How the Speed of a Trade Got Down to Nearly the Speed of Light
How the Speed of a Trade Got Down to Nearly the Speed of Light
68 days agoOdd LotsBloomberg
Podcast55 min 37 sec
Listen to Episode
Note: AI-generated summary based on third-party content. Not financial advice. Read more.
Quick Insights

Investors should focus on the "physical" side of trading by targeting exchange operators like NASDAQ (NDAQ), Intercontinental Exchange (ICE), and CME Group (CME), which capture consistent fees from the high-frequency trading arms race. To capitalize on the massive infrastructure requirements of AI, prioritize companies providing specialized data centers and high-speed communication hardware rather than just software developers. Be cautious of the "logarithm problem" in AI scaling, as the exponential increase in capital and electricity costs may soon lead to diminishing returns on investment. For cost-effective exposure to cloud infrastructure, monitor private innovators like Wasabi that offer significant price advantages over legacy providers. In the consumer finance space, Discover (DFS) remains a high-conviction play due to its near-universal merchant acceptance and ability to internalize technological efficiency gains.

Detailed Analysis

High-Frequency Trading (HFT)

• High-frequency trading is a machine-centered form of trading that exploits market structure and technical substrates rather than just identifying fundamental financial patterns. • The industry has transitioned from "human-perceptible" time (tenths of a second) to intervals as small as nanoseconds (one-billionth of a second). • Market Structure: Most HFT occurs on electronic order books managed by "matching engines" that pair buyers and sellers instantly. • The "Arms Race": - Firms compete to be the fastest to react to "stale" prices. - Example: When a stock index future price changes in Chicago, HFT firms race to update or execute against related stock prices in New Jersey. - This creates a feedback loop where firms must constantly invest in speed just to remain competitive.

Takeaways

Technological Advantage: Investment success in this sector is driven by "co-location" (placing servers in the same room as exchange engines) and specialized hardware (microwave links vs. fiber optics). • Liquidity Dynamics: HFT firms are generally split into two categories: - Market Makers: Provide liquidity by constantly populating the order book with bids and offers. - Liquidity Takers: Monitor the book and execute against existing orders when they spot a profitable discrepancy. • Diminishing Returns: While the speed race continues, the rate of acceleration is slowing because the costs of gaining picoseconds (trillionths of a second) are becoming harder to recoup from the finite pool of trading profits.


Artificial Intelligence (AI)

• AI and Large Language Models (LLMs) are the new frontier for technical investment, following a similar "arms race" logic to HFT. • Scaling Laws: The effectiveness of AI currently grows with the size of the network, the amount of training data, and the number of parameters. • The "Logarithm" Problem: Intelligence gains appear to be a logarithmic function of resources. This means that to get a linear increase in "intelligence," an exponential increase in capital, electricity, and data is required.

Takeaways

Capital Intensity: The industry is currently in a "scaling" phase where trillions of dollars are being spent on infrastructure. • Investment Risk: Investors should be aware of the "diminishing returns curve." There is a risk that the massive financial input (trillions of dollars) and environmental costs may not yield a proportional qualitative leap in AI capability (like AGI). • Existential Competition: Much like HFT, firms may continue to over-invest in AI not because the economics are perfect, but because "falling behind" is seen as an existential threat to the company.


Financial Intermediation & Infrastructure

• Despite massive technological leaps since the 1880s, the "unit cost" of finance (the cost to move and manage money) has not significantly decreased for the end-user. • Fee Capture: Efficiency gains from technology are often captured by the financial sector in the form of high salaries and management fees rather than being passed entirely to the general public.

Takeaways

Sector Pay: Finance remains an exceptionally high-paying sector because it successfully internalizes technological efficiency gains. • Infrastructure Opportunities: There is significant investment value in the "physical" side of trading, such as specialized data centers and high-speed communication lines (e.g., Spread Networks' specialized fiber routes or microwave tower networks).


Key Entities & Tickers Mentioned

NASDAQ (NDAQ): Acquired early electronic pioneers like Island and Instanet to modernize its matching engine. • New York Stock Exchange (ICE): Acquired Archipelago to compete with the speed of electronic communication networks (ECNs). • Chicago Mercantile Exchange (CME): A central hub for futures data that drives price movements in other markets. • Jane Street / Hudson River Trading / GetCo: Private HFT firms (often trading their own capital) that dominate the speed and liquidity landscape. • Wasabi: Mentioned as a provider of AI-enabled cloud storage at lower market costs (80% less than competitors). • Discover (DFS): Mentioned as having wide merchant acceptance (99% of US places).

Ask about this postAnswers are grounded in this post's content.
Episode Description
The average person can enter a stock trade on their computer, hit refresh, and the trade is done. As fast as that seems, there are professional traders moving even faster, executing thousands of trades per second. Over the years, the need for speed got so intense that competing firms would aim to get their own systems closer and closer to the exchange's computers, so as to minimize the length of the wires and get their trades in even faster. How did this happen? And how does this change the nature of trading itself? On this episode, we speak with Donald Mackenzie, a professor of sociology at the University of Edinburgh in Scotland. Professor Mackenzie has been studying the intersection of finance and tech for a long time, and in 2021 wrote the book, Trading at the Speed of Light. We discuss the history of finance technology and look at where the technological arms race is going next. Subscribe to the Odd Lots Newsletter Join the conversation: discord.gg/oddlots See omnystudio.com/listener for privacy information.
About Odd Lots
Odd Lots

Odd Lots

By Bloomberg

<p>Bloomberg's Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets and economics. Join the conversation every Monday and Thursday.</p>