Ranked: Big Tech CEO Insider Trading During the First Half of 2021
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Ranked: Big Tech CEO Insider Trading During the First Half of 2021

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Ranked: Big Tech CEO Insider Trading During the First Half of 2021

Big Tech CEO Insider Trading During The First Half of 2021

When CEOs of major companies are selling their shares, investors can’t help but notice.

After all, these decisions have a direct effect on the personal wealth of these insiders, which can say plenty about their convictions with respect to the future direction of the companies they run.

Considering that Big Tech stocks are some of the most popular holdings in today’s portfolios, and are backed by a collective $5.3 trillion in institutional investment, how do the CEOs of these organizations rank by their insider selling?

CEOStockShares Sold H1 2021Value of Shares ($M)
Jeff BezosAmazon (AMZN)2.0 million$6,600
Mark ZuckerbergFacebook (FB)7.1 million$2,200
Satya NadellaMicrosoft (MSFT)278,694
$65
Sundar PichaiGoogle (GOOGL)27,000$62
Tim CookApple (AAPL)0$0

Breaking Down Insider Trading, by CEO

Let’s dive into the insider trading activity of each Big Tech CEO:

Jeff Bezos

During the first half of 2021, Jeff Bezos sold 2 million shares of Amazon worth $6.6 billion.

This activity was spread across 15 different transactions, representing an average of $440 million per transaction. Altogether, this ranks him first by CEO insider selling, by total dollar proceeds. Bezos’s time as CEO of Amazon came to an end shortly after the half way mark for the year.

Mark Zuckerberg

In second place is Mark Zuckerberg, who has been significantly busier selling than the rest.

In the first half of 2021, he unloaded 7.1 million shares of Facebook onto the open market, worth $2.2 billion. What makes these transactions interesting is the sheer quantity of them, as he sold on 136 out of 180 days. On average, that’s $12 million worth of stock sold every day.

Zuckerberg’s record year of selling in 2018 resulted in over $5 billion worth of stock sold, but over 90% of his net worth still remains in the company.

Satya Nadella

Next is Satya Nadella, who sold 278,694 shares of Microsoft, worth $234 million. Despite this, the Microsoft CEO still holds an estimated 1.6 million shares, which is the largest of any insider.

Microsoft’s stock has been on a tear for a number of years now, and belongs to an elite trillion dollar club, which consists of only six public companies.

Sundar Pichai

Fourth on the list is Sundar Pichai who has been at the helm at Google for six years now. Since the start of 2021, he’s sold 27,000 shares through nine separate transactions, worth $62.5 million. However, Pichai still has an estimated 6,407 Class A and 114,861 Class C shares.

Google is closing in on a $2 trillion valuation and is the best performing Big Tech stock, with shares rising 60% year-to-date. Their market share growth from U.S. ad revenues is a large contributing factor.

Tim Cook

Last, is Tim Cook, who just surpassed a decade as Apple CEO.

During this time, shares have rallied over 1,000% and annual sales have gone from $100 billion to $347 billion. That said, Cook has sold 0 shares of Apple during the first half of 2021. That doesn’t mean he hasn’t sold shares elsewhere, though. Cook also sits on the board of directors for Nike, and has sold $6.9 million worth of shares this year.

Measuring Insider Selling

All things equal, it’s desirable for management to have skin in the game, and be invested alongside shareholders. It can also be seen as aligning long-term interests.

A good measure of insider selling activity is in relation to the existing stake in the company. For example, selling $6.6 billion worth of shares may sound like a lot, but when there are 51.7 million Amazon shares remaining for Jeff Bezos, it actually represents a small portion and is probably not cause for panic.

If, however, executives are disclosing large transactions relative to their total stakes, it might be worth digging deeper.

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Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

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Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

  • Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
  • Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
  • Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

  • Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
  • Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
  • Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

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