Jin Shi Shu Ju·2025-12-04 08:12Core Viewpoint - UK pension funds are reducing their exposure to the US stock market due to concerns over market concentration in a few tech stocks and potential bubble risks in the AI sector [1][4]. Group 1: Market Trends and Adjustments - Several UK pension plans managing over £200 billion in assets have shifted their asset allocation towards other regions or increased protective measures against potential stock price declines [1]. - The Nasdaq Composite Index, driven by major tech stocks like Nvidia, Alphabet, and Meta, has surged over 20% this year, raising concerns about market dominance by a few stocks and the risk of significant sell-offs for retirement savers [1][4]. - The concentration of US tech stocks, coupled with their historically high valuations, is prompting increased scrutiny regarding the risks posed to fund members [2][4]. Group 2: Specific Fund Strategies - The Standard Life investment plan is reducing its US stock allocation while increasing exposure to UK and Asian markets, reflecting sensitivity to potential market volatility [2]. - The Aon Master Trust sold approximately 10% (around £700 million) of its global stock portfolio this summer, primarily from US stocks, to capitalize on opportunities in the UK bond market [2]. - Fidelity is maintaining its US stock exposure but is focusing on more stable companies and increasing gold holdings for risk hedging, particularly for members nearing retirement [3]. Group 3: Institutional Warnings and Market Sentiment - The European Central Bank and the IMF have warned that high valuations of US tech stocks could pose significant risks if market optimism around AI fades [4]. - Despite concerns, some pension fund managers are hesitant to reduce their allocations to strong-performing US tech stocks due to fears of missing out on further gains [5]. - The Border to Coast fund has slightly increased its US stock exposure while reducing some AI-related positions, indicating a cautious approach to the evolving competitive landscape in the AI sector [6].