The global financial landscape witnessed a profound upheaval with the onset of the COVID-19 pandemic, raising pivotal questions about how such unprecedented events influence asset allocation strategies across diverse markets. Amidst this backdrop, recent research has embarked on a rigorous exploration of the pandemic’s effect on investment portfolio construction within the realms of commodities, currencies, and cryptocurrencies. By harnessing a novel composite asset selection approach that integrates innovative hybrid performance measures, this study pushes the frontier on understanding how the balance of risk and return morphs through crises and uncertainty. The implications are vast—offering new strategic insights to investors navigating volatile markets reshaped by global shocks.
Central to this investigation is the evaluation of the minimum variance portfolio (MVP) strategy, a cornerstone in modern portfolio theory that strives to minimize overall risk while optimizing returns. The research pioneers a nuanced comparison between two key methodologies for weighting assets within bi-asset portfolios: the recently developed Composite Weighting Index (CWI) approach introduced by Su in 2020, and the more established Mean-Variance Discrepancy Weighting Index (MDWI) approach conceptualized by Kroner and Ng in 1998. The comparison surfaces important observations around the robustness and reliability of these techniques when faced with the tumultuous conditions imposed by COVID-19.
Intriguingly, the findings reveal that the CWI method consistently outperforms its counterpart in predicting optimal weights for MVPs, demonstrating a remarkable stability across both pre-pandemic and pandemic eras. This persistence signifies that the strengths of the CWI approach transcend market shocks, offering investors a more dependable framework for portfolio optimization under uncertainty. Such a conclusion challenges assumptions that extreme market disruptions invariably erode established quantitative strategies and underscores the potential for emerging methods to enhance resilience in financial decision-making.
Beyond merely contrasting weighting techniques, the study delves deeply into the delicate interplay between return and risk—a long-standing conundrum for investors seeking balance. Through meticulous empirical analysis, optimal portfolios generated by separate performance metrics—volatility for risk and return for gains—emerge in opposing regions within the risk-return spectrum. This spatial divergence starkly illustrates the trade-off dilemma, emphasizing that prioritizing one metric necessarily compromises the other. The research responds to this challenge by formulating two hybrid performance measures, combining return and volatility considerations to better capture the multifaceted nature of portfolio optimization.
However, this sophisticated approach surfaces an unexpected quandary: the two hybrid measures, although conceptually aligned, sometimes produce discordant optimal portfolios. The divergence introduces a new layer of complexity, raising concerns about the reliability and consistency of performance assessments in practice. Confronted with this inconsistency, the study advances a composite asset selection methodology designed to reconcile these conflicting signals. This composite approach yields convergent, compromise portfolios capable of navigating the fragmented insights derived from different evaluation criteria, enhancing both the interpretability and applicability of asset allocation outcomes.
One of the most striking revelations emerges when examining portfolio compositions for the distinct phases surrounding the COVID-19 crisis. The research uncovers significant shifts in the asset pairs deemed optimal by the composite method before and during the pandemic. Specifically, the pre-COVID-19 optimal portfolios favor the Chinese yuan paired with Ethereum or Bitcoin with Ethereum, whereas during the pandemic, WTI crude oil combined with Ethereum prevails as the ideal choice. This temporal transformation not only illustrates dynamic market interrelations but also highlights the adaptive nature of portfolio construction in response to systemic disruptions.
Further granularity reveals that the assets contributing to improved portfolio performance differ starkly across the two subperiods. Ethereum holds prominent significance before the pandemic, while WTI and Bitcoin take precedence amidst the crisis. These non-overlapping asset inclusions robustly support the study’s hypotheses regarding the pandemic’s influence on asset allocation performance, suggesting a deeper structural break in market dynamics triggered by COVID-19. Such evidence underscores the necessity for adaptive portfolio strategies that can account for regime shifts rather than relying on static historical patterns.
For practitioners and asset managers, these findings carry important policy recommendations grounded in the minimum variance optimization framework. Investors seeking to capitalize on stable MVP weights should employ the CWI approach for more accurate forecasting, followed by the composite asset selection technique that accommodates dual hybrid performance measures, thereby addressing the trade-off between risk and return and mitigating disparate evaluation outcomes. Implementing this two-step process stands to elevate risk-adjusted returns while ensuring consistency in asset selection across diverse market conditions.
