The Ghost of 1987: Lessons from NTT and the Perils of the Mega-IPO Boom

By Barry Eichengreen
July 3, 2026

The global financial markets are currently gripped by a fervor not seen since the dawn of the internet age. A wave of “mega-IPOs”—massive public offerings for companies at the vanguard of Artificial Intelligence, orbital logistics, and deep-space infrastructure—has unleashed a torrent of speculative enthusiasm. As retail and institutional investors alike pile into these offerings, the discourse has predictably turned toward historical parallels. Analysts and pundits are searching for a map to navigate this uncharted territory, drawing comparisons to the railway mania of the 1870s or the electrification boom of the 1890s.

Yet, while these grand historical narratives are seductive, they often obscure the nuances of market cycles. There is, however, one specific, apposite, and profoundly sobering case study that warrants immediate attention: the Initial Public Offering of Nippon Telegraph and Telephone (NTT) in February 1987.

The Context: When Giants Walked the Earth

To understand the current market volatility, one must look back to the mid-1980s, a period defined by Japan’s meteoric rise as an economic superpower. NTT, the state-owned telecommunications monopoly, was the crown jewel of the Japanese corporate sector. Its privatization was not merely a financial event; it was a symbol of Japan’s technological and economic dominance.

When NTT hit the Tokyo Stock Exchange in 1987, it was the largest IPO in history up to that point. The sheer scale of the offering sucked liquidity out of the broader market, creating a “winner-take-all” dynamic that mirrors today’s AI-centric market concentration. Investors, convinced that NTT held the keys to the future of global communications, bid the price to astronomical levels. What followed was a cautionary tale of how institutional exuberance, when detached from valuation reality, sets the stage for systemic fragility.

Chronology of a Market Fever

The trajectory of the late 1980s provides a roadmap for how mega-IPOs can distort the economic landscape:

• 1985–1986: The Buildup. A period of loose monetary policy and high corporate savings in Japan fueled a massive expansion in the stock market. Technology was the narrative driver, much like AI is today.
• February 1987: The NTT IPO. The offering was priced at 1.197 million yen per share. Demand was so overwhelming that the government had to conduct a lottery for shares. The stock price doubled in the first month.
• Late 1987: The Peak. By the autumn of 1987, NTT’s market capitalization accounted for a staggering portion of the entire Tokyo Stock Exchange. The company was worth more than the entire German stock market.
• 1988–1990: The Slow Erosion. As the speculative bubble stretched, the underlying fundamentals of the Japanese economy began to fray under the weight of excessive leverage.
• 1990: The Collapse. The bubble burst. The Nikkei 225 entered a decade-long decline, and NTT’s share price plummeted, wiping out the paper wealth of millions of individual investors who had entered the market at the peak.

Supporting Data: Valuation vs. Reality

The primary lesson of the NTT era is the danger of "narrative-driven valuation." In 1987, NTT was a utility company with a massive moat, but its price-to-earnings (P/E) ratio defied all conventional metrics. It was trading at multiples that assumed infinite, uninterrupted growth—an assumption that rarely survives the friction of economic reality.

Today’s mega-IPOs in the AI sector exhibit similar traits. We are seeing companies with minimal revenue streams being valued at hundreds of billions of dollars based on "Total Addressable Market" (TAM) projections that assume total sector dominance.

Comparative Market Metrics

The data suggests that when a single entity—or a small group of entities—captures the majority of investor capital, the rest of the market begins to starve. This leads to an "innovation gap" where smaller, potentially more disruptive firms cannot access capital because the "mega-caps" have monopolized investor attention and liquidity.

Official Responses and Regulatory Concerns

Central banks and regulatory bodies have begun to voice cautious concern, though they remain largely reactive. In 1987, the Bank of Japan was slow to curb the speculation, fearing that any attempt to cool the market would trigger a premature recession. Today, the Federal Reserve and the European Central Bank face a similar dilemma.

Official communiqués from recent G7 economic summits indicate a growing unease regarding the "concentration of systemic risk." Regulatory agencies in the UK and the US are now pushing for more rigorous disclosure requirements for pre-IPO AI startups. They argue that the complexity of these new infrastructures—specifically the energy consumption and the reliance on proprietary hardware—creates "black box" risks that current financial reporting standards are ill-equipped to measure.

The concern is that if a "Mega-IPO" were to fail, the secondary effects on institutional pension funds and sovereign wealth funds would be catastrophic. The regulatory consensus is shifting from "market efficiency" to "market stability," with many officials quietly preparing for a potential "correction event" to avoid the contagion that followed the Japanese bust of the 1990s.

Implications for the Modern Investor

What does this mean for the current market cycle? The implications are three-fold:

1. The Trap of the "Infrastructure Moat"

Investors often mistake the necessity of infrastructure for the profitability of the company providing it. Just because the world needs AI compute power doesn’t mean that the companies providing it will be able to maintain high margins indefinitely. As seen with NTT, even a near-monopoly can be a poor investment if the entry price is too high.

2. The Liquidity Siphon

Mega-IPOs are "liquidity black holes." They absorb the capital that would otherwise fund secondary and tertiary innovation. We are already seeing signs of "funding winter" in early-stage startups that do not have an "AI" suffix in their business plans. This is a classic symptom of a late-stage bubble.

3. The Necessity of Mean Reversion

History suggests that when a stock reaches a valuation that exceeds the collective economic growth of its sector, a reversion to the mean is inevitable. Whether this happens via a "soft landing" (a long period of stagnant prices allowing fundamentals to catch up) or a "hard crash" depends on the macroeconomic environment and interest rate trajectories.

Conclusion: Avoiding the "Nippon Trap"

The railway boom of the 1870s took decades to realize its value, and the electrification boom of the 1890s unfolded over a generation. Investors who treated these as "get rich quick" schemes were wiped out, while those who held for the long term eventually saw the technology transform the world.

The NTT experience of 1987 teaches us that the timing of an investment is just as important as the quality of the technology. We are currently in the midst of a massive technological transition—one that will likely define the 21st century. However, we must be careful not to mistake the excitement of the IPO for the maturation of the industry.

As we look toward the remainder of 2026, the watchword should be skepticism. While AI and space travel are undoubtedly the future, the price at which one buys into that future matters. If we ignore the lessons of the NTT IPO, we risk repeating the mistakes of the past, turning a period of unprecedented human innovation into a cautionary tale of financial excess.

Investors would be wise to look beyond the hype, scrutinize the balance sheets, and remember that even the most revolutionary technologies are subject to the cold, hard laws of supply, demand, and valuation. The ghost of 1987 is not a warning against progress, but a warning against the hubris of assuming that the laws of economics have been suspended.