An All-Time High in “WHAT THE…?” By Michael Salvatore, Editor, TradeSmith Daily In This Digest: - An epic spike in fearful headlines…
- This week’s close is critical…
- Seasonality puts us near all-time highs by June…
- This under-the-radar AI play is just at the starting line…
- Expect fireworks from Jensen Huang tomorrow…
The Economic Policy Uncertainty Index just hit an all-time high… In October 2015, a bunch of economists from the National Bureau of Economic Research got together and decided to build a new kind of index for measuring not only fear in the stock market, but also fear about the overall economy. They created the Economic Policy Uncertainty Index, which works like this: Our modern monthly EPU index for the U.S. relies on 10 leading newspapers: USA Today, Miami Herald, Chicago Tribune, Washington Post, Los Angeles Times, Boston Globe, San Francisco Chronicle, Dallas Morning News, New York Times, and Wall Street Journal.
We search the digital archives of each paper from January 1985 to obtain a monthly count of articles that contain the following triple: ‘uncertainty’ or ‘uncertain’; ‘economic’ or ‘economy’; and one of the following policy terms: ‘congress’, ‘deficit’, ‘Federal Reserve’, ‘legislation’, ‘regulation’ or ‘white house’ (including variants like ‘uncertainties’, ‘regulatory’ or ‘the Fed’). Source: Measuring Economic Policy Uncertainty whitepaper So what we have is essentially a new(ish) VIX, but instead of being based on trading activity, it’s based on how much the mainstream media is telling you to be “uncertain” (scared) about the economy. Here’s what the index looks like so far this century. You’ll note the significant spike off to the right: 
Mainstream media economic uncertainty is at an all-time high right now. Common sense tells us why. Nobody seems to know what to think about, or even how to keep up with, all the news about tariffs, DOGE, and other zoomed-out developments like the negotiations to end the Ukraine war. But I’m seeing a fatal problem with this index… | Recommended Link | | | | The CEO of Nvidia said Elon Musk’s new project is… “easily the fastest supercomputer on the planet.” And Eric Fry, the legend who picked 41 stocks that jumped 1,000%+ is now recommending shares of a company that has partnered with Elon Musk in this new project. Click here for details. |  | | And that’s the fact that the reporting on the index itself, by its very definition, may very well spur the index ever higher. Every article in the top 10 newspapers that mentions the Economic Policy Uncertainty index already hits two of the three required words. One of other words is virtually guaranteed, especially right now. That’s not to say there’s no value in the index. Overlaid on a chart of the S&P 500, the index has typically leaded market declines, but sometimes also lagged them. 
The point I want to make is that you can’t look at a data point in a vacuum… The index above has a fatal flaw in that any coverage about the index will make things seem more uncertain than they actually are. This data is not valueless. But we should confirm it with the price action. Let’s check in on the SPDR S&P 500 ETF (SPY): 
This is a weekly chart with daily moving averages and RSI. We can see that SPY came up to kiss the 200-day moving average in this week’s trading (Monday, to be specific.) It’s since rejected from that level and traded lower. Bulls are finding it hard to buy stocks above the 200 DMA right now. But they’re also finding it hard to sell below the black dashed trendline, which acts as rising support/resistance going all the way back to the bottom of the 2022 bear market. We’ve also yet to pierce key support (the green dashed line) going back to the spring selloff in 2024 and established as former resistance in August 2023. Finally, SPY’s Relative Strength Index (RSI) is giving a buy signal (purple shading below). It’s risen out of oversold and crossed above its short-term moving average. That’s been a sturdy buy signal for the past nine months: 
If you bought SPY every time the RSI crossed above the yellow line and stayed above it for several days, and sold every time it crossed below, you would’ve made good money. This all tells me that the most likely direction for stocks is more up than down. We’ll probably see some chop going forward as investors digest the fear. But if the monthly close for SPY is above the 200 DMA around $571, then we’re likely to continue rising through April. And don’t forget about seasonality… Post-election year seasonality lines up well with this thinking, as you see in the chart below from Trade Cycles. For the past eight post-election year cycles, SPY has gone up 100% of the time from mid-April to mid-July, with an average return of 7.6% for the period: 