Portfolio composition guidance based on the empirical results suggests a strategic focus on a Chinese yuan-Ethereum alliance prior to the pandemic, with a pivot towards WTI-Ethereum combinations during the ongoing COVID-19 crisis. Notably, the actual asset weight distributions are finely tuned to reflect these shifts, with a 64.28% allocation to the Chinese yuan and 35.72% to Ethereum in the pre-COVID-19 era, reversing to a dominant Ethereum presence with adjusted proportions in the pandemic timeframe. Fund managers are thus advised to incorporate or emphasize Ethereum when managing portfolios pre-pandemic and consider transitioning toward WTI during periods of heightened market turbulence such as the COVID-19 outbreak.
The study candidly acknowledges its current limitations, recognizing that bi-asset portfolios, while informative for methodological testing, do not capture the full complexity of real-world portfolio construction, which typically involves multiple assets. This acknowledgment charts a clear direction for subsequent investigations—extending composite asset selection frameworks to multifaceted portfolios and simultaneously scrutinizing the persistence of identified patterns across broader asset universes. Such expansion promises to enhance both the robustness and real-world applicability of the approach, vital for sophisticated institutional asset management and burgeoning robo-advisory platforms.
In laying out a comprehensive analytical foundation, this research intersects pandemic-driven economic shocks with advanced quantitative portfolio methods, framing the COVID-19 crisis not only as a health emergency but as a catalyst for structural transformations in capital markets. Its insights shed light on the evolving behavior of commodities, currencies, and emerging cryptocurrency classes, providing both empirical rigor and strategic guidance amidst unprecedented uncertainty. The demonstrated efficacy of the CWI and composite asset selection approaches is particularly compelling for stakeholders seeking to reconcile theory with the pressing demands of crisis-era investing.
Moreover, the discourse around hybrid performance metrics and their reconciliation through composite selections represents a meaningful contribution to the ongoing debate within financial economics about performance measurement. It suggests a path forward in which no single indicator reigns supreme; rather, multi-dimensional evaluation frameworks paired with composite decision rules may better reflect the complex realities investors face. This resonates broadly with contemporary trends toward more sophisticated risk management and portfolio design methodologies that blend quantitative rigor with practical flexibility.
Taken together, these findings not only illuminate the pandemic’s imprint on market structures but also articulate a nuanced narrative of how asset allocation must evolve in tandem with shifting risk landscapes. Investors and fund managers who adopt these advanced methodologies stand to benefit from sharper insights and more resilient portfolios, gaining an edge in an increasingly unpredictable environment. At the same time, the work invites continued scholarly exploration into the systemic undercurrents shaping asset behavior during and beyond extraordinary crises, underscoring the enduring relevance of adaptive financial modeling.
As robo-advisory platforms and algorithmic investment solutions gain prominence, this research offers timely recommendations for integrating robust, dynamic allocation frameworks capable of withstanding sudden market dislocations. The adaptability of the CWI approach coupled with composite asset selection may well serve as a blueprint for automated systems tasked with managing complex portfolios in rapidly evolving settings. This intersection of quantitative innovation and practical application may define a new frontier for asset management technology post-pandemic.
In conclusion, the study presents a compelling narrative that the COVID-19 pandemic has materially affected asset allocation outcomes across commodity, currency, and cryptocurrency markets, necessitating a re-examination of traditional portfolio optimization strategies. By championing a composite asset selection approach that harmonizes conflicting performance measures and leverages stable weight forecasting methodologies, it charts a sophisticated and practical path forward. This contribution holds profound implications not only for academic inquiry but also for the practitioners and investors contending with one of the most volatile eras in financial history.
Subject of Research: Impact of the COVID-19 pandemic on asset allocation performance in commodity, currency, and cryptocurrency markets using composite asset selection approaches.
Article Title: Does the COVID-19 pandemic affect the asset allocation performance? Evidence from a composite asset selection approach.
Article References:
Su, JB. Does the COVID-19 pandemic affect the asset allocation performance? Evidence from a composite asset selection approach.
Humanit Soc Sci Commun 12, 1287 (2025). https://doi.org/10.1057/s41599-025-05258-0
Image Credits: AI Generated
