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Bad Trades

Your favorite social media guru is probably a bad stock picker

Research has shown that most "stock market influencers" are actually really bad stock pickers.

Jack Raines

One of my favorite parts of 2020 and 2021 was the emergence of the “finfluencer” (finance influencer) on social media sites like Twitter, Reddit, and StockTwits. These influencers ranged from anonymous accounts, who, perhaps once a month, tweeted higher quality breakdowns of under-covered stocks than you’d find in JPMorgan’s equity research department, to Wall Street Bets regulars who posted stock charts, poorly constructed “technical analyses,” and rocket ship emojis. 

WSB
via u/raseC_Ceda on r/wallstreetbets

Some finfluencers wrote about their favorite stocks behind paywalled Substacks, often justifying negative margins and 50x revenue multiples with high top-line growth. Meanwhile, dozens of “trading groups” pumped their favorite penny stocks, believing that a “not financial advice” disclaimer would protect them from any legal issues (and, in at least one case, they were right).

Of course, the influx of finfluencers led to an important question: do their recommendations outperform the market? Thanks to the Swiss Finance Institute, we now know that the answer is “No.” In fact, the majority of stock market influencers actually generate statistically significant underperformance.

Last year, Ali Kakhbod, Seyed Kazempour, Dmitry Livdan, and Norman Schürhoff published a paper on their findings after studying the performance of more than 29,000 StockTwits finfluencers. This abstract is just gold:

Tweet-level data from a social media platform reveals low average accuracy and high dispersion in the quality of advice by financial influencers, or “finfluencers”: 28% of finfluencers are skilled generating 2.6% monthly abnormal returns, 16% are unskilled, and 56% have negative skill (“anti- skill”) generating -2.3% monthly abnormal returns...

The advice by antiskilled finfluencers creates overly optimistic beliefs most times and persistent swings in followers’ belief bias. Consequently, finfluencers cause excessive trading and inefficient prices such that a contrarian strategy yields 1.2% monthly out-of-sample performance.

After four years, we now have proof that, yes, fading stock market gurus is a profitable trading strategy.

However, while finfluencers, as a group, generated negative returns, the researchers saw that a minority actually generated abnormally high returns. Sadly, these skilled ones had smaller audiences:

Less active finfluencers with fewer followers are more likely to be skilled. Skilled finfluencers are return contrarian; they make positive tweets after negative returns and negative tweets after positive returns. Skilled finfluencers are also social sentiment and news contrarian; they make fewer positive tweets when social sentiment is positive and more positive tweets after negative news. Similarly, they make more/fewer negative tweets when social sentiment is positive/negative and fewer negative tweets after negative news. More tweeting after high trading volume and, in particular, negative tweets on short-sale constrained stocks also indicate the presence of skill…

Antiskilled finfluencers ride return and social sentiment momentum. They make positive tweets after positive returns and negative tweets after negative returns. Antiskilled finfluencers are more/less likely to make positive/negative tweets after positive social sentiment. Antiskilled finfluencers are also less/more likely to make positive/negative tweets after negative news.

Basically, most finfluencers’ recommendations actively underperformed the market, but a minority of posters outperformed. The issue is that followers failed to accurately identify the skilled traders.

Intuitively, it makes sense that worse traders would have bigger followings. Skilled traders will make money regardless of their audience size, so they don’t need to self-promote. Unskilled traders, on the other hand, need large audiences to make money, because they are either selling stock picks to their followers, or they using their followers as counterparties.

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BlackBerry is on one of its hottest rallies of all time

History suggests that BlackBerry does extremely well when 1) it’s considered to be pioneering a transformative technology, or 2) there’s widespread retail enthusiasm for stocks.

If you squint (or dream), you could argue that both are going on right now.

Shares of the once-upon-a-time smartphone giant are up more than 160% over the past three months. The only times the shares have had a hotter run of form than this are at the tail end of the dot-com bubble, and in early 2021 when was it part of the meme stock craze headlined by GameStop.

Let’s start with the easy part first — here’s Scott Rubner, head of equity and equity derivatives strategy at Citadel, on retail’s significant footprint in the shares’ rally:

“Retail traders are the new price setters in the market. May volumes across our retail cash equities and options platforms are currently tracking at record levels. Daily volumes on our cash platform are setting new highs and are on pace to finish nearly ~10% above the previous record established during the January 2021 meme-stock era.”

