AI-related Stocks Diverge, Travel and Shared Economy Rebound

Overview

This report focuses on the trading landscape of the internet sector in late May 2026. The core viewpoint is that the market is shifting from 'broad bet on AI' to more refined stock selection logic. Although top tech stocks represented by Google and Meta are under pressure due to excessive valuations, travel services (e.g., Booking Holdings), shared mobility (e.g., Lyft), and certain high-short-interest ratio companies have shown strong rebound momentum. The report points out that there is widespread doubt in the market regarding whether non-giant companies can truly benefit from artificial intelligence, leading to structural rotation of funds across sectors. The study reveals this divergence through multi-dimensional data (price performance, valuation multiples, short interest ratios, historical mean comparisons) and emphasizes the need to pay attention to the matching degree between fundamental improvement and valuation rationality.

Core views

First, the report points out that as of May 22, the entire internet sector averaged a decline of 1.5%, with digital advertising companies performing the worst, down by -2.8%. This was mainly driven by declines in Google (GOOGL) and Meta (META), which fell 3.5% and 0.6% respectively, especially the decline of Google far exceeding its historical average. However, the market is not entirely pessimistic. The travel services sector (e.g., Booking Holdings, BKNG) recorded a 4.5% weekly gain, becoming the biggest winner; the sharing economy sector (e.g., Lyft, LYFT) also rose 7.2%. In addition, some companies that were heavily shorted previously saw dramatic rebounds; for example, LYFT had a short interest ratio as high as 23.0%, but its stock price surged 7.2% within a week, showing strong short-covering momentum. The report specifically points out that although Amazon (AMZN) gained only 0.8% in a week, its one-year performance (+15.4%) and five-year average valuation (13.3x EV/EBITDA) still show strong long-term resilience. Regarding valuation levels, using Google, Amazon, and Meta's NTM EV/EBITDA multiples as an entry point, the report found that current valuations are significantly higher than their 2-year (13.0x, 13.3x, 12.6x) and 3-year (13.2x, 13.3x, 12.0x) averages, with Google having a valuation premium as high as 39% (relative to the 3-year average), reflecting extremely high market expectations for future growth, but also planting seeds for potential pullback risks. In comparison, although valuations for companies like Pinterest (PINS) have increased, the sustainability of their profitability remains a key consideration factor.

Analysis framework

Morgan Stanley adopted a multi-dimensional quantitative analysis framework to evaluate the trading landscape of the internet sector. The core of this methodology is to decompose complex market phenomena into quantifiable indicators to reveal trends through horizontal comparison and vertical tracking. Specifically including: 1. **Horizontal Comparison**: Comparing market cap-weighted average performance across different sub-industries (such as digital advertising, e-commerce, travel) to identify leading rising and falling sectors. 2. **Vertical Tracking**: Using nearly 20 years of historical data to plot time series charts of key valuation indicators (such as EV/Sales, EV/EBITDA) to judge whether current valuations are at historical highs or lows. 3. **Event-driven Analysis**: Combining behavioral finance indicators such as Short Interest Ratio to interpret extreme market sentiment; for instance, high short interest ratios often predict potential short-covering rallies. 4. **Fundamentals and Valuation Linkage Analysis**: Combining stock price performance with corporate financial indicators (such as free cash flow yield, earnings forecasts) to avoid making judgments based solely on valuation multiples. This comprehensive analytical approach allows the report to go beyond simple rise/fall descriptions and delve into the essence of market pricing logic.

Methodology notes

• Industry/Industrial Analysis FrameworkSupply-demand framework

  This report implicitly uses the supply-demand framework to explain market trends. When market expectations for a certain type of asset (such as large-cap tech stocks) are too high, supply (i.e., investor willingness to sell) increases, causing prices to fall; conversely, when demand (i.e., capital inflow) is strong in certain areas (such as travel, shared economy), prices rise.

  Simply put, 'the more people buying, the higher the price goes; the more people selling, the lower the price falls'. The report captures the shifting balance of market power by observing stock price movements and short interest ratios.

• Valuation MethodEV/EBITDA valuation

  The report repeatedly used and compared the 'Next Twelve Months (NTM) EV/EBITDA' valuation metric as the core standard for measuring company value.

  EV/EBITDA is a commonly used indicator to measure the ratio of a company's total value (Enterprise Value) to its operating profit (Earnings Before Interest, Taxes, Depreciation, and Amortization). The lower this ratio usually means the company is cheaper; the higher, it may be overvalued. The report determines if the current valuation is reasonable by comparing it with historical averages.

