Ken Griffin’s Wellington Fund Delivers Mind-Numbing Returns and Its Top 5 Stocks

4. NVIDIA Corporation (NASDAQ:NVDA)

Citadel Investment Group’s Equity Stake: $893.41 Million
Number of Hedge Fund Holders: 180

NVIDIA Corporation (NASDAQ:NVDA) was a breakout stock in 2023, rallying by more than 230% and helping Ken Griffin’s Wellington Fund deliver mind-numbing returns. NVIDIA Corporation (NASDAQ:NVDA), which designs, develops, and sells graphic processing units, has seen its fortunes and sentiments improve amid the artificial intelligence boom.

As NVIDIA Corporation (NASDAQ:NVDA) continues to deliver record-breaking revenues and earnings, it should allow the Ken Griffin’s hedge fund to provide mind-numbing returns. Consequently, the Citadel Investment Group increased its stakes in the company by 57% in Q3 to $893.41 million. 

As of the end of September quarter, 180 hedge funds tracked by Insider Monkey had stakes in NVIDIA Corporation (NASDAQ:NVDA), up from 175 in the previous quarter. Rajiv Jain’s GQG Partners was one of the remarkable shareholder of NVIDIA Corporation (NASDAQ:NVDA) with stakes worth $6.11 billion.

Blue Tower Asset Management made the following comment about NVIDIA Corporation (NASDAQ:NVDA) in its Q3 2023 investor letter:

“In addition to the use of larger datasets, the training speed of AI models has increased dramatically. NVIDIA Corporation (NASDAQ:NVDA) ‘s stock almost tripled in the first three quarters of this year with a 197% gain, and a large reason for this is the huge role they have played in recent AI improvements. Nvidia’s single GPU AI training speed performance has increased by a dramatic 1000x in 10 years, with only 2.5x coming from Moore’s Law3-driven increases in chip density. Besides better chip manufacturing, there were three other improvement factors at play: simplifications in number representation for the weights of the neural networks, more complex mathematical instructions for reducing the computational overhead involved in mathematical calculations, and increased neuron sparsely (in neural networks, some neurons are useless and can be pruned from the network without reducing performance significantly).

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