Applovin CEO: The "Darkest Hour" of a 92% Stock Price Plunge and "Self-Redemption"
Today, AppLovin is one of the most valuable tech companies in the U.S., with an estimated $6 billion in cash this year and annual ad spending on its advertising platform reaching $20 billion. But few know that less than three years ago, the company's stock price plummeted 92% from its peak.
Recently, at the 2026 All-In Summit, AppLovin founder and CEO Adam Foroughi recounted this history for the first time in a systematic way—from the IPO collapse to the AI transformation, and then to the complete path of "turning the tide" through buybacks.
In the conversation, Foroughi stated frankly: "Advertising is ML 1.0, the first commercial realization of all the technologies driving AI today." AppLovin has followed this technological curve, completing the leap from mobile game advertising to e-commerce shopping intent creation.
An advertising empire "hidden in 100 million games"
AppLovin is not a household name. Foroughi himself admits, "That stupid name didn't help much."
However, its scale should not be underestimated.
In the conversation, Foroughi explained that AppLovin is essentially a mobile game advertising company—helping game developers monetize their traffic. He provided several figures:
- More than 1 billion people around the world play mobile casual games every day.
- In early 2024, AppLovin's annual advertising spending on its own platform reached $11 billion , and has since grown at an annual rate of approximately 60%, roughly estimated to be close to $20 billion today.
- He estimated the market size of the entire mobile game advertising ecosystem to be approximately $50 billion.
“Not long ago, social media advertising was a $50 billion opportunity,” Foroughi said. “That space is growing rapidly.”
More importantly, AppLovin's EBITDA margin is currently 84% , ranking first among its peers.
Darkest hour: Earning 1 billion annually, yet its market value has dwindled to only 3.8 billion.
The current state of this company is in stark contrast to its situation three years ago.
In April 2021, AppLovin went public with a market capitalization of approximately $28 billion, which once surged to $40 billion.
Then, it collapsed.
“In 2022, the stock price was falling almost every day,” Foroughi recalled. “We eventually fell to a market capitalization of $3.8 billion.”
That year, the company's EBITDA was $1 billion . Its valuation multiple plummeted from its peak at the time of its IPO to less than four times EBITDA.
He explained the crash as follows: "Your pricing in the market depends on the quality of your investors."
With the IPO boom of 2021, blue-chip investors simply didn't have time to research a company with an odd name. Early private equity shareholders and employees were eager to cash out, leading to supply exceeding demand and a sharp drop in stock price.
During that time, Foroughi received calls from family and friends. “They asked me, ‘Are you thinking about suicide?’” he said. “I said, ‘We started with a penny, and the stock price is still $10, and it’s gone up a lot.’ But as CEO, you quickly realize that your team is also receiving the same calls—and they don’t have your confidence or your shareholding.”
Self-redemption: Stop the roadshow, buy yourself back
Faced with market rejection, Foroughi made an unusual decision.
“I told the team that I wasn’t going to meet with investors anymore. They weren’t buying our stock, so meeting with them was a waste of time. But we had a lot of cash—so we bought back our own stock and became our own best investors.”
AppLovin then launched a large-scale buyback program.
The result was a cumulative buyback of approximately $6 billion , resulting in the cancellation of about 20%-25% of the outstanding shares. At its peak, these shares were worth over $50 billion .
At the same time, the company implemented a performance-based stock plan that covered core employees, not just the CEO. Foroughi's logic was: "We know it's tough right now. You thought you owned a house, and now you don't. But if you hold on, and we bounce back, you'll make a lot of money."
What supports his judgment is a key technological upgrade.
In April 2023, AppLovin upgraded its advertising algorithm from a regression model (ML 1.0) to a deep learning model (ML 2.0). The results were immediate—advertisers saw a significant increase in ROI, and the platform experienced explosive growth.
However, the company has still not made any public statement.
It wasn't until September 2023 that Foroughi met with investors in New York for the first time. By then, the stock price had rebounded from its low to around $80.
That week, the stock price rose from $80 to $150. The market capitalization increased from $28 billion to $55 billion.
"Just because I went to New York and told everyone: Our company is still here, we survived."
Advertising is essentially "ML 1.0": How to understand its technical logic?
Foroughi has a clear articulation of AppLovin's technical positioning.
Advertising is ML 1.0. It was the earliest commercial implementation of all these technologies, which are now driving AI.
