Top Stocks I'm Buying To Get Rich Without Getting Lucky

If you put $10,000 into Apple stock at the start of the smartphone era, you'd have over $750,000 today. If you invested it in Nvidia when Chat GPT came out, you'd already have over 130 grand. My name is Alex and I spent 8 years as an electrical engineer and AI researcher at MIT, which helped me find great stocks like Nvidia, TSMC, and Micron years before the rest of the market. So, let me show you my top 10 stocks to get rich without getting lucky. Your time is valuable, so let's get right into it. Late last year, I made a video on my top 10 stocks for 2026. But this channel has grown by over a 100,000 subscribers since then, and I get a lot of questions about which stocks I'm buying today. So, now that quarter 3 is over, I figured it's a good time to get everyone on the same page. I'm also not here to waste your time. So, here's the full list of stocks up front, how they're performing so far this year, and their returns versus the S&P 500, since the whole point is to get rich without getting lucky. And that's exactly what's going on right now. If you split your money evenly across this list, you'd be up 35% year-to date, around 2.5 times the S&P 500. It's not just about picking individual stocks. I always make lists that work together to be more than the sum of their parts, which I'll explain as we go. But accountability is important, which is why I have a few simple rules for this list. Once I pick the stocks, they're locked in for the entire year. That way, if I pick a bunch of losers, I can't just take them off the list and pretend it never happened. I also can't add any winners after they've already gone up. Every stock stays on the list for the whole year and I can only change their order based on new information. I'll show you the new order at the end of the video. I should also mention that I'm not a financial adviser. My background in engineering and AI help me understand the science behind the stocks, not just their financials. But why these stocks specifically? And are they still good investments today? Well, let's jump right into the list. I've been investing for over 15 years now, and the longer I invest, the more I realize that every great portfolio starts with a fund. When I add money to my portfolio, I usually keep it in an ETF instead of leaving it in cash. Most investors choose a fund that tracks the S&P 500, like SPY. But if you've been watching this channel for a while, you know it's actually pretty simple to outperform the S&P 500. For example, the NASDAQ 100 outperforms it over every single time frame, but it has some issues that might make it the wrong foundation for a portfolio focused on the AI era. First, the NASDAQ holds a lot of stocks that don't fit the AI theme at all, like Walmart, Costco, T-Mobile, and Pepsi. And second, they recently changed the rules to let the biggest IPOs into the NASDAQ 100 just 15 trading days after going public, while the old weight was 3 months. SpaceX joined the index on July 7th, and it's already one of the top 10 holdings, even though it lost $541 million last quarter. Anthropic, the AI lab behind Claude, is reportedly going public on the NASDAQ exchange in November with a valuation of up to $2 trillion, putting it on the same fast track for inclusion in the index. Reports claim that Anthropic had over $8 billion in operating losses last year. Just to be clear, I'm not saying SpaceX or Anthropic are bad companies. I'm saying that them sitting near the top of the index while making little to no profit introduces a lot of risk to where I park my cash. That's why I moved my money into a fund that lets me have my cake and eat it too. Vanguard's information technology ETF, ticker symbol VGT. VGT holds over 300 US tech companies, right between the NASDAQ 100 and the S&P 500 in terms of diversification. It also isn't afraid to let its winners ride. Just Nvidia, Apple, and Microsoft make up around 45% of the fund with other great companies like Broadcom, Micron, AMD, Palanteer, and Wham Research all in the top 10. On top of that, over 80% of the fund focuses on hardware, semiconductors, system software, and applications while skipping companies like Walmart, Pepsi, and SpaceX, which is currently classified as a communication services company. and it even has lower fees than SPY or Triple Q. So, I'm saving money while outperforming both indexes. VGT is up 35% year-to- date compared to 23% for the Triple Q's and 14% for SPY. That's why VGT is the foundation of my list of stocks to get rich without getting lucky. By the way, AI is moving fast, so it's important to have investing tools that you can actually trust. That's why I use Seeking Alpha, the sponsor of this video. Their community of over 250,000 investors means I always get the bull and bear thesis on any stock instead of one biased opinion. That really helps me deep dive companies and make much more informed investing decisions. But if you want to take your portfolio to the next level, Alpha Pix has you covered. Each month, their quant system and analysis team pick two strong buy stocks based on strict systematic rules. For example, Micron was the quant systems highest rated semiconductor stock last