Markets, at their core, are information systems. They aggregate the collective knowledge, expectations, and preferences of market participants in a price which functions as an exchange ratio. In equities trading, each trade contemplates the exchange of a certain amount of money for a title of ownership to some amount of capital goods. Price discovery, the mechanism through which markets reveal this information, is essential for economic calculation and resource allocation. But what happens when markets operate with less liquidity, fewer participants, or, increasingly, automated systems? The rise and fall of night trading two decades ago offers an opportunity to revisit that question, as its recent resurgence prompts a critical examination of whether these extended sessions foster meaningful price discovery, or merely act as a superficial exercise in keeping markets open for longer.
Lessons from the Past
By mid-1999, a frenzied period of financial innovation and financial market enthusiasm had reached a fever pitch. Dot com stocks were roaring as the first wave of online retail trading took shape. With retail investors eager to trade stocks outside regular sessions, night trading seemed destined to become the next big thing. In the midst of what was described as a democratization of market access, the idea was seductive: why should markets close when global events continue to unfold and investors have the tools to react?
Yet when the bear market began in March 2000, the bloom quickly came off the rose. Liquidity dried up, volumes collapsed, and overnight trading fell into disuse. What professional traders already knew was discovered by retail customers: when prices fall, hobbyist traders lose interest. And in those increasingly thinly-traded markets, prices lose their ability to reliably convey information. Instead of reflecting broad consensus or meaningful activity, prices in illiquid markets become noisy, volatile, or outright misleading.
Night Trading Resurgent
Today, after-hours trading is making a comeback, driven by several structural changes in markets. First, trading volume has exploded over the last decade as equity ownership has broadened and barriers to access have fallen. Commission-free trading platforms, fractional shares, and app-based brokers have dramatically lowered barriers to accessing markets, a trend that accelerated during the pandemic. With more participants willing and able to trade at all hours, extended sessions are likely to command greater liquidity than they did two decades ago.
It goes without saying that we are also in the midst of a powerful bull market, with the S&P 500 up nearly 70 percent from late 2022 to late 2024. Rising markets attract trading activity, and investors are eager to capitalize on any perceived advantage—including the ability to trade before the regular session opens or after it closes. Unlike the dot-com era, when the post-4pm EST session quickly became a relic of exuberance, today’s environment reflects both a surge in volume and an unprecedented ease of access to capital markets. Part of that has been propelled by the arrival of cryptocurrency trading, the first truly 24/7 asset class.
Perhaps most importantly, and just like nearly every change over the past thirty years: technology has fundamentally altered the equation. In the past, extended hours trading was limited by constraints that now sound almost quaint: Who’ll staff the desk? How do late trades clear? And will the revenue justify the costs?
Today, those barriers have been all but eliminated. Algorithmic trading and AI-driven systems can operate seamlessly around the clock, managing orders, matching trades, and maintaining liquidity with little human oversight. For financial institutions, automated systems make overnight trading operationally feasible. But this raises a deeper question: Does “intelligent” automated trading foster meaningful price discovery, or does it merely “babysit” markets?
Price Discovery or Noisemaker?
Price discovery depends on liquidity, diversity of market participants, and informed trading. In regular sessions, those conditions are met because markets are flooded with buy and sell orders from large financial institutions, hedge funds, and retail investors—all with varying motivations for trading, responding to news and fundamentals with arrays of strategies. After-hours markets, by contrast, remain thin relative to daytime sessions. While algorithms can provide liquidity, much of this trading occurs through limit orders, which are pre-set to buy or sell at specific prices rather than responding dynamically to new information. Those dynamic responses to market conditions will tend to be driven by risk parameters as opposed to trading instincts, market consensus or economic shifts. Overnight markets may simply become mechanical, driven by automated systems executing trades without meaningful intent.
Algorithms might place bids and offers to minimize spreads or capitalize on arbitrage, but those frequently lack the kind of informed judgment that underpins true price discovery. News released after the normal market close might prompt overnight trading, but with fewer participants and thinner liquidity, prices can become exaggerated or unstable. When regular trading resumes, these overnight movements often reverse, suggesting that after-hours prices were, at best, provisional guesses.
That dynamic raises important questions for investors, financial managers, corporate executives, economists, and policymakers alike. Can overnight markets reveal significant information if they are dominated by algorithms rather than active decision-makers? Prices in markets are used for everything from fund weightings to corporate actions and investment banking. If automated systems are merely maintaining order flow and matching trades for eight or ten hours, do the resulting prices represent anything more than placeholders? And if price discovery is impaired, does this undermine the broader function of markets as tools for economic calculation?
The Broader Implications
The resurgence of after-hours trading reflects both the opportunities and limitations of modern markets. On one hand, extended trading offers flexibility for participants, providing a way to respond to global events or economic data released outside regular sessions. On the other, less liquid and more automated markets run the risk of producing prices that distort, rather than reveal, underlying economic signals. For now, the volume and interest in extended trading are growing, but whether indicative price discovery can be generated remains uncertain. Generating commission revenue and responding to client demands is something all firms can and should do, but will prices after 5pm and before 8am carry any significance? Does extending market hours create a two-tiered market of more versus less information-fueled trading?
A quarter of a century after the dot-com era flirtation with after-hours trading that was carried aloft by such firms as Market XT and Wit Capital, new firms are filling those roles. While learning technology can keep the machinery of markets running, true price discovery requires more than automated systems. It requires a diversity of informed participants acting on new information—the very conditions that regular trading sessions provide. As extended trading hours expand, we must consider whether we are revealing new insights or merely babysitting the markets until the real price discovery begins.
Peter C. Earle, Ph.D is a Senior Economist covering financial markets and monetary policy at the American Institute for Economic Research (AIER).
FLASH FRIDAY is a weekly content series looking at the past, present and future of capital markets trading and technology. FLASH FRIDAY is sponsored by Instinet, a Nomura company.