He distinguished between two advertising logics:
Search advertising (bottom of the funnel) : Users already know what they want to buy, so they search on Google to complete the transaction. For this type of demand, large language models are directly replacing Google.
Discovery advertising (top of the funnel) : Users don't know what they want; ads create demand. "You show a recommendation and they say, 'Wow, this looks great, I'm going to buy it'—that's what drives Meta's advertising business, and that's what we want to do."
He believes that discovery advertising creates real economic growth, while search advertising merely accelerates a transaction that would have happened anyway.
He is cautious about whether AI agents will disrupt the advertising industry:
Some people use agents to optimize regular spending habits, such as automatically renewing monthly nutritional supplement subscriptions. But discovery platforms don't operate on this logic. The average shopper isn't the type to spend all their time on Twitter following the latest tech trends.
Our audience is more like the readers of The New York Times. And today, a large number of people still use Yahoo products every day.
Why can small companies outperform Meta and Google?
AppLovin boasts an EBITDA margin of 84%, a record it has maintained for many years. Faced with advertising giants like Meta and Google, both possessing top-tier engineers, why hasn't it been defeated?
Foroughi's answer was simple:
We never considered ourselves winners. Every morning we woke up feeling like the day was going to end badly, so we had to work like crazy.
His competitive logic is: focus, simplicity, and rapid iteration .
If you stay focused and streamlined, you can outrun the giants.
Regarding the concern that "high profit margins might be eliminated by competition," his explanation was:
These technologies are extremely complex. If you can continuously innovate and possess differentiated data, you can build a moat. Like Anthropic, it shouldn't theoretically be running so fast in the field of large language models—but when a model achieves economies of scale and is widely adopted, it forms a barrier that is difficult for others to overcome.
He also mentioned that AppLovin has an engineering team in Beijing, China. "Chinese people are very hardworking and very smart. Being able to work with them is one of the company's strengths. I often feel like the dumbest person in the meeting room when I'm sitting there—which actually makes me very excited to come to work every day."
Full interview transcript:
Adam Foroughi, CEO of AppLovin: Surviving a 92% stock price pullback, advertising as ML 1.0, and the $50 billion game advertising market.
September 21, 2026 · All-In Summit 2026Chapter 1: Adam Foroughi Joins the Besties!
Host: Adam is probably one of the most brilliant yet little-known founders. There's an advertising platform hidden within 100,000 mobile games, quietly surpassing Facebook Ads to become the preferred choice for e-commerce brands. Among over a thousand IPOs, AppLovin has the highest market capitalization. The founder's mindset must be one of winning. They'll likely generate around $6 billion in cash flow this year. In an unreasonable world, people will think you're cheating instead of realizing you've actually built one of the coolest technologies in the world. Welcome Adam Foroughi!
Host: Adam, thank you for being here. We think it will be very interesting to talk to you because you don't appear in the media headlines much, and the way you run your company is almost completely independent of the media—you don't give many interviews and don't talk about the company publicly. But it's an extremely successful company. Could you tell us what AppLovin does and give us a general overview of the market landscape?
Adam Foroughi: Absolutely. I think the reason we've been able to grow this big without early-stage venture capital is precisely because we've had to work hard and keep a low profile. Of course, the somewhat quirky company name hasn't helped much either.
We are essentially an advertising company that specializes in helping mobile game developers monetize their games in this field. Many people don't realize how huge the mobile gaming world has become—more than a billion people play casual mobile games every day, and these people are mostly adults and homemakers. The market opportunity is unimaginable.
We disclosed in January of last year, almost two years ago, that we had $11 billion in advertising spending annually on our own platform alone. Since then, we have maintained a year-on-year growth rate of about 60%, and roughly estimated, that figure is now close to $20 billion.
And we're not the only players in this market; many other advertising companies are also monetizing in this area. Taken together, the entire mobile gaming ecosystem attracts approximately $50 billion in advertising spending annually.
Not long ago, the social media advertising market was only $50 billion. This sector is growing rapidly, and audiences are actively watching ads, often choosing to watch them for rewards, a mechanism that creates the possibility of "intention generation."