October, even though it already more than doubled that year. The team picked it not just for AI, but as a diversified memory play across automotive, industrial, and mobile. Micron stock is up over 400% since. You also get portfolio updates, exclusive analyses, and webinar replays where their lead analyst, Steven Crest, explains exactly why each stock was chosen. But what really sets Alpha Pix apart for me is how they manage risk. Not just when to buy, but when to exit. Automated sell alerts if a company's fundamentals shift. Rebalancing if a stock hits 15% of the portfolio. And when a stock doubles, it only sells half and the profits keep growing. Everything I do in my own portfolio. And the results speak for themselves. The Alpha Pix portfolio is up by almost 350% since it launched in 2022 versus 103% for the S&P 500. So, if you want to build a best-in-class portfolio with a datadriven strategy, you can get started with Alpha Pick with my link below today. All right, surprising no one, the top stock on my list is Nvidia since they're at the heart of the entire AI revolution. They make the chips that most AI models train on, and they have the CUDA software ecosystem that no other company can compete with. But here's something that might surprise you. Nvidia stock is currently trading at about 19 times forward earnings. That's the lowest forward PE ratio out of the entire Magnificent 7. Set another way, investors are paying less for each dollar of profit that Wall Street expects Nvidia to make next year than for Apple or Microsoft. Even though Nvidia is growing several times faster, one reason the stock is so cheap is that Wall Street analysts keep saying the same thing every quarter, the biggest company on Earth can't keep growing at this pace. And that's true. Nvidia hasn't been growing at a steady pace at all. It's actually been accelerating. The revenues grew by 62%, 73%, 85%, and then 106% over the last four quarters. And these analysts keep making the same mistake. In August, Nvidia guided for around 70% growth next fiscal year, while Wall Street analysts expected about 45%. As a result, the stock added $442 billion to its market cap in a single day, the second biggest 1-day gain in stock market history. Like I've been saying for years now, Nvidia won't get disrupted by another GPU maker. Their hardware and software ecosystems are simply too entrenched. It'll take a fundamentally different kind of processor to chip away at their customer base one workload at a time. That's why Broadcom and Google are also very high on my list. Specifically, Nvidia's biggest customers don't want to rely on them forever. They want specialized chips for the workloads that they actually run billions of times every day. The battle between generalpurpose GPUs and custom chips optimized for specific applications is the single most important thing for AI investors to keep watching. Google has their own AI chip called the tensor processing unit or TPU. Today, Google owns more AI compute power than any other company on Earth. By one estimate, they own around a quarter of the world's total, mostly running on their own TPUs. They also own their entire stack, the chips, the data centers, the cloud, their own Gemini models, and the products and services built on top of them that are used by billions of people every month. Google Cloud is now making almost a hundred billion a year in revenue. They have a backlog of over half a trillion dollars and it's growing by 82% year-over-year, around twice as fast as Amazon Web Services and Microsoft Azure. On top of that, Google recently started selling their TPUs to outside customers, and they're renting up to a million of them directly to Anthropic. Think about how confident you have to be to rent out a million of your best AI chips to the company building the biggest competitor to your own AI models. Google is so far ahead with their full stack strategy that they can arm their own rivals and still come out on top. As a longtime Google shareholder, this is why I don't mind them raising their capex budget to $200 billion and going free cash flow negative last quarter. They understand that the AI race takes time and money to win, and they're aggressively investing both. But while Google mostly builds custom chips for themselves, Broadcom builds them for everybody else, including Google, Meta, OpenAI, and Anthropic. That makes Broadcom one of Nvidia's biggest direct competitors. Broadcom's AI chip revenue hit 16.7 billion last quarter, which is up a whopping $221% year-over-year, and they're expecting about $115 billion in AI chip revenue next fiscal year, and $230 billion the year after that. Broadcom also says that Anthropic is on track to become one of their biggest custom chip customers in 2027. So whether the market shifts towards Nvidia's GPUs, Google's TPUs, or custom chips made by Broadcom, I win because I hold all three. And all three of these companies have two things in common. First, their chips are actually built by Taiwan Semiconductor Manufacturing Company, ticker symbol TSM. TSMC builds about 90% of the world's most advanced chips and accounts for 72% of all contract chipm revenues. That's because they're the only company that can