• Event Game Theory and Behavioral FinanceExpectation Gap / Expectation Management

  The report analyzes the widespread doubt in the market regarding whether non-giant companies can become AI beneficiaries, which is a typical case of expectation gap.

  When the market generally believes all internet companies will benefit from AI, this expectation is already reflected in stock prices. Once a company's performance fails to meet expectations, a huge 'expectation gap' occurs, triggering significant stock price adjustments. The report indicates that the market is currently correcting this overly optimistic expectation.

• Cycle and Prosperity FrameworkInventory cycle (Kitchin)

  Although not directly mentioned in the report, its analysis features of 'short-term fluctuations' and 'medium-term trends' align with the observation logic of short-term economic cycles (such as Kitchin cycle).

  The Kitchin cycle typically lasts about 3-4 years, reflecting economic fluctuations caused by enterprise inventory adjustments. The sector rotation observed in the report can be seen as a rapid transfer of market funds between sectors with different 'prosperity levels', which is consistent with the laws of short-term economic cycles.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Booking Holdings Inc (BKNG.US)

  Benefiting from travel recovery and seasonal demand, it is the core beneficiary of this sector rotation.

  Strengths

  Stable business model, high customer stickiness, less affected by macroeconomic factors, excellent recent financial report performance.

  Weaknesses

  Valuation relatively high, relies on the sustainability of post-pandemic travel demand.

  Comparison

  Compared with other internet companies, its fundamentals are more solid; it is one of the few non-tech giants favored by the market.

  Risks

  Global economic slowdown leading to reduced travel spending; exchange rate fluctuations affecting international revenue.

• Lyft Inc (LYFT.US)

  High short interest ratio combined with short-term performance improvements triggered a large-scale short-covering rally.

  Strengths

  Stock price rebounded from very low levels, strong technical repair signals, market sentiment warming.

  Weaknesses

  Long-term business model faces fierce competition, profitability not yet fully stabilized.

  Comparison

  Compared to WW which was also shorted, its fundamentals are more supportive, and rebound momentum is stronger.

  Risks

  Market competition intensifies, user retention rate declines, may face capital market pressure again.

• Alphabet Inc. (GOOGL.US)

  As the core AI leader, its valuation is extremely overvalued by the market, becoming the main target of this round of adjustment.

  Strengths

  Strong moat in search and advertising businesses, stable cash cow businesses.

  Weaknesses

  Valuation too high (39% premium), market expectations for its next growth engine are fully priced in.

  Comparison

  Compared to other internet companies, its scale and influence are huge, but it is also the biggest source of risk.

  Risks

  Regulatory risks intensify, innovation lags behind expectations, leading to the bursting of valuation bubbles.

Key data

• GOOGL 1-Week Price Change-3.5%Far below the average performance of its digital advertising sector, reflecting market concern about high valuations.
• BKNG 1-Week Price Change4.5%Became the only company in the internet sector with a single-week gain exceeding 4%, showing outstanding performance.
• LYFT Short Interest Ratio23.0%Highest on the full list, indicating that market pessimism for this stock reached its peak, providing momentum for subsequent rebounds.
• GOOGL NTM EV/EBITDA vs 3-Year Average39% PremiumValuation significantly higher than historical levels, implying there is risk of a pullback.
• Internet Sector 1-Year Performance+11.9%Slightly better than the broader market, but with severe internal divergence.

Impact & implications

This report reveals a profound market shift: from chasing concepts (such as AI) back to the rationality of fundamentals and valuations. It implies that investors need to screen targets more prudently and cannot blindly buy just because a company belongs to the 'Internet' or 'AI' concept. For funds and institutions, holdings should be re-examined to reduce exposure to high-valuation, high-expectation leading stocks, while paying attention to niche tracks with reasonable valuations and real earning potential and growth prospects, such as travel services, shared mobility, and certain consumer e-commerce. For ordinary investors, the report provides a clear warning: market sentiment changes quickly, and short-term surges and crashes are often the result of missed expectations or short covering; long-term investment should be based on independent judgment of intrinsic company value.

Risks

• Market holds doubts about whether non-giant companies can become true AI beneficiaries, potentially causing related stocks to remain under pressure.
• Once rebounds end for companies with high short interest ratios, they may quickly fall back, forming a 'flash crash' risk.
• Slowing macroeconomic growth or interest rates staying high will suppress the overall valuation level of the internet sector.

What to watch

• In the next 1-2 quarters, whether each company can fulfill its performance guidance, especially regarding growth in profit margins and cash flows.
• Federal Reserve monetary policy direction; its decision on interest rates will directly affect the valuation anchor of tech stocks.
• Consumer demand data in sectors such as travel and shared economy to verify the sustainability of their growth.