For much of our company's history, we've been creating intent in this way—allowing users to naturally transition from one game to the next. What truly excites investors, and ourselves, is that deep learning models are now so powerful that we can leverage the same space to guide these adult users into consumer shopping scenarios. This allows us to enter a larger economic arena and create greater economic value. This is why our team is so passionate about what we're doing.Chapter 2: Discovery Ads vs. Search Ads, and Is Your Phone Really Listening to You?
Host: The first wave of internet advertising ignited numerous key technologies in many ways, which subsequently spread worldwide. For example, Google achieved this through AdWords, AdSense, and applied semantics. Is the same thing happening with this generation of internet advertising? Are any fundamental technologies with profound implications for the entire internet emerging here?
Adam Foroughi: Yes. Advertising can be considered ML 1.0—the earliest implementation of all these technologies that drive AI today. Large language models create far more economic value in society today than advertising, but advertising is a very lucrative application of deep learning models.
Recommender systems differ structurally from large language models, but in many ways they follow the same developmental trajectory. Much research in large language models can be transferred to recommender systems, and vice versa. Many scholars today who are engaged in research on large language models may have started their careers researching advertising systems. These two fields are deeply intertwined.
The advantage of advertising, and any advertising business, is that when you build a model, you are predicting a future outcome—it could be an ad, a recommended post on a social network, or a series of content—and you can immediately monetize the value of that prediction.
Host: Compared to 2006, is there a general pattern in how people react to advertising in 2026? Is there a predictable evolutionary trajectory?
Adam Foroughi: That's interesting. I got into this industry in 2005, and back then, advertising was a complete mess—it was all spam, and the technology was utterly inadequate. Then Facebook did something really smart—it realized that by combining all the data it had with excellent technology, advertising could become incredibly precise. Today, if you ask most shoppers, most of their shopping inspiration comes from Instagram. Advertising has become very much like the content itself.
The same applies to our field; people love the ads we show. You might think people wouldn't, but we've seen a lot of interaction with mini-game ads—these ads appear in other games, and people actively try out these previews because technology has become powerful enough to recommend truly relevant content to everyone.
Host: There are many concerns about the impact of AI on advertising networks, especially regarding Google. OpenAI now has advertising products, and I'm sure you've been closely following and learning from them. What will advertising look like when people start using chatbots for five or six rounds of queries? Clearly, 95% of users won't pay $20 a month for this technology; they'll expect it to be free. ChatGPT has already said it will be free. Could you talk about their advertising strategy? Will this lead to lower individual ad effectiveness but increased overall usage, or will it be more effective than Google Search's advertising model?
Adam Foroughi: Advertising has two dimensions. One is the bottom of the funnel—consumers generally know what they want to buy, but they're doing research to complete the transaction; this is Google's search business. If I wanted to buy a pair of leather shoes, in the past I would Google search, do some research, and then ads would guide me to where I needed to go. Today, you can complete the same closed loop using large language models. So this advertising model will directly compete with Google's search business.
Our field involves showing ads to users without any explicit intent. What we do is create something that wasn't there before—showing them a recommendation that makes them think, "Wow, this looks great, I'm going to buy one." This is the underlying logic driving Facebook's advertising business.
Transactions facilitated by search or large language models would have happened anyway—even if Google ads had never existed, the transaction would still have occurred as long as search existed, just via a different path. Therefore, there isn't much room for economic growth along this route.
But when you show a consumer an ad for a product they had no idea existed or that they needed—that's pure discovery, a complete discovery experience. That's what makes Meta Advertising so powerful, and that's what we're striving for. You create that "moment of discovery," which is not only a pleasant experience for the consumer—they're excited about what they've bought, waiting for the package to arrive, eagerly unpacking it—but you also create real economic growth.
Host: What about the arms race issue? Some people say they casually mentioned something at a dinner with friends, and later saw related ads on Meta or elsewhere. Are we overreacting? Is this really happening? Could the urge to sell more things be making advertising increasingly intrusive?
Host: Yes, it feels really weird whenever this happens. So what actually happens—I say something, and then an ad pops up?
Adam Foroughi: I think you definitely did some other traceable actions, like doing searches, browsing a website, or searching for products without realizing it, and then you talked about related topics and started seeing related ads. It wasn't that your microphone was on, or that an app was actually eavesdropping or anything like that.
