July 1, 2024
ChatGPT = tip of the iceberg
Dear Reader,
Artificial intelligence has exploded into the mainstream consciousness in the past couple of years.
AI is changing pretty much every aspect of the world we live in. How we produce and consume media, how we do business, receive healthcare, you name it — it’s changing faster than ever.
So it comes as no surprise that AI is changing the investing world, too.
At a basic, individual level, you can now feed a company’s financials into an AI tool and get it to read and analzye everything for you in seconds — like having your own Warren Buffett poring through numbers so you don’t have to.
But the stock market’s relationship with tech goes back way further than the current AI acceleration.
Dawn of the algos
Algorithmic — or ‘algo’ — trading began back in the early 1970s.
Financial institutions began experimenting with primitive automated trading systems that executed trades based on predetermined criteria, such as price movements or volume indicators, with limited computing power.
In the 1980s, stock exchanges went electronic, massively increasing the amount, and speed, of market data and execution capability. Trading algorithms evolved, too.
Broker Thomas Peterffy programmed a PC with a stock data feed to search for options relative to fair value — pioneering options trading in the process. Peterffy went on to found Interactive Brokers — one of the largest electronic trading platforms in the world.
The 1990s brought Direct Market Access (DMA) and electronic communication networks (ECNs). DMA enabled traders to interact directly with exchange order books, bypassing traditional brokerage channels and reducing execution times. ECNs provided electronic platforms for matching buy and sell orders, fostering competition and driving down transaction costs.
$1 trillion in 36 minutes
In 1998, the Securities and Exchange Commission relaxed regulations on alternative trading systems. This paved the way for a boom in computerized high-frequency trading.
In 2010, an algorithmic trading program went haywire, triggering a 36-minute ‘flash crash’ that wiped about a trillion dollars off the major U.S. markets before they quickly recovered.
The 2010 ‘flash crash’
In the early 2000s, algorithmic trading grew further, fuelled by advancements in computing technology and quantitative finance.
Hedge funds and proprietary trading firms led the charge, leveraging complex algorithms to exploit market inefficiencies and generate alpha.
The growing prevalence of algorithmic trading also raised concerns about market stability and fairness. Critics argued that HFT algorithms could exacerbate market volatility and contribute to flash crashes, prompting regulators to introduce stricter oversight and regulatory measures.
The algorithmic trading market is today valued at $14.42 billion USD.
That’s projected to explode about $10 billion higher to $23.74 billion in the next five years.
So while the AI boom has only captivated mainstream consumer attention as of late 2022, the investing world has been hard at work on using machines to interpret data for profit for more than half a century.
AI for investors, according to BlackRock
The current AI acceleration is making automation accessible to many more people, across many more areas of society. Trading algorithms powered by AI can enhance trading accuracy and efficiency, while also suggesting strategies based on unique goals and trading styles for improved performance.
But now it’s about more than just trading. ChatGPT’s explosion (which is really the large language model explosion) has drastically changed investment research, strategy and portfolio management.
BlackRock, the world’s largest asset manager (with $10 trillion FUM) is big into AI, and has been for a long time.
For decades, we’ve been applying natural language processing (“NLP”) techniques across a wide range of text sources including broker analyst reports, corporate earnings calls, regulatory filings, and online news articles. When analyzed at scale, each individual insight can be combined into an aggregate view that helps inform our return forecasts. The more effectively we’re able to extract and understand these insights, the more of an investment edge they may be able to provide.
(From BlackRock’s How AI is transforming investing.)
What this means is that BlackRock uses artificial intelligence to ‘listen’ to earnings calls, and predict how the market will react to them.
In other words, predicting the future to profit from it.
According to them, they have the most accurate model for doing so:
BlackRock’s earnings call AI destroying ChatGPT
The ChatGPT hype is the tip of the iceberg.
The rise of the machines in investing and trading began long ago.
But now it’s hitting full stride and everyone from the bedroom value investor to the biggest asset manager on the planet is harnessing it.
To summarize?
Well, let’s ask AI, shall we?
Here’s what ChatGPT told me about how AI changes the game for investors:
Beyond mere data analysis, AI excels in predictive analytics, leveraging historical data to forecast market trends with remarkable accuracy. This predictive prowess enables investors to discern opportunities and anticipate risks, optimizing investment strategies accordingly.
AI’s utility extends to portfolio management, where it orchestrates optimized investment portfolios, dynamically adjusting to market dynamics while balancing risk and return. This systematic approach ensures portfolios remain aligned with investors’ objectives amidst evolving market conditions.
AI represents a paradigm shift in investment methodologies, offering unparalleled analytical capabilities and strategic insights. As stewards of capital, let us embrace this technological frontier with vigilance and adaptability, leveraging AI to enhance investment outcomes responsibly.
Quote of the week
‘AI will be the most transformative technology of the 21st century. It will affect every industry and aspect of our lives.’
— Jensen Huang, CEO, NVIDIA
That’s it for this week’s The Benchmark email.
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Invest in knowledge,
Thom
Editor, The Benchmark
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