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Multi-Asset Insights

Reframing diversification in a multipolar world - Rethinking Asia’s diversification role
05 February 2026
    Articles
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    In a nutshell

    • Asia’s role is shifting from a high-beta play on global growth to a more heterogeneous region where local policy, inflation dynamics and China’s structural slowdown drive increasingly differentiated returns across equities, bonds and currencies
    • Correlations across Asian assets have become more time-varying and asymmetric, with country- and asset-specific clusters emerging and weakening the usefulness of long-term averages as a guide to diversification
    • China remains the dominant transmitter of return and volatility shocks across Asia, while markets such as Singapore and Malaysia tend to absorb volatility, reinforcing the need to distinguish between sources and sinks of regional risk
    • Policy divergence in monetary, fiscal, regulatory and currency frameworks has become the primary driver of internal differentiation in Asia, reducing synchronisation and reshaping traditional bond–equity and currency relationships
    • Empirical analysis of hedging relationships indicates that effective diversification now depends on combining complementary structural exposures, rather than treating Asia as a single beta, with carefully constructed long–short pairs and policy-anchored fixed income improving portfolio resilience

    Rethinking Asia’s diversification role

    Long treated as a regional allocation defined primarily by its sensitivity to global growth cycles, Asian markets are increasingly being shaped by local forces powerful enough to alter how diversification works across the region.

    For many global allocators, Asia historically functioned as a higher-beta extension of external demand, where equities amplified global growth, local-currency bonds provided carry with volatility, and currencies acted as conduits through which global shocks were transmitted. This framework worked during periods of synchronised expansion but proved fragile during stress when correlations across Asian assets tended to rise sharply and diversification benefits faded just when they were needed most.

    In recent years, this pattern has begun to change. Post-pandemic policy divergence, differentiated inflation dynamics, and China’s structural slowdown have weakened the forces that once synchronised Asian assets. The result is a more heterogeneous investment landscape in which correlations across equities, bonds and currencies are increasingly driven by domestic policy choices rather than by a single global or regional engine. This transition transforms Asia’s internal dispersion from a challenge into a potential source of portfolio resilience, provided investors understand how returns and risks propagate through the region.

    Empirical analysis of diversification benefits in Asia

    A critical starting point is recognising that correlation is not a fixed characteristic. It evolves with policy regimes, growth structures and capital flows. Over the past decade, correlations across Asian assets were largely governed by a small set of common anchors:

    1. US monetary policy
    2. China’s investment cycle
    3. Global trade volumes
    4. Commodity pricing

    These forces created a tendency for Asian markets to move together, especially during episodes of US tightening or Chinese-led stimulus.

    Recent experience highlights how fragile those assumptions can be. Rolling correlation analysis shows that Asia exhibits more time-varying and asymmetric correlations, undermining the usefulness of long-term averages as a guide to diversification. For example, Asian equities excluding Japan historically displayed a negative correlation of around -0.39 against the US dollar, reflecting the dollar’s defensive role.

    Figure 1: Cross-asset correlations based on 20-year weekly returns

    Figure 1: Cross-asset correlations based on 20-year weekly returns

    Click the image to enlarge

    Source: HSBC AM, Bloomberg. Data as of November 2025.

    However, following recent US policy shocks and renewed de-dollarisation dynamics, this relationship temporarily flipped positive as domestic policy responses within Asia overpowered traditional global linkages.

    Figure 1: Cross-asset correlations based on 20-year weekly returns

    Click the image to enlarge

    Figure 1: Cross-asset correlations based on 20-year weekly returns

    Click the image to enlarge

    Past performance does not predict future returns.
    Source: HSBC AM, Bloomberg. Data as of November 2025.

    More importantly, these shifts are not uniform. Dynamic conditional correlation analysis1 indicates that correlation clusters are becoming increasingly asset- and country-specific rather than region-wide. India and China A-shares display one of the lowest bilateral equity correlations in Asia, at roughly 22 per cent, reflecting fundamentally different growth drivers and investor bases. At the other extreme, Korea and Taiwan show persistently high correlation of around 72 per cent, driven by shared exposure to global technology and semiconductor cycles, increasingly reinforced by the AI supply chain. This structural alignment has important implications. While both markets can deliver strong performance during upswings in the technology cycle, their diversification benefits relative to one another are inherently limited.

    1 - Dynamic Conditional Correlation – A simple class of multivariate GARCH models, Robert Engle, 1999, Forthcoming Journal of Business and Economic Statistics 2002

    Similarly, Indonesia and Malaysia, more commodity-linked than ever, saw bond resilience due to central bank interventions that prevented global risk sentiment from destabilising yields. These observations imply that correlations are fragmenting, not disappearing, raising the cost of simplistic regional allocations but opening the door to more deliberate, design-driven diversification.

    Understanding diversification in Asia also requires examining interdependence and volatility spillovers rather than static correlations alone. To analyse this, a vector autoregression (VAR) framework was applied to daily returns, modelling current market performance as a function of its own lagged returns and those of other regional markets.

    Figure 3: The coefficients Φ that are statistically significant at 5% (p-value < 5%)

    Figure 3: The coefficients Φ that are statistically significant at 5% (p-value < 5%)

    Click the image to enlarge

    Source: HSBC AM. Data as of November 2025.

    Broadly, most Asian equity markets exhibit negative relationships with their own one-period lagged returns, reflecting short-term mean reversion. China remains the dominant directional influence. Movements in China A-shares continue to shape returns across other Asian equity markets, confirming its role as a regional sentiment anchor even as economic spillovers weaken.