Host: But one theory is that if several of us are having dinner together, these apps know our locations and can group us together. For example, we might all be talking about wanting to buy a certain car or a certain watch, and then Friedberg searches for that watch on his phone to add it to his collection before leaving. If the system tracks the locations of all of us, it could then push ads for that watch to all four of us—is that the logic?
Adam Foroughi: I don't think advertising companies can track location information. We don't track location at all. Tracking people's precise location and then using it to target ads is an extremely complex process. Moreover, listening to microphones, analyzing their content, and then converting it into advertising instructions involves a massive amount of data that is simply impractical.
Host: What if a few of us are friends and connected to each other?
Adam Foroughi: We don't have that data. But if you're on social networks, your social relationships can certainly drive the ad experience. If a friend searches for something, you might see related content. There's nothing wrong with that.
Indeed, there is an unsettling "creepy factor" involved, but with so many companies running ads on such a large scale, all the data collected is largely controlled.
What people often overlook is that it is precisely because these ads have become so precise that they have created enormous economic value. The ad you see, the ad you can relate to—20 years ago, you wouldn't have paid any attention to it. Now, a significant portion of GDP comes from this digital advertising economy. The more advanced these technologies are, the faster GDP growth.Chapter 3: The IPO Crash and Becoming Your Own Best Investor
Host: Adam, I think the way your company operates is really interesting. Are you in Los Angeles right now?
Adam Foroughi: I'm in Los Angeles. The company was originally in Silicon Valley, but was founded in Palo Alto.
Host: Palo Alto. And you have many developers here in China, right?
Adam Foroughi: Our engineering departments are in Palo Alto, Beijing, and Singapore.
Host: You didn't raise a lot of venture capital, and the company went public in 2021 with a market value of about $20 billion?
Adam Foroughi: We went public in April 2021 through a joint IPO, which raised approximately $28 billion.
Host: 28 billion. And then by 2023, how much had the market value fallen to?
Adam Foroughi: There's something interesting about the public markets. When we went public in 2021, we had $600 million in EBITDA and a market capitalization of $28 billion, which peaked at $40 billion. But in 2022, the stock price was falling almost every day, eventually dropping to a market capitalization of about $3.8 billion. And that year, we achieved $1 billion in EBITDA.
Host: That's unbelievable. Wait a minute, let's break this down—the market isn't buying into this business for some reason, so what did you do?
Adam Foroughi: You'll soon realize, and I understand even better because of my finance background, that your stock price in the market depends on the quality of your shareholders. Our early shareholders included private equity investors, co-founders, and other team members who would choose to sell after the IPO. At the time, a large number of companies were going public, and blue-chip investors simply didn't have time to research what this oddly named company was all about. So we faced a situation of extremely low demand and extremely high supply, which caused the stock price to plummet. The valuation multiple fell from a high level—I wouldn't use 50 times EBITDA to value the company—to an absurdly low point of less than 4 times.
So, as someone with a financial mindset, when faced with such a crash, you must recognize that opportunities exist on the other side. I turned to my internal team and said: I'm not going to talk to investors anymore; they're not buying our stock, and talking to them is a waste of time. But we're generating a lot of cash flow, so let's use it to buy our own stock and become our own best investors. This led us to launch a very aggressive stock buyback program. Since then, we've bought back approximately $6 billion worth of company stock and cancelled about 20% to 25% of the outstanding shares. At the peak of the stock price, this $6 billion buyback was worth over $50 billion.
Therefore, that seemingly frustrating moment can be transformed into a huge opportunity.
Host: Have you always thought this way, or have you also had a very low period where you thought, "Oh my god, what's wrong with me?"
Host: Yes, that's exactly what I was going to ask—when the stock price drops by 92%, how do you maintain the company's internal culture?
Adam Foroughi: It was really tough. Family and friends kept calling to ask, "Are you okay? Are you feeling down?" I said, "Look, we started from a penny, and the stock price is still around $10. In absolute terms, it's still a lot higher." But as CEO, you immediately realize something very difficult: your team members are also receiving the same calls. And they don't have your composure, nor your equity stake.
So our approach was to cultivate a "we're against the world" mentality—everyone has abandoned us, but we're determined to continue buying back shares. We also launched a performance-based stock incentive plan. This kind of plan is usually only for the CEO, but we extended it to the company's core employees, telling them: We know things are tough right now; you thought you owned a house, but now you feel like you have nothing. But if you persevere, once we rebound, you will reap substantial rewards on the upside.
