.

Speaker 1:

We have a question from Hans how will the private company positions work? If the ETF has significant inflows, will the position size be diluted? The short answer is yes, since we are investing $1 million into Anthropic and $1.5 million into XAI. On Dry, by the time we invested, I think it's about like 8%, but with more flows coming in, the private is going to be diluted. But also, you have considered a fair value, because I think we invest in Anthropic at a valuation of 61.5 billion. Now the company is talking to Nestron, which is a much higher valuation. So along the time we have a fair value committee that are considering all the information that we're going to have a fair value of that. So the total value of the private is going to change as well. So all those factors are going to impact the real-time weight of private exposure within the ETF.

Speaker 1:

But how do we really prevent dilution going forward as we grow the fund? We have a very strong pipeline that we work with our partner, aetna Capital Management. They're on the cap table of many AI companies. They have a close relationship with many AI companies including. So first we're on the cap table of Anthropic and XR already. So if they do follow up rounds we can actually participate and invest in more. If we have more money available and the pipelines is really beyond that, we have been talking to many other companies, like in the AI space, so that pipeline is very critical. So whenever we have a deal flow, a deal opportunity, we can take it. We can actually just adding more private company going forward once the fund becomes bigger. So generally we are talking investing about like 10% by the time we invest and we're going to keep adding new names to the portfolio as the fund grows bigger.

Speaker 1:

Okay, so, hans, you have another question. When new ETF shares are created, assume new XAS shares cannot be purchased. Yes and no right. So that's what I answer. Right, with the inflow you're going to have new shares created, so the public equity is going to be in-coin creation. So our AP, our broker, is going to deliver the shares of those public equities and the private portion is going to be cash creation. So we're going to receive cash. So we cannot invest in XCI directly at that moment. But, as I said, we have a strong pipeline that's available. We're going to keep investing more money to target a decent weight of the private within the fund. So that's kind of like the plan for the ETF going forward to maintain the right exposure to the private AI companies, as we talked about today.

Speaker 2:

Derek, I just wanted to ask a question as well. I'm talking about where you're allocating to private companies, public companies, etc. More like in terms of the segment of the AI ecosystem, with hardware, infrastructure, applications, etc. Which of those three areas do you think offers the most untapped potential in terms of AI?

Speaker 1:

So currently I think a lot of people just don't have any exposure, any direct exposure to the model company. When you think about model companies OpenAI, anthropic, xai I think they should be part of the infrastructure or they should be a standalone. Actually, they are at the core of the ecosystem, right? Actually they're at the core of the ecosystem, right? Because think about, like, what is driving this random innovation? Chatgpt is everybody knows that, so people don't have access. So now, what's driving this enterprise? Ai is really Anthropix, api, all those like models really powering the AI agents to automate workflow for enterprises. People don't have access to those models as well. So those model companies I think is very unique is at the epicenter of this round of AI investment, but that's only in the private side. You do have a little exposure like Microsoft a little bit, some like OpenAI. You have the other like Google, have this like Gemini. You have Facebook meta apps. You have some models through like public holding, maxapp, but it's not direct, it's not really pure exposure to the model companies.

Speaker 1:

Then I would think, application offer more opportunities going forward, just like many technology breakthroughs. Previously you do buy NVIDIA. Now then you're going to build out all the database data centers. All those CapEx are going to be deployed and they're going to build out all the database data centers. All those CapEx are going to be deployed and they're going to generate returns.

Speaker 1:

Cash flows are high going forward, but all that is based on the application Right. So previously we have seen that trend similar in the Internet the consumer apps, enterprise apps, all those then those apps, those software companies, now becoming like now, multi-billion dollars from a few hundred millions so then now trillion dollar now. So that trend is similar. I would think going forward, where companies can really build out applications is going to capture a big part of the value. Where companies can really build out AI applications is going to capture a big part of the value going forward. So that's potentially, I think, a future investment we're going to focus on is really AI-native applications, maybe on the private side and public side. So that's kind of like the eight to four planning. Yeah.

