A Regime Shift in Liquidity, Geopolitics, and Technology

January 2026 marks a clear inflection point. The global economic and geopolitical framework established in the 1970s is fragmenting at the same time as a technological discontinuity—driven by AI and automation—is accelerating.

This conjunction materially increases dispersion across assets and strategies. In this environment, portfolio outcomes will be determined less by beta exposure and more by positioning across liquidity, geopolitics, and structural versus cyclical growth.

Liquidity: Still Supportive, but with Policy Asymmetry Risks

U.S. liquidity conditions remain broadly constructive for risk assets (Figure 1), albeit with rising policy uncertainty.

The Federal Reserve has resumed balance-sheet expansion via “Reserve Management Purchases,” injecting approximately USD 40bn per month to alleviate reserve constraints visible in the repo market. This liquidity is flowing into the banking system and supporting credit creation, reinforcing near-term risk appetite.

Fig.1 – FED Liquidity

source:SARIM

However, the outlook for sustained quantitative easing is less certain following the nomination of Kevin Warsh as the next Fed Chair. Warsh has consistently argued for using the price of money rather than the quantity of money to manage financial conditions. While accommodation can be delivered through either channel, a policy pivot toward tighter balance-sheet control would represent a meaningful shift later in the cycle.

Offsetting this risk is an exceptionally large fiscal-liquidity impulse ahead. An estimated USD 4.7tn in tax-related cash flows is expected to be released over the next twelve months through household refunds, corporate repatriation, and accelerated depreciation and capex incentives. In scale, this exceeds prior crisis responses and equates to roughly 20% of U.S. GDP.

We expect this liquidity wave to disproportionately benefit consumer discretionary (refund-driven spending), technology (buybacks), industrials (capex), financials (credit growth and M&A), and real assets such as housing. The central risk is whether liquidity can overwhelm a deteriorating political backdrop.

Geopolitics: Structural Re-Armament, Short-Term Volatility

The post-World War II institutional order is eroding. Europe faces a forced re-armament cycle amid industrial decline and a prolonged war in Ukraine, while the U.S. is pursuing a more confrontational global posture, combining military actions with sharply higher defense spending.

This environment supports sustained structural exposure to defense, weapons systems, rare earths, and copper, driven by re-armament, supply-chain security, and strategic stockpiling.

Fig.2 – FANG+ Nyse Index does not look good

source:TradingView

In the near term, however, U.S. domestic political risk is rising. A likely loss of Republican control in the midterms would imply prolonged institutional conflict, impeachment risk, and policy gridlock. Historically, such episodes translate into higher volatility premia and valuation compression—particularly for long-duration growth assets.

Given stretched valuations and heightened sensitivity to AI-related execution risk, the Nasdaq appears especially vulnerable. We recommend short-dated downside protection via index puts or delta-hedged structures as a tactical hedge (Figure 2).

Technology: Structural Conviction, Cyclical Caution

AI and robotics represent a secular transformation of productivity (Figure 3) and capital allocation. We maintain high long-term conviction in the theme and view it as a core structural exposure.

That said, near-term risks have increased. Circular financing, aggressive capex, and increasingly concentrated positioning among U.S. technology firms argue for caution into the midterms. We favor quality-biased exposure—companies with balance-sheet strength, pricing power, and defensible cash-flow visibility—while limiting incremental risk deployment in the short term

Fig.3 – Intelligence explosion by 2030

source:OpenAI

How to read this chart? The AI Futures Project, led by former OpenAI researcher Daniel Kokotajlo, originally predicted that AI systems could achieve fully autonomous coding and trigger an “intelligence explosion” by 2027. They’ve now revised that to around 2030, citing slower-than-expected progress and greater complexity than anticipated.

Portfolio Implications

• Maintain pro-risk positioning while liquidity remains supportive, but reduce reliance on passive beta
• Structural overweight: defense, strategic metals, and energy transition inputs
• Tactical hedges: Nasdaq downside protection amid political and valuation risk
• Diversification: selective emerging markets exposure, with a focus on China
• Hard assets: gold as a strategic hedge against USD structural debasement (Figure 4), with disciplined risk management

Fig.4 – Historical currency value decline paths

source:Bloomberg

In short, this is not an environment for complacency. Liquidity may delay adjustment, but regime change is underway. Successful portfolios will balance structural conviction with tactical flexibility. 

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