# Transcript: Featured Session: A Conversation with Andrew Ross Sorkin on the 1929 Financial Crash —  and Today's Economy

**Date:** March 15, 2026 · 10:00 PM  
**Session:** [Featured Session: A Conversation with Andrew Ross Sorkin on the 1929 Financial Crash —  and Today's Economy](/sessions/2026-03-15/pp1149739-featured-session-a-conversation-with-andrew-ross-sorkin-on-the-1929-financial-cr)

## Summary

This session features Andrew Ross Sorkin discussing parallels between the 1929 financial crash and today's economy, drawing insights from his book. He explores the role of technology, speculative bubbles, human behavior, and regulatory challenges, highlighting how historical patterns of market exuberance and fear resonate with current trends in AI and financial innovation.

## Topics

`1929 financial crash` · `economic history` · `artificial intelligence` · `market bubbles` · `financial regulation` · `speculation` · `technology impact` · `journalism` · `prediction markets` · `geopolitics`

## Key Takeaways

1. Economic history offers crucial lessons: understanding past financial crises, like 1929, can illuminate current market dynamics and potential risks, especially concerning new technologies and speculative behavior.
2. Be wary of market exuberance and 'democratization of finance' rhetoric, as historical examples show how easy credit and FOMO can lead to unsustainable bubbles and significant personal losses.
3. While AI presents transformative opportunities for productivity and entrepreneurship, its rapid development also introduces economic uncertainties, including potential job displacement and the risk of investment-revenue mismatches.
4. Effective financial regulation is critical: the aftermath of the 1929 crash led to vital reforms like the SEC, and current trends in tokenization and prediction markets highlight the ongoing need for transparency and oversight to prevent future crises.
5. Maintain a skeptical but optimistic outlook: despite recurring periods of economic anxiety and potential bubbles, history suggests that long-term progress often favors optimism, though painful transitions for individuals and industries are inevitable.

## Full Transcript

Andrew Ross Sorkin explains that he wrote his book on the 1929 financial crash because people often asked him to compare it to the 2008 crisis, and he realized he didn't have good answers. He didn't truly understand what happened in 1929 beyond a vague notion of something very bad occurring. About a decade ago, he began researching, becoming captivated by the period and, more importantly, the characters involved, whose stories he felt had not been fully told.

While writing the book, Sorkin found himself reporting on the contemporary economy and experiencing a sense of déjà vu, noting striking similarities between the past and present. This unintentional parallel made the book even more relevant, as many aspects of the 1929 era felt eerily familiar to today's economic climate.

There's a pervasive sense of impending doom today, whether it's due to AI, geopolitics, or other factors, which mirrors the anxieties of the past. Sorkin questions if this is inherent human nature or if current circumstances are demonstrably different. He believes the present moment, with its technological advancements in AI and geopolitical tensions, certainly lends itself to such concerns.

The 1920s also experienced an extraordinary technological revolution with automobiles and radio, generating immense excitement. While there were few 'Cassandras' back then compared to now, the current complexity is higher. Today, there's a dual concern: will the AI bubble pop and destroy the economy, or will AI's success also disrupt the economy in unforeseen ways?

A key example from 1929 was RCA, whose ticker symbol was 'Radio.' This was a leading stock, and people were enamored with it, believing it represented the future. RCA also held patents for television, indicating it wasn't a fundamentally bad company.

The primary problem in 1929, differing from today, was the extraordinary level of margin trading. People could put down a dollar and borrow ten from a broker, leading them to invest far beyond their means and understanding. When the market dropped 50% in late 1929, most couldn't hold on, leading to brokers seizing assets.

Interestingly, by the end of 1929, the stock market was only down 17% from its peak, but most people couldn't endure the initial steep decline to even reach that point. This highlights the devastating impact of over-leveraging and the inability to withstand market volatility.

Beyond just stock prices, the 1920s saw trading become a significant part of pop culture, much like today. Financial titans and industry leaders, previously overshadowed by athletes or politicians, began appearing on magazine covers, symbolizing a shift in public fascination. The phrase 'democratize finance' was also used, as everyone sought a 'lottery ticket' opportunity.