make advanced chips for every side of the chip war at scale. GPUs for Nvidia and AMD. Smartphone processors for Apple and Qualcomm. Custom AI chips for Amazon and Google and Microsoft. TSMC is so far ahead of every other foundry that they can set the price and customers have to pay. There's just nowhere else for them to go. Last quarter, their revenues were up by 51% year-over-year. And TSMC is reportedly raising their prices by up to 10% next year as well. Another thing all these companies have in common is relying on other companies for memory. AI chips are only as fast as the memory that supports them. And high bandwidth memory is one of the biggest bottlenecks of the entire AI buildout today. Almost all high bandwidth memory on Earth is made by just three companies. And out of those, Micron is the only one based in the United States. Micron already has contracts reserving most of their high bandwidth memory through 2027 at much higher prices and they expect the memory shortage to get even worse in 2027 and 2028 as demand for AI keeps increasing. That's why AI companies are signing multi-year contracts and prepaying for memory chips that aren't even built yet. Micron has $32 billion in customer commitments, most of which are cash deposits. And Nvidia more than doubled their own supply commitments to $279 billion last quarter alone, mainly to lock in memory. Like I've been saying for a couple years now, memory is no longer a cyclical commodity. Last quarter, Micron's revenue hit 54 billion, almost a 5x yearover-year with 87% gross margins. And even though Micron is worth over a trillion dollars today, it still trades at just six times forward earnings. So while Wall Street analysts argue over which chip is faster, TSMC and Micron get paid either way. That's another example of how all the stocks on my list work together. And if you feel I've earned it so far, consider hitting the like button and subscribing to the channel. That really helps and it lets me know to make more updates like this. Thanks. Now, let's keep moving down my list. Every AI data center also needs power and cooling. A single NVIDIA rack takes around 120 kW to run today, which is over 10 times more than a traditional server rack. The Vera Rubin racks that are currently shipping take around 200 kW of power, and requirements keep going up with each generation. The thing is, the old way of wiring data centers simply can't carry that much current. A single 1 megawatt rack would need up to 440 lbs of copper to make it work. That's one reason that Nvidia partnered with companies like Verdiv, ticker symbol VRT, to redesign the entire power architecture from the ground up. This redesign moves data centers to 800 volts of DC power, the same standard that Nvidia will use to support 1 megawatt racks. But power is only half the problem. A rack that draws 600 kW builds up a ton of heat, way more than traditional air cooling can handle. These racks need direct to chip liquid cooling, and Verdive builds that, too. Every gigawatt scale AI factory being built today needs what they're selling, and their latest guidance shows it. Verdive raised its sales forecast to about $14 billion this year, and they expect year-over-year sales growth to speed up from 18% in quarter 2 to about 35% in quarter 3. Verdiv is also acquiring a company called Utility Innovation for up to $2.6 billion. This company designs micro grids, on-site power systems that tie a data centers generators and batteries together, plus the software and switch gear to control them. That lets new data centers get power much faster than waiting on the grid. And it extends what Vertive sells from the power source all the way to the chip. But before anyone can even order Vertive systems, they need grid connected power in the first place. And that's where IN comes in. Iron has over 5 gawatts of secured power across the US and Canada, Spain, and Australia. And they're using it for AI data centers. Nvidia itself has a 5-year, $3.4 billion cloud contract with Iron. And they also took a warrant to buy 30 million iron shares at $70 per share. Iron stock currently trades at $35 per share, which implies around a 100% upside just to hit Nvidia's strike price. Microsoft also signed a 5-year $9.7 billion deal for Iron's capacity and prepaid 20% of it upfront. And in July, Iron signed another $2.8 billion worth of contracts, and its customers now include Perplexity and Figure AI. In fact, Iron's $4 billion run rate target for this year is now fully under contract, and it still only uses about 10% of the power that they've already secured. That means they'll be able to support around 10 times that number once all their AI infrastructure is built out up and running. That's a big reason this stock is so volatile. Building data centers costs money that IN doesn't have yet. So, they have to keep raising capital to close that gap. What makes Iron special though is they have the most secured power for their size by far, which is exactly why I own it. All right, so far we've covered my top socks for AI chips and the infrastructure built around them. But software sits on top of that infrastructure, which is why I saved it for last. Let's start with Meta Platforms. Meta currently