---
title: "Goldman Sachs trader: The volatility at this time of year is a \"normal phenomenon,\" nothing \"abnormal\""
type: "News"
locale: "zh-CN"
url: "https://longbridge.com/zh-CN/news/264997180.md"
description: "Goldman Sachs pointed out that the recent 5% pullback in the US stock market is a normal fluctuation in the AI cycle, and it is expected that there is still a 5-10% upside potential before the end of the year. This judgment is based on three major supports: AI investment is still in the early stages, institutional positions are not yet saturated; tech giants have robust balance sheets and over 20% profit growth; and the current valuation is fundamentally different from the internet bubble— the Nasdaq 100 index is trading at a 46% discount compared to that time, and listed companies generally generate strong free cash flow"
datetime: "2025-11-09T03:46:23.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/264997180.md)
  - [en](https://longbridge.com/en/news/264997180.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/264997180.md)
---

> 支持的语言: [English](https://longbridge.com/en/news/264997180.md) | [繁體中文](https://longbridge.com/zh-HK/news/264997180.md)


# Goldman Sachs trader: The volatility at this time of year is a "normal phenomenon," nothing "abnormal"

**Goldman Sachs believes that the recent 5% pullback in the U.S. stock market is a typical year-end seasonal fluctuation in the AI cycle and does not signal an abnormal end to the upward trend.**

Goldman Sachs traders pointed out that despite the market experiencing a pullback, there is still room for growth before the end of the year. The combination of seasonal factors, the early stage of the AI investment cycle, and relatively light institutional positioning suggests that the index still has the potential to rise further.

According to Goldman Sachs fixed income, foreign exchange, and commodities trader Shreeti Kapa, a 5% decline at this time of year is a normal phenomenon in this cycle. She believes that although the market has experienced a strong rebound since the April low, overall it "has not been excessive."

**Kapa's optimistic view is based on favorable seasonal factors at year-end and anticipates that the market has another 5-10% upside before the end of the year, accompanied by broad market participation.** She noted that many institutional investors are currently skeptical about the market's future, believing that this year's market peak has already occurred and are attempting to adjust their positions accordingly. In her view, this widespread cautious sentiment actually creates the possibility for the index to "rise significantly" in the remaining 35 trading days of the year.

**Regarding macro uncertainties, such as the risk of a federal government shutdown, Kapa believes this is merely a temporary issue. As for concerns about artificial intelligence potentially replacing white-collar jobs, she acknowledges that this is a pillar of retail demand but believes "this is not a problem today."**

## Room for Growth at Year-End

**The core logic supporting the continued rise of the market before year-end is based on the judgment that the AI revolution is still in its early stages.**

Kapa believes that institutional investors have not fully allocated their positions to the AI theme. At the same time, capital flows are expected to become favorable before year-end, and the market anticipates that the Federal Reserve's monetary policy next year may be more dovish than last year.

On the corporate fundamentals side, while large tech companies are investing heavily in AI, they possess robust balance sheets, reasonable price-to-earnings ratios, and over 20% compound earnings per share growth. Kapa emphasized that the main contradiction in the current market is not concerns about investment returns, but rather "solving the spending issue and investing in this potentially historic technological revolution."

## Is it 1998 or 2000 Now?

Discussions about whether the current market is replaying the tech bubble are ongoing, but the key distinction lies in today's valuation basis and profitability.

Eric Sheridan, head of technology, media, and telecommunications research at Goldman Sachs, pointed out that compared to the internet and real estate bubble periods, there is much more discussion today about an "AI bubble." He acknowledged that private market valuations are significantly higher than public markets and are more focused on revenue growth rather than profits, which bears similarities to historical risk signals.

However, he emphasized that today's public company valuations are still based on free cash flow, return on capital, and profit margins, which is starkly different from the situation in 1999 when companies without revenue received the highest valuations. He **stated that today's tech giants are mostly able to generate substantial free cash flow and engage in stock buybacks and dividends, which were "almost nonexistent" in 1999.** In addition, current capital market activities are also far below the levels seen during historical bubble periods, and the IPO market is behaving "more selectively."\*\*

## Trillion-level investments remain within controllable range

The competition in artificial intelligence has sparked immense imagination regarding the scale of future capital expenditures, **but from a macro perspective, this wave of investment may still be within a controllable range.**

David Cahn, a partner at Sequoia Capital, proposed a thought-provoking conversion: he converted the energy demand for data centers required for building artificial intelligence from "gigawatts" to "dollars." He estimates that constructing AI energy facilities of 100 to 250 gigawatts would mean expenditures of $4 trillion to $10 trillion for data centers. He believes that such a massive investment must be justified by breakthroughs in achieving Artificial General Intelligence (AGI).

However, Goldman Sachs macroeconomist Joe Briggs provided another perspective **. He pointed out that while the current scale of AI investment is enormous in nominal dollar terms, its impact appears "more moderate" when measured as a percentage of GDP.** Over the past 12 months, AI investment in the United States has accounted for less than 1% of GDP, whereas historically, peak infrastructure investments have typically reached 2% to 5% of GDP. The Brigg team estimates that generative AI will ultimately create $20 trillion in GDP economic value for the United States.

## Valuation and positioning provide support

Multiple data points indicate that current market valuations and investor positioning are still distant from historical highs, providing potential support for the market going forward.

According to data from Goldman Sachs Global Investment Research (GIR), the current trading price of the Nasdaq 100 index is approximately 46% discounted compared to the internet bubble period, and the lower price-to-earnings ratio indicates that earnings provide support for valuations. Although current Treasury yields are lower than those during the 1999-2000 period, the market return over the past 12 months has also been relatively low, and the report suggests that this indicates there is still room for the market to rise in the next 6-12 months.

In addition, investor positioning data also supports Shreeti Kapa's viewpoint. **Data shows that after being in a neutral state for most of the third quarter, the current market positioning has actually entered the "light positioning" zone, which means that once market sentiment turns optimistic, there will be a large amount of capital waiting to enter.**

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