Research on the Spillover Effect of Meme Coin Markets: From Zero to Hero

A recent study published in the "Economics Letters" analyzed the event of a well-known political figure issuing a Meme coin, revealing the heterogeneous volatility spillover effects driven by market sentiment and fundamentals. The study found that political signals amplified speculative dynamics, highlighting the significant role of political factors in shaping the cryptocurrency market and investor behavior.

Introduction

Political dynamics increasingly affect financial markets, and the cryptocurrency market has become a significant intersection of politics and finance. The 2024 U.S. presidential election further highlights this relationship, as a Republican candidate has shifted to support digital assets, claiming to make the U.S. the "crypto capital of the world" and placing cryptocurrency at the core of the economic agenda. As a result, the market anticipates a more favorable policy stance during their term.

These are expected to be realized on January 18, 2025, when the candidate issued the official Meme coin on the Solana blockchain. Within 24 hours, the coin's price skyrocketed by 900%, with a trading volume reaching $18 billion, and its market capitalization surpassed that of the largest Meme coin at the time, DOGE, by $4 billion.

The next day, the issuance of the Meme coin associated with his family further fueled market speculation. These events are not only speculative in nature but also constitute a significant exogenous shock, whose impact goes beyond the realm of financial speculation, sending signals for broader regulatory and political agendas.

This study aims to examine how this event serves as both a political signal and a financial event affecting the cryptocurrency market, focusing on three key issues:

1. How does the release of this Meme coin affect the returns and volatility of major cryptocurrencies?

2. Did this event trigger a financial contagion effect in the cryptocurrency market?

3. Does this impact exhibit heterogeneity, manifesting as different cryptocurrencies responding differently based on their technical foundations, uses, or speculative appeal?

To address these issues, this paper adopts the BEKK multivariate Generalized Autoregressive Conditional Heteroskedasticity ( MGARCH ) model, which is particularly suitable for analyzing the dynamic relationship of volatility and correlation over time.

This article selects the top ten cryptocurrencies by market capitalization for empirical research and finds that after the release of the Meme coin, there is a significant volatility spillover effect among crypto assets, indicating the presence of financial contagion in the market. The event triggered a major shift in market dynamics, with Solana and Chainlink recording the largest gains due to their infrastructure and strategic associations. In contrast, mainstream cryptocurrencies such as Bitcoin and Ethereum exhibited strong resilience, with their cumulative abnormal returns (CARs) and variance stabilizing in the later stages of the event. Conversely, other Meme coins like Dogecoin and Shiba Inu experienced depreciation, and funds likely shifted towards newly issued Meme coins.

Indeed, the issuance of this Meme coin occurred in an environment of high political polarization in the United States, and this brand itself is closely related to strong political sentiments, which has heightened investor sensitivity and intensified market reactions. For some investors, this symbolizes a unique speculative opportunity, giving rise to a strong "herding effect"; while other investors are aware of political and regulatory risks due to its controversial image, taking a more cautious stance. This polarization explains the observed high volatility and differentiated market reactions—from enthusiasm for expected political support to skepticism regarding reputation and political uncertainty.

In recent years, the contagion effect in the cryptocurrency market has received increasing attention due to its significant implications for financial stability, risk management, and portfolio diversification. Existing research has primarily focused on spillovers between cryptocurrencies or between cryptocurrencies and traditional financial assets, revealing patterns of connectivity, contagion risk, and volatility transmission. However, most of these studies concentrate on financial or technical triggers, such as market crashes, liquidity constraints, or blockchain innovations. Political signals, especially those related to the contagion mechanisms of politically connected tokens, remain a gap in research.

This study is the first to analyze the impact of politically connected tokens on the cryptocurrency market. It expands the understanding of how political narratives influence decentralized finance markets. Moreover, unlike previous studies that have mainly focused on negative shocks, this research focuses on the impact of positive shocks driven by political signals on the market. Notably, there is evidence that positive shocks have an even greater effect on the volatility of cryptocurrencies than negative shocks. Ultimately, this study provides important references for academia, practitioners, and policymakers, revealing the heterogeneity of market responses to politically connected tokens and emphasizing how asset characteristics influence financial contagion dynamics.