trades at around 22 times forward earnings, which is the second lowest multiple in the entire Magnificent 7, only behind Nvidia. It's cheap because Meta is spending between 130 and $145 billion in capex this year alone, which is close to double what they spent in 2025. But here's the thing, their family of apps have over 3.6 billion daily active users across Facebook, Instagram, Messenger, and WhatsApp. So, of course, they need to spend aggressively on AI infrastructure if they want to serve over four out of every 10 people on the planet. And while Wall Street analysts see Meta spending as a risk, they're already proving that it's worth it. Ad impressions are up by 14%, the average price per ad is up by 12%. And their revenues are up by 28% all yearover-year. And just last month, Meta launched Muse, a personal AI agent that can shop, book travel, and even negotiate on your behalf. Muse hit number one on the app store in less than two weeks and Meta stock jumped 27% over that month. That's why I'll keep dollar cost averaging into this global growth machine. And we can't talk about growth machines without talking about Palunteer, which has been on my list for 3 years in a row. Palanteer's revenue grew by 93% year-over-year, and they raised their fullear guidance to $8.15 billion, which implies 82% growth. They also guided for over $3.4 billion in US commercial revenue, which would be 134% growth for that segment. That makes Palanteer one of the only profitable pureplay AI software companies on the market. And they're almost doubling in size year-over-year with 55% net margins. And I expect that growth to continue because the global artificial intelligence market is expected to more than 11x in size over the next 9 years, which would be over a 30% compound annual growth rate from now through 2035. That's about twice the growth rate of the S&P 500 for 9 years straight. And Palanteer is positioned to take a meaningful slice of that growth with its AI software platforms. And we can't talk about software without also talking about security. Every dollar spent on AI infrastructure, on models, software, and services is a dollar that's at risk from new kinds of cyber attacks. That means cyber security isn't optional. It's the cost of doing business today. That's why I've been buying Crowdstrike stock for the last few years now. Ticker symbol CRWD. The big reason I like Crowdstrike is their Falcon Cloud platform, which has three key parts. It has a library of cloud-based modules for things like anti virus scans, firewall management, and protecting against malware. They also have a proprietary threat graph that tracks the connections between people, their devices, and the networks they have access to. Kind of like Palunteer's ontologies, but specifically for enterprise networks. Then they can compare actual network traffic against that graph and deal with any differences as they come up. Crowdstrike's threat graph now processes over a trillion security events every day. And they get that data with their Falcon agent, a tiny piece of software that runs on every device to send data back to CrowdStrike so they know when to run those different cloud modules and update their threat graph. The global cloud security market is expected to triple in size over the next 6 years and that's before accounting for AI enabled cyber threats. Those threats are already here. In July, OpenAI reported that their own AI models broke out of a test environment and hacked into HuggingFace, which is a major online platform for AI developers. Hugging Face said it was the first attack they ever handled that was driven entirely by an autonomous AI system. One month later, Crowdstrike reported record new recurring revenues, up 51% year-over-year, and the stock had its single best day ever. And I expect the cyber security industry to grow even faster than that with CrowdStrike in a great position to capture a lot of that growth. So here's my updated list of top stocks to get rich in 2026 without getting lucky. After 9 months, I still feel great about the stocks and their performance. So I'm only making two slight changes to the order. First, TSMC moves up just one spot. So it trades places with Broadcom. Broadcom's AI revenue is still growing over 200% year-over-year, but Google recently signed a custom chip deal with one of their biggest rivals, Marll. Chip designers can compete. The company that builds everyone's chips doesn't have to. And second, I'm moving Iron to the bottom of the list, which bumps Palanteer and Crowd Strike up one spot each since both of them just recorded record quarters while Iron is still riding off old Bitcoin mining hardware. That doesn't make I a bad company or a bad investment. I just want to keep this list in order of execution risk. So, now that we're in the final quarter of 2026, let me know what you think of this list down below. Or if you want me to make a deep dive video on any one of these stocks. And if you want to see even more stocks that I'm buying to get rich without getting lucky, check out this video next. Either way, thanks for watching and until next time, this is Tickerol U. My name is Alex, reminding you that the best investment you can make is in you.