Of all the companies I\u2019m betting against, my biggest bet is against Applied Digital (APLD).<\/p>\n
I\u2019m the portfolio manager of a small hedge fund, Fieldsong Investments, and we hedge our long equity positions with put options. These are essentially bets against stocks; they make money if the stock goes down in price more than a certain amount. Our hedge has more invested in Applied Digital puts than puts on any other company.<\/p>\n
This article is devoted to discussing Applied Digital, its benefactor Nvidia (NVDA), and the detection of egregious manipulation of financial reports.<\/p>\n
According to The Bear Cave<\/a>, a newsletter devoted to exposing corporate misconduct, the company was incorporated in Nevada in 2001 as Reel Staff to provide staffing to production companies, but did a stock merger the next year with Flight Safety Technologies. Then in 2008 it pivoted to plasma technology and changed its name to Applied Science Products. Then it acquired Cummins Family Produce the next year so that it was now processing and packaging potatoes.<\/p>\n If that strikes you as crazy, this kind of switching is not that uncommon for shell companies. In 2021, the company changed its name to Applied Blockchain after acquiring crypto mining assets. The next year it changed its name to Applied Digital and switched to next-generation datacenters. All of this is frankly admitted on their website<\/a>.<\/p>\n The company\u2019s Chairman and CEO is Wes Cummins (of Cummins Family Produce). Cummins was also President of B. Riley Asset Management; B. Riley Financial, its parent company, recently made headlines due to the bankruptcy of Franchise Group, one of its key holdings, and is the most shorted stock in the financial sector. If you want to read more about both Applied Digital\u2019s and B. Riley's shenanigans, here\u2019s a good article<\/a>.<\/p>\n But none of these are the reasons I bet against this company. I create ranking systems to guide me in choosing stocks to bet on (go long) and to bet against (using put options). Applied Digital was for many months ranked #1 on my ranking systems for puts, but I could never afford the options: I don\u2019t like to pay too high a premium. They seemed like a stock certain to collapse, with terrible financials, negative price momentum, poor sentiment indicators, and barely any prospect of ever making any money. But then they raised $160M from a Nvidia private placement, which made the stock price go up and the put price go down. For me, this presented a good buying opportunity.<\/p>\n This is a company with negative gross margins, huge net losses, depleted cash reserves (well, until the Nvidia loan), large asset sales, equipment issues, and questions about the true demand for their supposed services. Last quarter\u2019s interest expense was $18M, revenue was $44M, operating income was \u2013$37M, net loss was \u2013$65M. Those numbers were clearly unsustainable, and the most recent quarter\u2019s numbers are significantly better, but their cost of goods remains higher than their revenue. In addition, they recently issued $53M in convertible preferreds, and have plans to issue another 49M more shares at $3.24 (the current price is over $6). There\u2019s a good Seeking Alpha article<\/a> that outlines much of this.<\/p>\n Nvidia seems to be shoring up Applied Digital, infusing it with cash so that it doesn\u2019t fail. They did this with CoreWeave last year<\/a>. In a nutshell, Nvidia is loaning vast sums to its own customers so that they can buy more Nvidia chips. And those customers are drowning in debt, with hugely negative income, so they\u2019re using those chips as collateral. How can this last? The scheme is unsustainable.<\/p>\n How is Nvidia increasing its revenue when the price of its chips is going down (indeed, all of Nvidia\u2019s most popular chips have decreased in price) and why are those revenue increases so much higher than those of comparable companies like Advance Micro Devices and Taiwan Semiconductor? In part, it\u2019s by making unsafe loans that effectively prop up its revenue. It\u2019s basically selling chips to itself. Almost all of its sales increases are concentrated in sales to data centers and similar clients. Applied Digital and CoreWeave aren\u2019t the only data companies with shaky financials: check out Super Micro Computer (SMCI), another Nvidia customer whose Beneish M-Scores (explained below) are super high. Once Nvidia\u2019s customers start to default\u2014and once they start buying non-Nvidia chips\u2014will the ship go down? And how long will that take?<\/p>\n Last year I researched at length a system that estimates, from financial statements, the probability that a company is engaged in manipulation of their financials or \u201cfraudulent\u201d behavior, closely based on the work of Messod Beneish. Some of what I\u2019m going to say here repeats what I wrote then<\/a>.