Where is the safe haven really located? | Conversation with Economist Zhu Ning

Source: CITIC Press This article is a condensed version from the podcast “Hedging Not Profiting”

Tariffs fluctuate, geopolitical conflicts erupt, shadow banking collapses, AI disrupts traditional industries—these events, just a year ago, were considered low-probability “tail risks”; now, they hang like the Sword of Damocles over every ordinary person.

Carrying these pressing questions of the era, host Jeff of the podcast “Hedging Not Profiting” engaged in an in-depth conversation with Professor Zhu Ning, Vice Dean of Shanghai Advanced Institute of Finance at Shanghai Jiao Tong University and author of “Rigid Bubbles.” They used Nassim Nicholas Taleb’s classic works “The Black Swan” and “Antifragile” as intellectual coordinates, attempting to sketch a cognitive blueprint and survival strategies for turbulent times.

We Are No Longer in the “Average Stain”

In Taleb’s context, “Average Stain” refers to data like height and weight—individuals cannot significantly influence the overall. “Extreme Stain,” by contrast, emphasizes “winner-takes-all”: putting Elon Musk’s hundreds of billions into a sample of ordinary Shanghai residents with millions, the average wealth instantly jumps by an order of magnitude. In this realm, seemingly rare “black swans” are the true rulers, even determining the course of history.

Professor Zhu Ning points out that three powerful waves of the era are making this “extreme stain” omnipresent.

First, the deep resonance of globalization. In the Age of Discovery (16th-17th centuries), a plague might only affect a city; in 2020, COVID-19 swept the globe in two months. Today, a blockade of the Strait of Hormuz can trigger chain reactions in global energy and food supply chains within days. Globalization makes vulnerabilities transmit faster and more fiercely than ever before.

Second, the explosive compounding of technology. Human average lifespan has extended from less than 40 years in 1900 to over 70 today, forcing more people to leverage risk for financial support in later life. The AI revolution, while causing mass layoffs of “screwdriver” workers, hires top researchers at sky-high salaries, further intensifying the winner-takes-all landscape.

Third, the high-frequency oscillations of political order. A leader’s governing style is reshaping the global financial, economic, and trade order in unprecedented ways.

Professor Zhu Ning, in his book “Rigid Bubbles,” has long warned: under implicit government guarantees, people treat risky assets as safe assets. Once sentiment shifts, exposed risks can be deadly.

You’re Not a Turkey, But You Live Like One

Why do humans, battered repeatedly, keep stumbling into risks?

In “The Black Swan,” Taleb tells a brutally cruel metaphor: a caged turkey is fed and cared for gently for 1,000 days, leading it to develop immense confidence in the future. But on the 1,001st day—Thanksgiving—it’s slaughtered.

Professor Zhu Ning points out that behind this “turkey” is a deep-rooted human “confirmation bias” and “narrative fallacy,” and the deeper reason is: “The evolution speed of the human brain far outpaces the complexity of modern society.”

First, herd instinct. On the ancient African savannah, not following the herd often meant death; the genes of outsiders had long been eliminated by natural selection. Jeff bluntly explains in the podcast: “It’s in our genes to herd. Because in ancient times, if you wanted to hunt an elephant, going to extremes in stain wouldn’t matter to you.” Humans are naturally more willing to accept the “average stain” and not proactively consider extreme events that could change their fate.

Second, the mismatch of fast and slow systems. Kahneman’s research shows that human thinking involves “fast” and “slow” systems, and most of the time, we rely on the “fast” system—intuition, experience, “everyone’s doing it.” These biases are not born for modern society but are embedded in our genes from billions of years of evolution for species survival.

Third, survivor bias and silent evidence. During WWII, the British analyzed returning aircraft’s bullet holes, mainly on wings and tails, and planned to reinforce those areas. But a statistician pointed out: “You’re looking at the wrong targets. The planes hit in these areas are the ones that returned; those hit in the cockpit and fuel tanks never came back.”

To avoid spending the first 1,000 days like a turkey, we need to recognize two realities:

First, the world is extremely complex, and our understanding is very limited—if even Nobel laureates and top Wall Street traders blow up their funds, why should ordinary people predict future rises and falls accurately?

Second, always be alert that your “positions” are distorting your judgment—use Taleb’s words: make extreme assumptions without mercy: if something terrible happens, can I survive?

Expert Predictions Are Less Reliable Than Monkey Darts?

If even our brains systematically deceive us, is relying on “expert forecasts” even more unreliable?

“We economists are not good at predicting; we are good at explaining,” Zhu Ning jokes in the podcast, “and we’re best at explaining why our predictions are always wrong.” Jeff adds a harsher fact: Wall Street tests show that sell-side analysts’ prediction accuracy is about as good as chimpanzees throwing darts, sometimes even worse.

Taleb’s own attitude is even more radical. He highly admires philosopher Karl Popper—Popper’s core idea: “All supposed facts can be overturned or changed overnight.” This is the philosophical foundation of Taleb’s thinking.

