They say in the world of trading, a millisecond is an eternity. I’ve seen it firsthand. Back in the early days of my career, a fast trade meant a guy in a colored jacket screaming across a pit. Now? It’s a pulse of light in a fiber optic cable, a decision made by an algorithm in the time it takes a hummingbird to beat its wings once. And in that pulse of light, fortunes are made and lost. High-frequency trading, or HFT, is the engine of this new world. It’s often painted as the villain, the shadowy force that rigs the game against the little guy. And honestly? Sometimes, it is. But the real story, like most things in tech and finance, is a lot more complicated.
I’ve been building and investing in tech companies for over two decades. I’ve had a couple of successful exits, and I’ve put my money into over 200 startups, including some of the biggest names in AI like Anthropic and OpenAI. I’ve seen how technology can be a massive force for good. But I’ve also seen its dark side. HFT is one of those areas where the line between innovation and exploitation gets real blurry, real fast. So let’s pull back the curtain and take a hard look at what’s really going on.
What is HFT, Really? (The 101 for the Uninitiated)
Forget the Hollywood image of a rogue AI taking over the world. HFT is simpler, and in some ways, more insidious. At its core, HFT is about using powerful computers and complex algorithms to execute a massive number of orders at insane speeds. We’re talking trades that last for a fraction of a second. The goal isn’t to make a huge profit on a single trade. It's to make a tiny profit on millions of them. It’s a game of pennies, played at the speed of light.
Think of it like this: you’re in a grocery store, and you see that a can of soup is priced at $1.00 in one aisle and $1.01 in another. You’d buy all the $1.00 cans and sell them for $1.01, making a penny on each. Now, imagine doing that a million times a second, across every grocery store in the world, all from the comfort of your server rack. That’s the core of many HFT strategies. They’re not making deep, insightful bets on a company’s future. They’re just exploiting tiny, fleeting price discrepancies.
To do this, they need two things: speed and proximity. Speed comes from the algorithms and the hardware. Proximity comes from something called “co-location,” which is a fancy way of saying they pay a premium to put their servers right next to the stock exchange’s servers. This shaves precious microseconds off their trading times, giving them a huge edge. It’s an arms race. The weapons are fiber optic cables and processing power.
The “Dark Side” - Where the Bad Press Comes From
So where does the villain narrative come from? It’s not entirely unearned. There are some very real concerns about how HFT impacts the market.
Front-Running: This is the big one. It’s the digital equivalent of a broker seeing you’re about to place a big order, buying up the stock just before you, and then selling it to you at a higher price. HFTs can do this on a massive scale. Their algorithms can detect large incoming orders and jump the queue. It’s a practice that’s supposed to be illegal, but the lines are so blurry they might as well not exist. I remember a few years back, I was looking to make a significant investment in a publicly-traded robotics company. We were careful. We broke up the order, tried to be discreet. But the price still ticked up just moments before our big blocks went through. We ended up paying a few million more than we should have. Did I have concrete proof it was an HFT firm front-running us? No. But I’ve been in this game long enough to know the smell. It’s the cost of doing business now, a tax you pay to the speed demons.s.
Market Destabilization (Flash Crashes): When you have a bunch of algorithms all following similar strategies, you can get some scary feedback loops. The most famous example is the “Flash Crash” of 2010. In the span of about 36 minutes, the Dow Jones Industrial Average plunged nearly 1,000 points, erasing almost a trillion dollars in market value, only to recover most of it just as quickly. The initial blame fell on a complex web of HFT algorithms all trying to sell at once, creating a cascade of selling pressure. It was a hell of a reminder that these systems, for all their sophistication, can spin out of control in terrifying ways.
An Unfair Advantage: This, for me, is the real kicker. The HFT arms race has created a two-tiered market. You have the high-frequency players with their co-located servers and their billion-dollar infrastructure, and then you have everyone else. The small-time retail investor, the pension fund, even a reasonably large investor like me – we’re all playing a different game. We’re on the dial-up modem while they’re on a dedicated fiber line. It’s not a level playing field. It’s a rigged game, and it makes a mockery of the idea of fair markets.
A Founder’s & Investor’s Perspective
I once invested in a fintech startup that was trying to use AI to democratize access to sophisticated investment strategies. They had a brilliant team, a great product, but they kept running into the HFT wall. Their models were smart, but they couldn’t compete on speed. They were trying to play chess while the HFTs were playing a high-speed game of rock-paper-scissors. That was a brutal lesson in how the very structure of the market can kill innovation before it even gets started.
This is the part that really gets me. As an angel investor, I’m in the business of funding innovation. I’m looking for companies that are building the future, creating real value. HFT, in so many ways, feels like the exact opposite. It’s not about building better companies; it’s about being a faster, more parasitic middleman. It’s a zero-sum game, or worse, a negative-sum game if you factor in the massive resources poured into the speed arms race. That’s money that could be going into R&D, into creating new products, into solving real-world problems.
It’s Not All Bad, Is It?
Now, it would be easy to just paint HFT as the ultimate evil and call it a day. But that’s not the whole picture. There are some arguments in favor of HFT, and they’re worth considering.
The main argument is liquidity. HFTs are always in the market, ready to buy or sell. This constant activity means there’s almost always someone on the other side of your trade. This constant activity narrows the “bid-ask spread”—the difference between the price someone is willing to pay for a stock and the price someone is willing to sell it for. A narrower spread is good for everyone. It’s a lower transaction cost. The billion-dollar question is whether that small benefit is worth all the costs and the systemic risk.
Some also argue that HFTs contribute to “price discovery” – the process of determining the correct price of an asset. By constantly reacting to new information and adjusting prices, they help the market reflect the true value of a stock more quickly. I’m not buying that one. Not for a second. Are they reacting to fundamental information about a company’s performance, or are they just reacting to the noise of other algorithms? I suspect it’s more of the latter.
The Road Ahead
So, what’s the answer? I don’t think we can or should try to ban HFT. The genie is out of the bottle. But we can and should do more to level the playing field and mitigate the risks. Things like a small financial transaction tax could discourage the most speculative, high-volume strategies. Implementing randomized, frequent batch auctions, where orders are collected over a short period (say, 100 milliseconds) and then executed at a single price, could neutralize the speed advantage. We need to think about market structure in a way that prioritizes long-term investment over short-term speculation.
As an investor in AI, I’m an optimist about technology. But I’m also a realist. I know that every new technology brings new challenges. HFT is a powerful tool, but it’s a tool that has been allowed to run wild, with its own incentives that are not always aligned with the health of the market or the economy. The dark side of HFT isn’t a myth. It’s a complex reality we need to confront with smart, thoughtful regulation. We can't turn back the clock to the days of screaming traders in pits. But we have to build a market that’s actually fair and stable. A market that does what it’s supposed to do: fund the real innovations that will actually build our future, not just skim pennies off the top.
Frequently Asked Questions
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.