Apple Emerges as the Top FAANG Stock Choice by Lawmakers on Capitol Hill
Apple Emerges as the Preferred FAANG Stock Among Lawmakers in 2023
It's clear which FAANG stock is most popular with members of Congress. Of the 535 members of Congress, 100 bought or sold stocks in 2023, according to options trading platform Unusual Whales. One-third of them outperformed the S&P 500.
With FAANG stocks skyrocketing in 2023, you might think representatives and senators loaded up on the widely followed growth stocks. But that wasn't the case. Lawmakers on Capitol Hill were net buyers of only one FAANG stock last year.
The Apple of politicians' eyes
- Apple (NASDAQ: AAPL) turned out to win the votes of politicians in 2023. Representatives and senators bought $2.4 million of the tech stock, enough to land it in the No. 2 spot, narrowly trailing ConocoPhillips. Apple also ranked fifth among stocks traded by members of Congress based on number of shares.
- Twenty lawmakers traded Apple last year. This made the stock slightly less popular than Microsoft and JPMorgan Chase with 23 and 21 members of Congress trading each stock, respectively.
Apple emerged as the top FAANG stock choice for lawmakers, surpassing other tech giants like Google and Facebook. Political figures from both parties, including Rep. Ro Khanna and former House Speaker Nancy Pelosi, were actively investing in Apple stock.
Why just Apple?
- It makes sense that Apple was a top pick for lawmakers -- it was the biggest company in the world based on market cap in 2023 and has been one of the most popular stocks among all investors for years. What is surprising, though, is that Apple was the only FAANG stock for which members of Congress were net buyers.
The post also highlights the reasons why Apple was favored by lawmakers and explores the potential implications of their investment decisions for the stock's future performance.
This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.