The market's rapid ascent fueled this frenzy; from early 1928 to September 1929, the stock market rose 90%. This created a powerful sense of FOMO (fear of missing out), drawing people from across the country to big cities, eager to get rich quickly before the opportunity vanished.

The book highlights intriguing characters, such as Winston Churchill, who, before becoming Prime Minister, was nearly broke and got caught up in the market's allure. He made and lost millions during the 1929 crash, even being present at the New York Stock Exchange on Black Thursday.

Other notable figures included Mike Mehan, the specialist trader for RCA, who became a celebrity, and Evangeline Adams, an astrologer with an office at Carnegie Hall. Bankers, including J.P. Morgan, consulted her for stock advice, and she had a newsletter with 100,000 subscribers, illustrating the era's speculative fervor.

Technological limitations also played a role in the 1929 crash. Stock prices displayed on exchange boards were often hours behind real-time, causing confusion and panic. People would physically go to the exchange to get information, leading to widespread, uninformed selling.

Savvy traders, like Jesse Livermore, employed elaborate systems, paying staff to relay real-time numbers from the exchange floor to gain an advantage. Wealthy investors also formed 'pool operations,' essentially pump-and-dump schemes, often paying journalists to talk up stocks, which the public knew about but still tried to ride the wave.

This transparency of manipulation, where the public was aware of schemes but hoped to get in and out before the collapse, is reminiscent of recent phenomena like GameStop. Sorkin notes that journalists trying to warn people during such periods are often met with resistance, with the public feeling they are being protected from opportunity rather than risk.

The concept of real-time market data is surprisingly modern; even in the late 1990s, it was a significant feature of online brokerages. In 1929, most people traded without constant data, and the first mutual funds were just beginning to emerge.

John Raskob, a key figure of the era, transformed credit in America by introducing installment plans for General Motors cars, making credit socially acceptable and expanding consumer markets. He also proposed a mutual fund and is credited with advocating for the five-day work week and moving holidays to Mondays to boost consumer spending.

The difficulty of 'ringing the bell' (calling a market top) was evident in 1929, as even prominent figures like Charles Merrill (of Merrill Lynch) were ridiculed for warning people to exit the market before its final 90% surge. Regulators, including the Federal Reserve, were hesitant to act decisively, fearing they might trigger a recession.

Journalists and money managers face similar challenges; the incentive for money managers is to beat the index, not to be overly conservative and get fired for missing gains. This herd mentality often leads to following others 'down off the cliff' rather than acting as an early warning.

The conversation shifts to AI, noting a recent change in perception from 'AI is a bubble' to 'AI is transformative, potentially destructive.' While there's concern about over-investment in data centers and private credit, the long-term impact on employment and the potential for AI to move to 'the edge' (personal devices) remain uncertain.

The 1929 crash itself was not preordained to become the Great Depression; it was the initial domino that eroded confidence. The subsequent period of austerity, President Hoover's tariffs (which drastically cut trade), and the Federal Reserve's inaction exacerbated the crisis, lessons that were applied in 2008 and during the pandemic.

The aggressive monetary injection during the COVID-19 pandemic led to a rapid economic recovery but also significant inflation, which, despite full employment, was met with public discontent. This highlights the complex trade-offs in economic policy responses.

Despite numerous global shocks in recent years—COVID, trade wars, actual wars, supply chain disruptions, and AI anxiety—the economy has shown remarkable resilience. However, current events like the Red Sea closure pose a significant test, particularly regarding energy prices.

Regarding tariffs, Sorkin notes that while journalists warned of dire consequences from Trump's initial proposals, the market didn't collapse because policies were often shifted or softened. CEOs, while privately critical of chaotic policies, often keep quiet due to fear of government retaliation and the desire to maintain business relationships.

Sorkin discusses AI's role in journalism: while not used for writing articles due to hallucination risks, it's invaluable for internal tasks like calendar management and email. He envisions AI transforming reporting by handling background research and drafting, allowing journalists to focus on human interaction and original information gathering.

He also reflects on his own book research, where he manually digitized thousands of archival documents. Today, AI could revolutionize historical research by processing vast corpora of non-digitized files, identifying connections, and accelerating the research process for historians.

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*Source: stt · Language: en · Model: google-vertex/gemini-2.5-flash*

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