Later, when investors started to refocus on us, coinciding with our upgrade from ML 1.0 to ML 2.0—shifting from regression models to deep learning models—the results were remarkable. Our advertising algorithm drove the entire business; the better the algorithm, the higher the ROI for advertisers on our platform, all based on performance-based billing. This led to the company's rapid growth.
In April 2023, we launched a new model, but we still didn't communicate it publicly, so the outside world was unaware of it. Around September 2023, I went to New York, by which time the stock price had risen to about $80, and had recovered somewhat driven by performance. I said it was time to start talking to investors, because the market capitalization was high enough that we couldn't continue with such aggressive buybacks as before.
That week, the stock price jumped from $80 to $150, and the market capitalization more than doubled from about $28 billion to $55 billion—all because I went to New York.
Host: Just because you went to New York and said, "Hey, our company is still alive, we made it through"?
Adam Foroughi: Yes. I sit in those meetings and it's easy to see the other person's reaction—I'm very experienced at this. Those people are sitting there, clearly on the phone with someone outside saying, "Buy, buy, buy, buy." It's just so satisfying.
Host: And what about the reverse? Once they do a lot, don't they start asking, "Adam, how do we expand? How do we grow faster? Why only games? Why not e-commerce? Why not this or that?"
Adam Foroughi: Absolutely. It's a real dilemma; nothing you do seems right.
Most people aren't actually contrarian investors—the extremes of a market downturn are mirrored by the extremes of a market upturn. Our stock price rose from $9 to $750 in two and a half years, and our market capitalization grew from $3.8 billion to $250 billion. Both ends were extremes.
We've now returned to a relatively stable position and are full of expectations for growth opportunities. But I've found that there's no fundamental difference between investors in the public and private markets—they both chase trends, just often lagging behind. The best among them are able to capture these trends earlier than the market itself. This is why there's a gap between top VCs and average VCs, and also between top public market investors and average investors.Chapter 4: Privacy Regulations, Apple's Controls, and How AI Agents Are Changing People's Shopping Behavior
Host: Could you talk about privacy? Apple and the EU are indeed watching companies like yours, believing your data collection methods are too aggressive. Some game developers also don't want platforms collecting their user data, and are therefore gradually tightening restrictions. Zuckerberg directly addressed this issue back then. So how does this hinder your business? When Apple tries—frankly—to shake your business, how do you deal with privacy issues?
Adam Foroughi: In any of these kinds of areas, you want the regulations to be clear. Once the rules are clear, the technology can adapt. Five years ago, you could precisely target a user on iOS; today, if a user says, "I don't want to be precisely targeted," you put them in a group and serve them less targeted ads.
Interestingly, after Apple made this change, a large number of users complained, saying, "Show me more relevant ads; you're just showing me junk ads now." So privacy regulations are indeed necessary—they allow tech companies to act as intended—but on the other hand, consumers do need relevant ads to help them discover products.
You're in a game, watching a 30-second ad to exchange for a life; you're actually gaining something with monetary value. So, would you rather watch 30 seconds of junk ads or 30 seconds of content relevant to you? Since these privacy rules were implemented, tech companies have adapted, and deep learning networks have become incredibly powerful.
Host: We have a quick follow-up question—about game acquisitions. You've tried acquiring some games before, and we also have Bending Spoons with us today. They're actively acquiring businesses that aren't necessarily bad, but have relatively slow growth and aren't very attractive to venture capitalists. For you, is becoming a game studio a sustainable direction? Wouldn't that conflict with existing partners?
Adam Foroughi: We've sold all those games. The initial purchases were a data strategy decision—when we built our first deep learning model, we needed data to train it, and game studios were typically unwilling to share their data with third-party companies. So we bought the studios ourselves to fill in the training data for our first model, built a model that performed very well in the market, and the company began to grow rapidly. Once our third-party partnerships started coming in, we spun off those studios.
Host: In a world where AI agents are everywhere, what form will advertising take? The human-computer interaction interface may have changed; it will no longer be typing on a computer or browsing on a mobile phone, but may be Meta Glasses or other devices—what role will advertising play in "AI agent commerce"? So many people are working hard to promote the implementation of AI agent commerce.