If seasonality plays out like that here in 2025, that would be enough to put stocks back near all-time highs by the summer. Will we see exactly that? Probably not. But seasonality data is a good blueprint for what to expect throughout the year. It’s done fairly well so far in 2025. And we’ll keep updating you on what it’s telling us here in TradeSmith Daily. Switching gears, Andy and Landon Swan have a unique insight on the AI trade… The AI industry has lots of picks-and-shovels companies. They’re the ones that keep the industry going by providing basic goods and services that fuel the trend. The term hearkens back to the Gold Rush, when shovel makers became rich off the backs of fortune seekers buying the tools needed to profit from the trend. For the AI megatrend, you have processing power in the form of computer chips. You have data centers and cloud storage. And you have energy from utilities companies as well as water management for cooling. But there’s a kind of blind spot picks-and-shovels play in the AI trade that’s apparent once you learn about it. It’s the data itself. AI is nothing without a high-quality, well-organized dataset. The better the stuff you train an AI with, the better your results are going to be. Thinking on this, brothers Andy and Landon Swan – cofounders of LikeFolio – have dug up an awesome play on data organization that’s flying under the radar. Here’s what they have to say about it… Imagine Google or Microsoft developing a new AI system that needs to understand and process human language. Training this AI requires vast amounts of annotated data – billions and billions of data points that need to be labeled with relevant information, like identifying parts of speech like nouns, verbs, etc. and sentence structures. […] Large companies developing AI projects often spend 80% of their time preparing data and only 20% training AI algorithms – a time-consuming process for those managing massive data inputs for large language models (LLMs) and other AI tools. So, they turn to Innodata (INOD) for help. Innodata uses a combination of automated tools and human experts to label large datasets accurately, and large tech players like Google or Microsoft then use that annotated data to train the AI models, improving their ability to understand and generate human language. Getting a handle on these massive datasets is a big deal, and there aren’t many pure play service providers operating in this space. And this isn’t just a great idea. The business is booming: Innodata’s largest customer now generates an annualized run rate revenue of $135 million, and revenue from its seven other major tech customers surged 159% sequentially, validating its land-and-expand strategy. The company also has multiple pilots underway, including a large-scale enterprise deal with the potential to generate seven- or eight-figure revenue. Looking ahead, Innodata expects at least 40% revenue growth in 2025, with potential for further upward revisions as new business is secured. AI models are only as good as the data they are trained on, and Innodata is becoming a critical resource to organize high-quality AI training data at scale. But as regular readers know, it’s not just about the balance sheet when it comes to the Swans. They also track unique metrics that reveal more about the company – namely, trends that are likely to show up in future earnings reports. As just one example, here’s a chart they prepared showing a strong trend in INOD’s web visits, indicating interest not just from potential customers but also likely investors: 
INOD is a smaller name, but it’s one to watch. The stock has one of the higher Volatility Quotients (VQ%) I’ve seen lately, at 72.4%. For context, bigger, more established AI plays like Nvidia (NVDA) have a VQ% of 42.4%. Not too surprising, since Innodata is a much earlier-stage company. But it’s earnings positive, growing, and operates in a unique niche in the larger AI trend. That’s why Andy and Landon added it to the MegaTrends watchlist close to a year ago: 
Andy and Landon are great at finding names like this precisely because of how they look at stocks. They don’t just see balance sheets or charts. They see brands, and sentiment, and a host of other factors that lead them to early winners. On Sunday, right here in TradeSmith Daily, Andy made a bullish call on Robinhood Markets (HOOD) and not 24 hours later, the stock ripped 7% higher on its newest predictions product announcement. With their early lead, MegaTrends subscribers have more than doubled their money on HOOD in less than a year. Add that to the long list of profitable MegaTrends trades made in 2024, including 445% on Coinbase Global (COIN), 211% on Palantir Technologies (PLTR), and a quick 79% on a Duolingo (DUOL) position opened and closed in less than six months… And it’s clear, their consumer-driven insights pay off. See for yourself how their stock-picking system works here. Finally, tomorrow is a big day for tech… Remember those days when Steve Jobs would take the stage in his black turtleneck? Nowadays, it’s Jensen Huang of Nvidia (NVDA) with his black leather jacket moving markets. And tomorrow he’ll be hosting Nvidia’s first-ever Quantum Day as part of its annual AI Conference. Just weeks ago at the 2025 Consumer Electronics Show (CES), Huang had basically said to check back in 2045: “If you kind of said [it’d take] 15 years for very useful quantum computers, that’d probably be on the early side,” he said – 20 years was more believable. So why did Huang downplay quantum computing in January – only to turn around and announce that he’s going to dedicate an entire day to it? Was this all a case of misdirection? Gamesmanship? Was Huang trying to mislead competitors? We could be about to find out tomorrow at 1 p.m. Eastern in his “fireside chat” with 14 leading voices in quantum computing. But now is the time to brace for impact. Before Q Day, you can hear all about the quantum play Louis Navellier has identified as his Next 50X Nvidia Call – a small-cap protected by 102 patents with close ties to Nvidia itself. Already, quantum computing stocks have left these market doldrums far behind. So why wait for Huang to take the stage and drop his next big announcement… get up to speed on quantum innovation now by clicking here. To your health and wealth, 
Michael Salvatore
Editor, TradeSmith Daily | 
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