<\/p>\n At that time, an investment research firm exposed a company I had invested in (Tingo Group) as a massive fraud. Most of this company\u2019s revenue apparently came from some other companies that they had recently acquired, but it turned out to be practically impossible to verify that any of that revenue actually existed outside of the company\u2019s books. Shortly thereafter, the SEC suspended trading in its shares and filed charges against its founder.<\/p>\n Based on their most recent financial statements, I had given this company a very high rating and had put a lot of money behind it. (I wasn\u2019t the only one to rate the company highly: Seeking Alpha offers \u201cquant ratings\u201d for all publicly traded US stocks, and gave it an A+.)<\/p>\n This hurt. Not only did it hurt financially\u2014I lost over $80,000\u2014but it hurt my credibility as a quantitative investor. In the big picture, I could stomach the loss. But my investing philosophy is founded on the maxim that safer stocks are better investments than risky ones. And yet I put a large bet on a stock that this research firm would shortly and rightly label a swindle with fictitious financials.<\/p>\n One reason I was caught off-guard is that Tingo Group was listed on the NASDAQ as a US company. Listed stocks domiciled in the US are the safest stocks on earth simply because the SEC is better at going after fraudsters in the US stock market than any other government regulatory body.<\/p>\n Stock market history, though, is full of frauds. It\u2019s in the very nature of the beast. We are taught that we should beware of companies engaging in manipulation of their financial statements. Yet every<\/em> company, by the very nature of financial reporting, has some leeway in constructing financial statements. There are hundreds of gray areas when reporting financials\u2014which is one reason I frequently say that there is absolutely nothing scientific about financial data<\/a>. What am I doing when I rank stocks based on this discretionary data, then? Well, I\u2019m dealing in probabilities. If a stock\u2019s reported free cash flow is high, that doesn\u2019t mean that it\u2019s a winner: it means that it\u2019s more likely to be a winner than a stock whose reported free cash flow is extremely low.<\/p>\n So what could have tipped me off that Tingo was a fraud? Was there something quant-based <\/em>that I should learn from this experience? Was there a screening rule I could apply to my universes to prevent this from happening again? Prompted by these questions, I researched and published the above-linked deep exploration into the subject of detecting fraudulent reporting.<\/p>\n In 1999, a professor of accounting at Indiana University published \u201cThe Detection of Earnings Manipulation\u201d in Financial Analysts Journal<\/em>. (This was a thorough revision of a method he had first published in 1997.) Messod Beneish was not the first nor the last to attempt to use financial statement analysis to detect fraud. But his method has held up better than any other; in a 2020 follow-up paper, \u201cThe Cost of Fraud Prediction Errors<\/a>,\u201d he proved that it had a lower ratio of false to true positives than any other method besides a machine-learning-based one introduced in 2020.<\/p>\n Beneish arrived at his formula by examining 74 firms that manipulated earnings over a six-year period and comparing those to 2,332 similar firms that did not. He came up with eight factors whose higher values seemed to indicate a greater chance of manipulation, seven of which compare the latest fiscal year\u2019s figure to the previous one\u2019s.<\/p>\n There are a lot of online versions of the Beneish M-score (M stands for manipulation<\/em>), and many of them take slightly different approaches to the one Beneish originally proposed. The closest one available to Beneish\u2019s original method is an excellent online calculator<\/a> from Indiana University\u2019s Kelley School of Business, where Beneish teaches, which breaks down any company\u2019s M-score by factor and gives probabilities and odds. It\u2019s faithful to the original calculation, using annual figures and Winsorizing, which most other services don\u2019t do.<\/p>\n According to the Kelley School calculator, Applied Digital gets a very high score, with 120-to-1 odds that the company is a \u201cmanipulator\u201d (meaning that there\u2019s less than a 1% chance that it isn\u2019t). Nvidia\u2019s score isn\u2019t quite so high, but it still gets 63-to-1 odds that it\u2019s a \u201cmanipulator\u201d too.<\/p>\n When I studied how the M-score works, I looked at the M-scores and the eight factors for about forty companies that have received damning reports from an investment research firm that specializes in accounting irregularities, undisclosed related-party transactions, and illegal financial reporting practices. Not all of those companies engaged in financial manipulation, but a majority of them seem to have.<\/p>\nWhy Nvidia Propped Up Applied Digital<\/h2>\n
Earnings Manipulators (and Why Applied Digital and Nvidia Can Be Labeled as Such)<\/h2>\n