And then there’s the harder part, part of the story that the traders bidding up BlackBerry now are dreaming about: the QNX division, which offers software that the company is positioning as an operating system for robots.

QNX’s software has early uptake in the field of autonomous driving, with BlackBerry eyeing a much more widespread role: in April, it announced a partnership to deploy this technology on Nvidia’s robotics platform. Nvidia’s Jensen Huang, for his part, has long been calling for agentic AI adoption to be followed by physical AI (i.e., robots).

In a QNX press release unveiling a report this week, the company argued that software, not hardware, is the real problem in terms of making sure robotics works.

I supposed it would be poetic, in a way, if the company at the leading edge of the smartphone revolution also plays a big role in the proliferation of robotics.

markets

Micron and Sandisk rally on new Street-high price targets from Susquehanna

Micron and Sandisk both hit fresh all-time highs in early trading after Susquehanna bestowed new Wall Street-high price targets on the two memory stocks.

Analyst Mehdi Hosseini upped his view on the former to $1,750 from $600, and to $3,250 from $2,000 for the latter.

“Supply is now expected to remain tight through 2027, sustaining elevated margins and thus warranting valuation re-rating,” he wrote, per Bloomberg.

It’s the fifth time in the past year that the average price target on Micron has gone up by more than 10% in a week. UBS’s Tim Arcuri more than tripled his price target on Micron earlier this week, and has already lost the title of “most bullish.”

But even as analysts are tripping over themselves to raise their price targets on these stocks, the ferocity of the rally in Micron has outpaced their best efforts.

The high-bandwidth memory specialist traded at a record premium to the consensus Wall Street price target this week, based on data going back to 2008.

markets

Okta soars on Q1 earnings beat, raised outlook driven by AI security demand

Okta shares are surging in early trading Friday after the identity security provider posted Q1 fiscal 2027 financial results that exceeded Wall Street estimates. The strong results are fueled by accelerating corporate demand for cybersecurity software, as well as the deployment of autonomous AI systems.

Key numbers:

  • Adjusted earnings per share of $0.91 compared to analysts estimate of $0.85.

  • Revenue of $765 million compared to an estimate of $752.7 million.

The company generated subscription revenue of $750 million, up 11% year over year. Okta also has $271 million in free cash flow, up from $238 million in the prior years quarter.

While standard cybersecurity software protects human workers, the latest catalyst sparking Oktas strong corporate performance is the rapid emergence of autonomous AI agents that can access sensitive corporate databases and interact with privileged executive accounts.

“AI agents are rapidly becoming a new workforce inside every organization, creating a wave of identities that must be secured and governed alongside human users,” said Todd McKinnon, CEO and cofounder of Okta. “We’re expanding our opportunity as the world’s leading independent and neutral identity provider and helping customers make identity the unified control plane for their secure agentic enterprise.”

Okta raised its fiscal 2027 revenue guidance to between $3.185 billion and $3.205 billion, roughly in line with estimates of $3.18 billion. The company formally dropped its long-term projected non-GAAP tax rate from 26% down to 21%. This adjustment is a direct byproduct of the federal corporate tax frameworks under the One Big Beautiful Bill Act.

Shares of Okta have risen around 9% since the beginning of this year.

markets

HPE, SMCI surge after Dell’s Q1 beat on strong AI server demand

HP Enterprise and Super Micro Computer shares are surging in premarket trading, getting a big boost from rival Dell’s strong Q1 results.

Dell’s $16.1 billion in AI-optimized server sales for the quarter alone proved that enterprise data center demand is accelerating faster than Wall Street had anticipated. The company posted revenue of $43.8 billion, exceeding Street estimates of $35.5 billion. Management now sees full-year sales of about $167 billion, well above the $142 billion expected by analysts.

The read-through is particularly relevant for Super Micro, one of the largest suppliers of Nvidia-powered AI server systems, and HPE, which has been expanding its AI infrastructure and liquid-cooling offerings through its partnership with Nvidia.

The moves suggest investors view AI infrastructure as a broad spending cycle that benefits server makers across the entire ecosystem.

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