Speaker 2:

And then that relates as well to the AI score, right, when a company starts out being hundreds of millions and then goes to billions. So when you're adding private companies, you're looking at that. They have a clear path towards monetization, right. And then how do you take that and work it into the AI score?

Speaker 1:

Yeah, so that's part of the score we're calling revenue visibility. So basically means they can really make money going forward. So if you think about it, there's a lot of AI companies there's. If you think about many other AI ETFs. There are like 70, 80 companies that any company putting AI in their description or prospectus earnings call it's going to be screened as an AI company by the index provider. Then it's included in the ETF.

Speaker 1:

So we don't like that approach because I think, going forward, every company AT&T is going to say we're going to use AI. Che is going to say we're going to use AI. Che is going to say we're going to use AI, but that doesn't mean that's a good investment. Well, potentially, but that's really relevant for this structural growth. You really have to look at how much impact from AI to this business model and how much monetization they can make. And even some pure AI companies like Kuser, like I talked about is the private company, but I think a lot of the revenue eventually going to be passed through to Anthropic, because they pay Anthropic for API to really making that software service available, to really making that software service available. So themselves, if themselves is not making a lot of money, but actually they rely on another company. We don't think that's like healthy. So, similar to many other public AI application companies, I think like if the company just like wrapping AI with a very thin margin, they're not really creating a business model.

Speaker 1:

That's going to be. You have this flying wheel of monetization. It's really hard, I think, especially at this stage when everybody's questioning demonetization so investors become more picky on companies. I think it was going to be. There'll be a lot of questions, a lot of cautious going forward If just company claim to be from the earning call. You probably noticed that a lot of companies that we don't own but like people thought oh, it's AI play actually tanked after earning call because it's not making money right. So we have seen that trend for a year now. So that monetization, the business model, is very important and really you need someone to assess that. You really need someone to be situation where you have to talk to the model companies, application companies who are they providing service to and who's actually generating a? The model companies, application companies who are they providing service to and who's actually generating a healthy mode that can really make money? Going forward is critical. It's not just like do keyword searching and finding AI in their description.

Speaker 2:

Right. So then, sort of a follow-up question from that would be since you've been so involved in this space and you're critiquing and going over every company that's not only in your fund but that you've decided to not have included in the fund, what surprises have you seen?

Speaker 1:

We have seen like I think it's a lot of companies that people ask why are you not owning this? So we have to explain why. So it's a little bit risky because what if the company is doing well, but after one year, I think compared to our holdings, to the companies we don't hold, actually for the picture, have we doing? Okay, just like. Even just like when the earnings call come out like a lot of business models really not really having mode right. So they're just like.

Speaker 1:

On cybersecurity, a lot of people know one company I'm not going to say the name, but like it's like oh, that's the AI play. It was like no, it's not, it's not, it's not. It's like oh, that's the AI play. No, it's not, it's not. It's like end-to-end. It's like traditional cybersecurity is not really integrated into the AI workflow. We're not including that. The investor is like pissed because he owns the name. So it's like but like now, after a year, he's like okay, you're right. So we have several conversations like that because now everyone is finding AI names. Yeah, some Western may be doing better than Fun, better than AGX, but I think it's really hard to pick several names and claims like oh, I'm AI ready because this industry is so dynamic, the business industry is so dynamic, the business model is always changing.

Speaker 1:

The capability of AI, of the models of agenda AIs, is evolving every day. Even like we make mistakes, right, everybody makes mistakes because nobody can see the future 100% right we all. I think we live in a time that technology breaks through so fast. You have to keep running every day to really keep up. Oh, what is the genetic AI? What is that?

Speaker 1:

So when we're talking about, I think, like especially in the financial industry, when we are doing a lot of discussion on AI, some terminology is confusing, If not really to the industry, you have no idea what I'm talking about. That's why you have to partner with venture investors who come like they're one step ahead of traditional public equity investors, because they know the upcoming stuff, they know the trend. I think you have to acknowledge that there's a limitation public equity investors because they they know the upcoming stuff, they know the trend. So I think, like you have to acknowledge that like there's limitation of information, knowledge and insights we have. So keep learning, um, and be humble and just like um, keep, keep. Like you can make mistakes, but like it's this long trend, long-term structural goals for community. So we have time, uh, to really adjust and adapt so we can make right decision going forward.

