Nvidia Completes Stock Split To Make Shares More Affordable
The 10-for-1 stock split at Nvidia has taken place, after the meteoric share price rise helped it become one of the most valuable tech firms
Nvidia has completed its 10-for-1 stock split, as the GPU powerhouse seeks to lower its share price to help new investors acquire shares.
Last Friday Nvidia’s share price, which had been trading around $1,200 per share, underwent a 10-for-1 stock split, with its share price trading at $120 on Monday.
On Wednesday morning Nvidia’s share price was trading at $121.91.
Nvidia’s share price has rocketed in value during the past 12 months, so much so that last week the firm briefly overtook Apple to become the second most valuable tech firm in the world, worth over $3 trillion.
More affordable shares
With Nvidia’s share price last week trading at around $1,224.40 – the high price made it difficult for some investors to purchase whole shares.
So the Associated Press reported that Nvidia carried out a stock split at the close of trading last Friday, where it divided its existing shares to increase the number of shares available to investors.
Nvidia carried out a 10-1 stock split, which means each share was divided in 10.
This means that if an investor previously had 10 Nvidia shares, they will now have 100.
However, the value of the investor’s overall shareholding will remain the same, as the share price was also divided up.
Meteoric shares
Nvidia’s stock price has endured a meteoric rise in recent years, after it more than tripled in 2023.
Indeed in May 2023 Nvidia’s market value had surpassed the $1 trillion mark.
So far in 2024, Nvidia’s share price has more than doubled.
Indeed, it was only in February 2024 when Nvidia’s Q4 and FY24 results had helped push the firm’s market value (market capitalisation) close to the $2 trillion mark.
Then just three months after reaching close to the $2 trillion mark, Nvidia added another $1 trillion in market value, which is quite a remarkable achievement.
Nvidia has seen soaring demand for its semiconductors, which are used to power artificial intelligence applications.