Adam Foroughi: I think the reality is that a part of the world is indeed starting to use agents to optimize certain consistent shopping behaviors. For example, I might entrust my supplement subscription to an agent to automatically optimize and deliver it on time every month. But discovery advertising platforms are not like that, and the typical consumer is not the kind of person who deeply uses agents, is active on Twitter, and is always keeping up with the latest technology.
Our audience is more like the readers of The New York Times—there are still a large number of people using Yahoo products every day. The average consumer wants to find a product, experience the shopping process firsthand, compare prices, track logistics, and experience the entire transaction.
If you tell him afterwards, "Hey, the AI can actually do all this for you and save you 20%," I think for a $50 transaction, it doesn't matter at all—because going through the process yourself brings dopamine, which is what they enjoy.
So it's true that some tech-savvy people will adopt intelligent agents, but I think we overestimate the representativeness of the Twitter community and forget that ordinary consumers are not like that.Chapter 5: How Small Teams Beat Giants, Building Profit Moats, and Team Building in China
Host: Let me explain how you won—Meta and Alphabet/Google are the smartest companies in the world, with top-notch engineers, and most of their revenue comes from advertising. They've built their own models and been doing it for a decade or two. How does a small company compete and succeed in this specific field? And what is the operating model that supports your continued success?
Adam Foroughi: Here’s something that has helped us get to where we are today—we never felt like we’d won. Every morning we woke up feeling like something bad was going to happen, so we had to work like crazy. This created a small company with a lot of real domain experts who were deeply involved in this field, highly focused on the mobile gaming experience and how to translate that into consumer behavior on the other end.
I believe that if you are focused enough and stay small, you can move faster than the giants. That's the power to challenge the giants.
Host: So where are the "loopholes" in their business? I'm talking about looking at a profit and loss statement, like when I analyzed Amazon ten years ago—we found loopholes everywhere. The later insight was that Amazon would absorb these loopholes and turn them into new business lines. This is our long-term logic for being bullish on Amazon. For you, where are the loopholes? Is it the payment infrastructure, or something else? Or to put it another way, where is the room for profit margin expansion that gives people reason to buy into this story?
Adam Foroughi: I believe our EBITDA margin is number one in the market, at 84%. So I'm not sure how many "leaks" we still have.
Host: Given these figures, it's indeed difficult to say there's any omission—but let's look at it from another angle: advertisers come to our platform because their business model is transaction-based. For example, they're selling lipstick, and we provide them with an arbitrage opportunity—they "buy" consumers from us, and once that consumer completes the transaction, their customer acquisition cost is immediately covered. A consumer spends $20 on the lipstick, but they pay us less than $20 minus the cost of the product, so they're satisfied and keep increasing their investment. This performance model is highly replicable.
Our "loophole" lies in the fact that we are not the entire chain. We are not the advertisers themselves; what we want to do is empower advertisers to reach consumers. We operate with an extremely lean approach, highly focused on algorithms and automation, so there are very few loopholes.
Host: The other side of the story is that when you have an 85% EBIT margin, people say, "This company might be over-profiting," and then competitors say, "I can wipe out Adam's margin; I'm willing to do it at 60% or 50%." But—and perhaps this is an extension of David's question—this doesn't actually happen; the margins remain quite stable. Why is that?
Adam Foroughi: Because these technologies are so complex, if you keep innovating and have differentiated data, you can build a real advantage. Using a similar logic, Anthropic shouldn't have been leading the way in the large language model field, but once a model reaches a certain scale and is widely adopted by a large community of users, it forms a moat that is difficult for others to overcome.
Host: Tell us about the Chinese team, what are their advantages?
Adam Foroughi: Chinese people are very humble, very, very hardworking, and very intelligent. Whether you're working with Chinese engineers in China, in the US, or elsewhere in the world, you're working with some of the smartest people in the world.
When I started my business, one of my goals was to work with great people and figure things out together. Now, whenever I sit among my team members, I know I'm probably the dumbest person in the room—and that motivates me to come to work every day.
Host: Honestly, how do you feel after hearing this?
Adam Foroughi: It works very well for me.
Host: Okay, let's give Adam a round of applause! Thank you, Adam.
Adam Foroughi: Thanks, guys, it's great to know you guys.
Risk Warning and DisclaimerInvesting involves risk; please exercise caution. This article does not constitute personal investment advice and does not take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article are suitable for their specific circumstances. Any investment decisions made based on this information are at your own risk.