Speaker 2:

Yeah, there's another question that's just come in on the Q&A and that is how are valuations impacting the strategy today and the returns going forward?

Speaker 1:

So that's a really good question because it is really like a mindset, right? So if you think about like AI, if you think about like AI investment or technology investment generally in the past, you have like a period of usually like look at like a SMB founder, right, simple, the one-on-one like buy low, sell high. When the valuation is high, you sell. When the valuation is low, you buy, and in the next five years, 10 years, you're going to be doing better than others. That's still valid. I'm thinking in terms of general equity investment, especially like S&P 500. But you have some period that the valuation is really not that relevant when you have I think this is especially true when the internet was really taking off and you have a period of high forward PE, but the subsequent five-year return and 10-year returns is amazing. So why is that? Because the forward PE is for one-year PEs when you look at next year and without taking consideration of the long-term growth rate, right? So when you have a growth rate like this at the early stage, you have to look at the end game. So in five years, in 10 years, well, how much company, how much money the company gonna make? What's the revenue, what's the earnings? Um, you cannot just linearly calculating the growth return and forecasting the four PE ratio and determine oh, that's the valuation. So I would think like traditional valuations becoming tricky for this type of investment, especially when AI is like internet, I believe. So I would think like considering valuation is important on the short term, right. So it could be when sentiment change, when tariffs come, there's some like short term disruption corrections that those high forward PE companies tends to be sold by short term investors. So it depends on the strategy. You can do that, of course, right. So you can do some trading risk management. You can do hedging if you want to manage risk. But it's challenging, it's hard to time the market and it's short-term Usually. Each correction, just like what happened this April right, we have a huge drawdown actually across the market, especially tech and AI, but the rebound is way bigger than the drawdown and actually looking at the year today, the Ajax hugely outperformed S&P 500 and NASDAQ 100. So how do you really manage that risk? I think like, just as I said, you either be patient, long-term horizon and then just embracing it, or you have even more risk where you maybe do some hedging or like trading strategy to re-manage down the risk. But it's tricky, it's hard. I think a lot of people just missed it. A lot of friends like oh, I sold like 50% of my portfolio doing the April like tariff, like other things. I never bought it back. Then I missed all the rally. So there's a risk upside as well. So just be careful. I think there's like just staying long term is a good strategy, but also if you want to manage risk, you got to be really smart, I guess. So, okay, so I think those are the next questions.

Speaker 1:

Some of these companies are trading at 10X price to sales. Is that not a concern? How do you decipher who's going to win relative to extreme variations? Yeah, so if someone is reading like 10xps, so that's something I think like really like I'm not going to talk about each company. As I said, there's like forward looking is only like one or two years, right, so you have to look at like longer term.

Speaker 1:

Then a company is like you have to really think about the how the analyst usually, when you look at like I think like internet or like just like either industry analyst or macro analyst or economist tend to be very cautious.

Speaker 1:

I think like when some technology breakthrough happened, just happened during the internet era right. So you have a lot of cautious, even like today. I think, like people talking about, oh, inflation could be a very like like a trigger recession or stagflation, trigger recession or stagflation. Well, I think in the short-term period, those inflation can be like the macro topic, can really drive the sentiment around, but just like long-term, you see, technology is actually adding a lot of productivity and usually the real productivity add is more than the economists or analysts forecasted and that, if you have a longer horizon, that really has changed a lot of the GDP or assumptions or the revenue growth assumptions for a lot of companies, revenue growth assumptions for a lot of companies. So dynamics, I think, like in shorthand, those macro and variations and all those things matters. But in the long term you have a long horizon which I think I recommend it for type of investment like this. You should have a very long horizon to really navigating through all the noises and all those kind of like corrections and disruptions along the way.

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Michael A. Gayed, CFA

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