The most compelling evidence comes from the Long-Term Capital Management (LTCM) case. This firm gathered Nobel laureates, former Fed officials, and top Wall Street traders, confidently claiming: “According to our risk control models, the chance of losing 50% of assets in a month is one in a million.” Yet, a year later, the firm went bankrupt.

So, if expert predictions are so unreliable, why does this industry still exist?

Zhu Ning offers a thought-provoking answer: the process of logical thinking still has value; the direction of prediction matters more than precision. The Club of Rome’s “Limits to Growth” (1970s) predicted disasters that did not materialize as expected, but it spurred global environmental awareness and sustainable development efforts.

“Big research still matters because it points everyone roughly in the right direction,” Zhu Ning says, “but you must never think your forecast is correct.”

How Can Ordinary People Build an “Antifragile Barbell”?

Since predictions are doomed and black swans are constant companions, what should ordinary people do?

The answer, distilled from Taleb’s “The Black Swan” and “Antifragile,” is two words—“Redundancy.”

Jeff and Professor Zhu Ning also summarized their framework from these books: “The Black Swan” is “defense”—the core is survival, avoiding losses, and not getting slaughtered; “Antifragile” is “offense”—benefiting from adversity and growing through volatility.

In a nutshell: “The Black Swan” teaches you “how not to be knocked down,” while “Antifragile” teaches you “how to bounce higher after being knocked down.” The central strategy running through both books is the “barbell strategy”—abandoning the comfortable middle ground and allocating all assets at both ends of the barbell.

How to protect the conservative end? Embrace “boredom,” refuse to lose money.

Better to give up high returns than to risk principal safety through any cycle. He quotes Buffett’s two risk control maxims: “Never lose money,” and “Always remember the first.”

Taleb also said more vividly: “I spend most of my time thinking about what could kill me, and then I spend the second most time thinking about how to avoid those places.” Indeed, Taleb himself practices this—he regularly buys out-of-the-money options, “buying insurance” at low cost, and profits from black swans when they arrive, as in 1987’s “Black Monday” and the 2008 financial crisis.

So, how to safeguard the aggressive side of the barbell? The answer: be the 1% of “extreme stain.”

The conservative side ensures you “stay alive”; the aggressive side uses small capital to seek huge or even outsized gains, profiting from chaos when black swans strike.

It’s crucial to note an extremely important boundary condition—this is the most overlooked critical perspective in this podcast.

Zhu Ning emphasizes: “I have a slight difference in opinion with Taleb: he is already financially free, so he can allocate assets as he imagines. When he gets low returns or buys insurance contracts, he has the money to do so. Not every novice has this luxury.”

Jeff adds: “Taleb himself is a former options trader, very familiar with derivatives and tools for guarding against extreme events. And in developed markets, these tools are quite accessible. But in the current A-share market, there aren’t many options for shorting.”

In other words, Taleb’s strategy is more of an ideological guide than a ready-made “homework.” For ordinary people, a more pragmatic approach is: a mental shift—not suddenly going from conservative to reckless, but gradually opening thresholds and exploring new things.

Jeff shares a vivid cautionary tale to emphasize “liquidity”: “I have a client who bought 700k yuan worth of ETFs, only to find he bought into the top ten shareholders of that ETF. The fund only has a total of 100 million yuan, so his 700k yuan made him the ninth-largest shareholder. When he tries to sell, he might find no counterparties.”

Perhaps a relatively universal, low-cost entry method is to buy diversified broad-market ETFs—keeping pace with the market and effectively avoiding individual stock pitfalls. Focus on funds with larger scale, higher liquidity, complete licenses, good ratings, and comprehensive ETF layouts.

These seemingly “boring” details are often the key to surviving storms intact.

Epilogue: Don’t Use Yesterday’s Map to Navigate Tomorrow’s Road

At the end of the conversation, Professor Zhu Ning summarized the core ideas of “The Black Swan” into three levels:

Cognitive—recognize the world’s complexity and your own limited understanding;

Action—leave yourself redundancy, adopt the barbell strategy;

Macro—policy makers should avoid encouraging leverage or excessive resource concentration among the populace.

For ordinary asset holders, the insights from this conversation can be summarized into four points:

First, re-examine your “certainty.” Anything you think “cannot happen” might become reality tomorrow. When you start believing “this time is different,” beware—this is often the most dangerous signal of risk.

Second, abandon “all-in” thinking. The essence of the barbell strategy is to ensure survival in any extreme scenario: debt not exceeding repayment capacity, assets not concentrated in a single asset, and not relying on just one skill or industry.

Third, learn to embrace “boredom.” In the era of extreme stain, not losing money is itself a victory. Those “boring” safe assets are the true havens in storms.

Fourth, reserve ammunition for offense. The flip side of black swans is opportunity. When others panic, those prepared can profit from chaos.

Finally, Jeff concludes with a succinct remark: “The world is full of unpredictable, destructive risks. Don’t be overconfident, and never expose yourself to deadly tail risks.”

In a world where black swans have become the new normal, the greatest danger is not risk itself, but still navigating with yesterday’s map, trying to find tomorrow’s way.