Wall Street & the AI Bubble Debate: How AI Prompts May Help During Volatility

This Week’s Focus: The Anatomy of an AI Bubble

Michael Burry just bet $1 billion against the AI boom. The investor who famously shorted the housing market before its 2008 collapse disclosed in late September that Scion Asset Management had purchased put options against Nvidia and Palantir, two stocks now priced at levels even optimists call historic. Nvidia recently crossed the $5 trillion mark in market cap. Palantir trades at over 200x forward earnings.

The timing is striking. After months of relentless gains, the Nasdaq just posted its sharpest weekly slide since spring. Legendary investor Mark Mobius also warned that AI stocks could drop as much as 40%, citing excessive capital expenditures and inflated expectations. Yet he noted any correction might prove temporary, with capital rotating to undervalued emerging markets rather than fleeing tech entirely.

The AI story remains powerful, but so do the warning signs. Each technological leap, from dot-com to crypto, blurs the line between innovation and exuberance. The task now is separating conviction from crowd psychology.

And that's where structured prompting earns its value.

AI in Action: Using Structured Prompting to Read Market Cycles

The recent market turbulence offers a chance to see how AI can strengthen analysis, not by predicting prices but by organizing how we interpret them. The following prompt examples show how analysts can combine valuation, sentiment and behavioral data to spot signs of speculative stress before the market does.

📌 Prompt Example 1: The AI Bubble Question

Instead of asking, "Are we in an AI bubble?"—a question that invites opinion—a structured prompt dissects data, sentiment, and fundamentals to form a coherent view.

Example Prompt

Act as a market strategist analyzing AI-sector valuations. 

1. Retrieve current forward P/E, P/S and 12-month growth estimates for Nvidia (NVDA) and Palantir (PLTR) stocks. 
2. Compare each to its own historical averages and to sector benchmarks during the 1999–2000 and 2020–2021 peaks. 
3. Calculate the valuation premium: (Current multiple – Historical average) ÷ Historical average. 
4. Assess whether these premiums are supported by revenue growth above 25%, margin expansion or market-share gains. 
5. Present results in a concise table: Company | Valuation Premium | Fundamental Support (Yes / Partial / No). 
6. Estimate the implied growth rate required to justify current valuations and the downside risk if growth underperforms by 20%.

Provide references where applicable.

By separating retrieval from reasoning, this framework clarifies where valuation expansion stems from genuine productivity gains and where it reflects narrative momentum. The goal is not to call the top but to locate the fault lines between innovation capital and speculative capital.

📌 Prompt Example 2: Reading Behavioral Heat  

Valuations show excess, but sentiment shows timing, when optimism turns to euphoria. This second prompt helps identify the emotional contours of a bubble before data confirms it.

Example Prompt

Act as a behavioral finance researcher. 

1. Retrieve recent sentiment indicators for artificial intelligence (AI) stocks, but specifically Nvidia (NVDA) and Palantir (PLTR) stocks. These indicators should come from public sources such as Google Trends, Reddit discussions and retail trading data. 
2. Identify common media and analyst phrases that reflect euphoric language (for example, “can’t lose,” “inevitable,” or “paradigm shift”). 
3. Compare current sentiment intensity with the market peaks of March 2000 and November 2021 using historical sentiment or volatility indices. 
4. Review current analyst consensus: percentage of “Strong Buy” ratings versus “Hold” or “Sell,” and note whether bullish concentration has increased since April 2025.
5. Summarize findings in a “Sentiment Heat Index” (0–100) with a short interpretation of how current enthusiasm compares with past cycles. 
6. Conclude whether today’s tone signals early-stage optimism, late-cycle euphoria or neither.

By prompting for behavioral signals, not just valuation metrics, analysts learn to map emotion as data; a key advantage when markets are driven by narrative momentum.

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Prompting the Three-Dimensional Bubble Framework

Bubbles rarely form from valuation alone. They appear when fundamentals, sentiment, and policy align in the same direction. This framework helps analysts gauge how these forces interact and whether enthusiasm rests on evidence or narrative.

Combined Prompt

Analyze [SECTOR] across these three dimensions.

Valuation: Compare current multiples to the five-year range. What must go right for prices to hold?

Behavior: Gauge sentiment concentration. Are investors positioned for perfection?

Policy: Identify upcoming regulatory or geopolitical risks and estimate their likely impact.

Output: Create a simple risk matrix — Green (0–1 dimensions elevated), Yellow (2), Red (all 3).

This multidimensional view shows how valuation, behavior and policy pressures can converge. It would have flagged the 2021 SPAC boom early, when all signals turned red and the sector fell about 70% in nine months.

Bottom Line

AI is transforming industries, but exuberance is testing discipline. Structured prompting combines valuation, behavior, and policy insights to separate sustainable growth from speculative momentum.

The goal is not to predict when exuberance ends but to stay rational when others do not. And in a market this emotional, that is an edge algorithms alone cannot replicate.

Thank you for reading AI in Investment Research & Finance. Here’s to spotting tomorrow’s market stories today.

Until next time!