    Additionally, volatility transmission analysis using multivariate volatility models2 shows that China remains the primary transmitter of volatility across Asia.

    Figure 4: The volatility spillover from one market to another market - volatility decomposition

    Figure 4: The volatility spillover from one market to another market - volatility decomposition

    Click the image to enlarge

    Source: HSBC AM. Data as of November 2025.
    2 - Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility McAleer et al. (2009)

    By contrast, Singapore and Malaysia tend to act as volatility absorbers rather than sources, reflecting strong institutional frameworks and domestically anchored drivers. Korea and Taiwan exhibit high mutual volatility spillovers, underscoring how deeply embedded both markets are within the same global technology cycle.

    These findings imply that while return correlations have weakened, volatility transmission remains uneven and state-dependent. Effective diversification therefore requires monitoring not just where returns diverge, but where risks still cluster.

    Fundamental analysis of diversification drivers

    Policy divergence has emerged as the dominant driver of Asia’s internal differentiation. Central banks across the region now operate under increasingly distinct frameworks, reflecting differences in inflation sensitivity, growth objectives and institutional constraints. India has prioritised positive real interest rates to anchor growth and inflation credibility, while other economies rely on targeted easing or administrative measures to manage inflation pass-through.

    Fiscal strategies further reinforce dispersion. Japan sustains aggressive fiscal support alongside accommodative financial conditions. India prioritises public capital expenditure. Indonesia deploys fiscal buffers to stabilise inflation, while China increasingly relies on quasi-fiscal credit channels. These divergent approaches weaken synchronisation in sovereign bond behaviour and alter bond-equity interactions across markets.

    Regulatory divergence and geopolitics amplify these effects. Technology regulation in China, industrial policy in India, semiconductor export controls affecting Taiwan and Korea, and shifting defence alignments across ASEAN all influence capital flows and risk premia in ways not captured by traditional growth narratives alone.

    China’s role illustrates this transformation most clearly. Once the primary synchroniser of Asian returns, China is now a source of differentiation. Its domestic liquidity cycle, regulatory environment and policy objectives increasingly decouple its market behaviour from export-driven peers. When sized appropriately, China exposure can now enhance diversification rather than concentrate risk.

    Japan represents another structural inflection point. Its transition from entrenched deflation toward sustained inflation and wage growth has altered long-standing relationships between equities, bonds and the yen. Historical assumptions about Japan’s stabilising role can no longer be taken for granted.

    Currency dynamics complete the picture. While the US dollar and Japanese yen retain counter-cyclical properties, several Asian currencies increasingly reflect domestic policy credibility and intervention capacity. The Indian rupee often stabilises during risk-off periods due to real-yield support and reserve policy. The Indonesian rupiah benefits from commodity-linked flows and active intervention. The Singapore dollar reflects a managed exchange-rate framework anchoring inflation expectations independently of interest-rate cycles.

    Together, these factors indicate that Asia’s diversification is increasingly policy-led rather than growth-led, representing a structural shift rather than a cyclical one.

    Implications for portfolio construction

    The practical value of this analysis lies in portfolio construction. China A-shares serve as a useful reference point for evaluating hedges within an Asian multi-asset framework. Indian equities, Chinese government bonds and the US dollar exhibit relatively low average correlations with China A-shares, though with significant time variation.

    An examination of historical drawdowns shows that Chinese government bonds and the US dollar consistently delivered positive performance during periods of equity stress, reinforcing their role as effective hedges. Indian equities, while often declining less than China A-shares, displayed more regime-dependent behaviour.

    To formalise these relationships, hedge ratios following Kroner and Sultan (1993) were estimated. Lower ratios imply stronger hedging potential and lower cost. For example, a US$1 long position in China A-shares would historically require a short position of approximately US$0.78 in Indian equities to achieve hedge efficiency.

    Figure 5: The average hedge ratio: How much to short one asset to hedge $1 long position in another asset

    Figure 5: The average hedge ratio: How much to short one asset to hedge $1 long position in another asset

    Click the image to enlarge

    Source: HSBC AM. Data as of November 2025.

    Several long-short equity pairs exhibit attractive hedging characteristics. Hong Kong equities may be hedged using Indian or Thai equities, while China A-shares show hedging potential against Indian and Indonesian equities. For Korea and Taiwan, China A-shares and Brazil emerge as potential hedging counterparts.

    However, diversification must be distinguished from hedging. Korea and Taiwan’s high mutual correlation and shared exposure to the AI cycle mean they are unlikely to hedge each other effectively. Portfolios holding both are implicitly concentrated in a single structural theme.

    Taken together, these developments imply that Asia no longer delivers diversification simply by being geographically distinct. Instead, effective diversification requires deliberately combining exposures with distinct policy regimes, economic structures and volatility transmission characteristics.

    In practical terms, strategic Asian allocation should move beyond ‘Asia beta plus carry’ mindset toward a framework built on complementary structural exposures. Blending domestic-demand economies with export-cyclicals, pairing policy-anchored fixed income with higher-beta equity exposure, and using currencies selectively as stabilisers can all materially improve portfolio outcomes. For investors, Asia is no longer a single cycle. It is a multi-driver ecosystem, and the opportunity lies in harnessing its growing internal diversity to build more resilient portfolios.

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    Authors

    • Yuanfang Ma
      Yuanfang Ma Portfolio Manager, Multi-Asset
    • Guang Yang Lim
      Guang Yang Lim Senior Manager, Asset Allocation
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