Nasdaq Correction: Time to Buy the Dip on Nvidia?
The Nasdaq Composite (NASDAQINDEX: ^IXIC) has moved into correction territory (down at least 10% from all-time highs). A significant contributor to that drop has been Nvidia (NASDAQ: NVDA) stock, which is down about 20% year to date, as of this writing. The chipmaker reported outstanding results recently, but investor concerns about tariffs and the U.S. suddenly looking like it could be headed toward a recession have rattled the market in the near term.For investors interested in Nvidia who have a long-term mindset, this price correction presents a great opportunity to scoop up Nvidia shares on the cheap. Let's look at three reasons why the stock is a must-buy for the long term on this dip.With an approximate 90% market share for graphics processing units (GPUs), Nvidia is the dominant leader among the chip designers that are powering the artificial intelligence (AI) infrastructure buildout. While originally designed to speed up graphics rendering in video games, Nvidia's GPUs' fast processing times have made them ideal for helping train large language models (LLMs) and running inference for AI.Continue reading
The Nasdaq Composite (NASDAQINDEX: ^IXIC) has moved into correction territory (down at least 10% from all-time highs). A significant contributor to that drop has been Nvidia (NASDAQ: NVDA) stock, which is down about 20% year to date, as of this writing. The chipmaker reported outstanding results recently, but investor concerns about tariffs and the U.S. suddenly looking like it could be headed toward a recession have rattled the market in the near term.
For investors interested in Nvidia who have a long-term mindset, this price correction presents a great opportunity to scoop up Nvidia shares on the cheap. Let's look at three reasons why the stock is a must-buy for the long term on this dip.
With an approximate 90% market share for graphics processing units (GPUs), Nvidia is the dominant leader among the chip designers that are powering the artificial intelligence (AI) infrastructure buildout. While originally designed to speed up graphics rendering in video games, Nvidia's GPUs' fast processing times have made them ideal for helping train large language models (LLMs) and running inference for AI.
