Nvidia stock falls to $175 as director sells $44M stake amid AI sector slowdown
As of December 18, Nvidia stock is trading at $175.6, down 3.8% in 24 hours and down over 17% from its 2025 high. The stock has entered a consolidation phase, moving sideways between $168 and $182 over the past two weeks.
Highlights
- Nvidia is consolidating near key support at $170 after a 17% pullback from recent highs, with technical indicators signaling indecision.
- A $44 million insider sale by director Harvey Jones has added pressure amid broader rotation out of AI and tech stocks.
- A break below $168 could trigger further downside, while a move above $185 would reopen upside toward $200 and beyond.
Support is developing between $168 and $170, a zone that coincides with the 50-day simple moving average (SMA) and the December lows. A sustained break below this range could trigger a retracement toward $155, which aligns with the 100-day SMA and prior breakout levels from September. If $155 fails, the next support level lies near $143, where stronger long-term buying interest could emerge.
On the upside, immediate resistance is seen at $182. A clean break above that would clear the path toward $200 and then the 2025 high at $212. Those levels remain strong technical and psychological barriers. Momentum indicators are neutral, with the Relative Strength Index (RSI) hovering around 50 and MACD signals flattening. These suggest a lack of conviction from either bulls or bears in the near term.

Nvidia stock price dynamics (October 2025 - December 2025). Source: TradingView
Despite the current pause, NVDA maintains a longer-term bullish structure. The 200-day SMA is trending higher below $140, well beneath current levels. As long as the stock holds above $168, the broader uptrend remains intact, although buyers will need to reclaim $185 to resume upward momentum.
Insider sale and sector rotation pressure AI leaders
On December 17, Nvidia director Harvey Jones sold approximately 250,000 shares for a total of about $44 million. The average sale price was $177.33, very close to current trading levels. Jones still holds over 7 million shares, so the move appears to be long-term profit-taking rather than a loss of confidence. However, its timing has added pressure to a stock already facing valuation concerns and macro-driven volatility.
The sale coincides with a rotation away from mega-cap AI and semiconductor stocks. Recent weeks have seen investors favor more defensive sectors such as healthcare and consumer staples. For instance, Eli Lilly has outperformed Nvidia over the past month, suggesting a tactical shift in institutional positioning. Nvidia, after months of leading gains, now appears to be pausing as capital flows rebalance across the market.
Further weighing on sentiment are concerns about the sustainability of capital spending for AI infrastructure. Oracle’s difficulties in securing financing for its planned data center expansion have raised broader questions about the affordability of AI buildouts, which directly affect demand for Nvidia’s high-performance GPUs. Though Nvidia’s fundamentals remain strong, these macro constraints have introduced caution among short-term investors.
Range-bound trade likely before breakout
In a bullish scenario, Nvidia holds above $170 and breaks cleanly above $182. A move through $185 could trigger a test of $200, and potentially the $212 high from November. A decisive close above that would open up upside toward $225 in the first quarter of 2026, especially if earnings or macro data are supportive.
In a bearish scenario, a break below $168 would likely prompt selling toward $155, with extended risk down to $143 if broader market weakness intensifies or investor appetite for AI names declines further. A move below $155 would shift the intermediate outlook from neutral to bearish.
Nvidia has acquired SchedMD, the maker of Slurm, to strengthen its position in AI and HPC infrastructure by expanding into open-source workload management. This move deepens Nvidia’s software strategy, aiming to drive long-term platform adoption across AI and supercomputing ecosystems.
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