With Nvidia (NVDA) falling 10% on Friday and the afterhours session not exactly demonstrating confidence, it seems easy to label NVDA stock as a potential bear target. However, the bulls have moved in earnestly based on options market data, particularly data focused on major transactions. And the contrarian sentiment also makes sense in many ways.

Yes, NVDA stock is overpriced based on traditional financial metrics. Pulling up Barchart’s Key Statistics screen, we see that shares trade for nearly 70X trailing-12-month (TTM) earnings. Against book value, the multiple stands at almost 51X. Finally, it trades at 34.48X last year’s revenue. No matter how you slice it, you can easily find better deals than Nvidia – at least on paper.

However, the fundamental argument for NVDA stock has recently centered on artificial intelligence. With its graphics processing units able to meet the rigorous demands of generative AI protocols, sales have skyrocketed. Moreover, Nvidia commands incredible brand and pricing power and that equates to higher profitability.

Therefore, on both fronts – earnings and sales – Nvidia runs atop the pack. Subsequently, the logic stands that NVDA stock deserves its rich premium. While there are many other tech firms that offer a better valuation, very few enjoy the market dominance that Nvidia wields.

Still, that’s the be-all, end-all of this discussion, a matter that has been complicated by Nvidia’s derivatives market activity.

Institutional Traders Go the Contrarian Route with NVDA Stock

Following Friday’s close, NVDA stock represented one of the highlights in Barchart’s unusual options volume screener. This tool shows which trades are the most aberrant, alerting retail investors to what the smart money is doing. With Nvidia derivatives, total volume reached 3.39 million contracts against an open interest reading of 4.25 million contracts.

Drilling down, call volume hit about 1.83 million contracts while put volume came in at 1.56 million. This pairing yielded a put/call volume ratio of 0.85. That’s fairly even relative to earlier readings that have demonstrated decisive bullishness toward NVDA stock. Of course, the severe fallout rattled many nerves.

Nevertheless, on the whole, the options flow screener – which filters exclusively for big block transactions likely placed by institutions – shows an overwhelming number of trades with bullish sentiment. That implies that the big dogs of Wall Street are buying up the weakness. Again, that makes sense for the fundamental factors mentioned above.

However, the immediate problem is that NVDA stock lacks discernible support lines to around $675, when shares briefly encountered a corrective action before swinging higher. To be sure, Barchart’s Trader’s Cheat Sheet shows support lines at $699.92, $710.15 and $730.96. Still, these levels appear tenuous because there’s a lack of history supporting such prices.

Stated differently, NVDA stock shot up very quickly to its all-time high. But in doing so, it didn’t establish “base camp” prior to running up the peak. So, the descent could be swift, just as it was on Friday.

Most importantly, at some point, valuation will matter. Sure, Nvidia’s AI business looks red hot at the moment. However, with the Federal Reserve signaling a delay in its prior aim to cut interest rates, risk-on sentiment has dried up. Further, if energy costs continue to rise, the central bank could be forced to raise rates.

There are so many risk factors involved, meaning that it may be too early to go contrarian on NVDA stock.

Fundamentals Might Not Be as Good as You Think

In all fairness, the one factor that has kept the machinery going is the projected valuation of the global AI market. According to a Bloomberg report, the sector could be worth $1.3 trillion by 2032. Further, digital intelligence protocols may act as a force multiplier, bolstering productivity and thus lifting the global economy.

I don’t think anyone disputes the potentiality of AI. However, what is up for debate is the probability of the projected paradigm shift.

According to a research experiment conducted by Teche, a learning and teaching blog published by Macquarie University, popular chatbot ChatGPT generated fake references – in fact, five out of six references written by the AI protocol were fake.

Here’s the problem: there’s no industry that I can think of where a failure of more than 83% would be considered acceptable. Even in baseball – a sport of managed failure – batting .167 just won’t cut it. And that’s the harsh reality that you don’t hear regarding AI’s supposed productivity.

Yes, AI can do plenty of stuff at lightning speeds. But if most of the output is inaccurate, then said “productivity” is useless. That needs to be factored into the valuation of AI-related enterprises. And so, the correction may only be the beginning.