Big Tech risk premium hits 23-year high as volatility surges
The spread between the Nasdaq-100 Volatility Index (VXN) and the CBOE Volatility Index (VIX) has reached 12 points, the widest gap in 23 years, signaling heightened uncertainty for AI-heavy tech stocks. Since early May, the VXN jumped 43% while the VIX rose only 9%, surpassing volatility spreads seen during the 2008 financial crisis and the COVID-19 pandemic. Major AI beneficiaries like NVIDIA and Microsoft are driving this divergence as investors weigh massive infrastructure spending against uncertain revenue timelines.

*this image is generated using AI for illustrative purposes only.
The spread between the Nasdaq-100 Volatility Index (VXN) and the CBOE Volatility Index (VIX) has widened to 12 points, the largest gap in at least 23 years, according to Bloomberg data highlighted by The Kobeissi Letter. This divergence has more than tripled since the start of May as technology-stock volatility has accelerated far faster than volatility across the broader market. The move suggests investors are pricing significantly more uncertainty into AI-heavy technology stocks than into the S&P 500, tracked by the SPDR S&P 500 ETF Trust (NYSE: SPY), and the broader market benchmark reflected in the Invesco QQQ Trust (NASDAQ: QQQ).
Since the beginning of May, the VXN has climbed roughly 43%, or about nine points, while the VIX has risen just 9%, or approximately two points. That widening gap is notable because previous market shocks — including the 2008 financial crisis and the COVID-19 pandemic — produced peak spreads of roughly 7 and 11 points, respectively. The current 12-point spread now exceeds both. Rather than signaling broad market panic, however, the divergence suggests investors are assigning a much larger risk premium specifically to technology stocks, particularly those concentrated in QQQ relative to the broader SPY benchmark.
Tech Volatility vs. Broader Market
| Metric | Current Move | Historical Peak (2008/COVID) |
|---|---|---|
| VXN (Nasdaq-100 Volatility) | +43% (approx. 9 points) | ~11 points (COVID) |
| VIX (CBOE Volatility) | +9% (approx. 2 points) | ~7 points (2008) |
| VXN-VIX Spread | 12 points | 11 points |
The Nasdaq-100, tracked by QQQ, is heavily weighted toward artificial intelligence beneficiaries, including NVIDIA Corp., Microsoft Corp., Apple Inc., Amazon.com Inc., Alphabet Inc., Meta Platforms Inc. and Broadcom Inc. Those companies have led the market higher over the past two years, helping lift both QQQ and, to a lesser extent, SPY, fueled by hundreds of billions of dollars in AI infrastructure spending. At the same time, investors continue to debate when those investments will translate into meaningful revenue growth, leaving valuations increasingly sensitive to earnings, guidance and AI adoption trends.
That uncertainty appears to be showing up in options markets, where traders are demanding significantly higher premiums to hedge technology exposure than the broader market represented by SPY. Historically, rising implied volatility has often been associated with investor caution. But elevated volatility can also accompany periods of strong market leadership, particularly when expectations are high and investors anticipate larger price swings around earnings, product launches or macroeconomic developments.
For long-term investors, the record VXN-VIX spread may therefore say less about the direction of the market and more about the concentration of expectations surrounding Big Tech and its outsized influence on QQQ versus SPY. The message from options markets is clear: Wall Street still believes technology will drive the market — but it also expects the ride to be considerably bumpier than it has for the broader S&P 500.
Could this record spread signal a potential rotation out of AI-heavy tech stocks into undervalued sectors of the S&P 500?
What specific earnings results or guidance from major tech firms are required to justify the current elevated risk premiums?
If the VXN-VIX spread begins to narrow, would this indicate a successful monetization of AI technologies or simply a loss of investor confidence?





