Data and Methods

2.1 Data and Sample Selection

This study uses proprietary data on minute-by-minute closing mid-prices, covering the 10 most representative cryptocurrencies among the top 20 by market capitalization: Bitcoin ( Bitcoin, BTC ), Ethereum ( Ethereum, ETH ), Ripple ( Ripple, XRP ), Solana ( SOL ), Dogecoin ( Dogecoin, DOGE ), Chainlink ( LINK ), Avalanche ( AVAX ), Shiba Inu ( Shiba Inu, SHIB ), Polkadot ( DOT ), and Litecoin ( Litecoin, LTC ). The data is sourced from a centralized trading platform in the United States, obtained from the LSEG Tick History database.

The dataset contains 20,160 observations, covering the time period from January 11, 2025, to January 25, 2025. It includes a symmetric time frame around the release of the Meme coin on January 18, 2025, which allows for comparative analysis before and after the event.

According to the practices established in existing literature, this study uses the following formula to calculate cryptocurrency returns:

Yield = ln(Pt ∕ Pt-1)

Pt represents the price of digital assets at time t.

The event time is defined as January 18, 2025, Coordinated Universal Time ( UTC ) at 2:44 AM, which marks the official release of the new U.S. president's Meme coin. Cumulative abnormal returns are calculated to assess the information cascade effect. This article calculates the average benchmark return for each cryptocurrency from January 1, 2025, to January 10, 2025, to represent a relatively stable preliminary sample. Then, the benchmark is subtracted from the actual returns within the sample period to obtain excess returns over the market benchmark, which are then accumulated to derive CARs.

( 2.2 method

Use the BEKK-MGARCH model to analyze the impact of the launch of this Meme coin on the cryptocurrency market. Assume that the logarithmic returns follow a normal distribution with a mean of zero and a conditional covariance matrix of Ht, the model is set as follows:

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Among them, H represents the unconditional covariance matrix. The parameter matrix satisfies a, b > 0, and a + b < 1, to ensure the stability and positive definiteness of the model. Subsequently, the contagion effect test is conducted. Considering the potential Type I error issues that may arise when using high-frequency data, this paper adopts a stricter significance level of α = 0.001.

Result

) 3.1 Volatility Spillover Effect

The preliminary analysis results reveal the interrelationships among cryptocurrency assets. In the covariance structure, the interconnectivity between assets significantly increases in the phases following an event. This finding supports the hypothesis that "events trigger volatility spillover effects." Similarly, the amplitude of fluctuations in stable logarithmic returns increases, reflecting the phenomenon of rising market instability and accelerating adjustment speed. All images show that the returns of various cryptocurrency assets experienced significant fluctuations during the event, further emphasizing the systemic impact of this event.

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The estimation results of dynamic conditional covariance indicate that the event indeed triggered financial contagion and volatility spillover effects in the cryptocurrency market. The covariance coefficients in the later stages of most events are significant at the 0.001 significance level, particularly among assets such as ETH, SOL, and LINK, where the covariance significantly increased, showing stronger interconnectivity and a higher degree of market integration. In contrast, while SHIB and DOT also reached a significance level of 0.01, their impact was weaker. Additionally, some assets like LTC and XRP experienced a decrease in covariance after the event, indicating that the spillover effect is not evenly distributed among all assets. Overall, the results highlight the structural impact of this Meme coin issuance event on the entire cryptocurrency market.

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3.2 information cascading effect

Cumulative abnormal returns ### CARs ### analysis further reveals the information cascade effect triggered by the issuance of this Meme coin. The results indicate that the event has a significant structural impact on market dynamics, manifested as asset-specific response paths and increased volatility.

Before the event, most cryptocurrencies experienced positive returns, possibly driven by speculative expectations or the market's optimistic attitude towards someone's potential election as the 47th President of the United States. This indicates that even in the absence of concrete information, investors have exhibited significant speculative buying behavior, a phenomenon that aligns with the widely documented "fear of missing out" characteristic in the cryptocurrency market.

In the phase following the occurrence of the event, three key dynamics are particularly prominent:

1. SOL has performed excellently, surpassing all other assets, which is likely related to its direct technical relationship as the underlying blockchain for the Meme coin.

2. LINK has also performed strongly, possibly related to its association with the large American tech company Oracle.

3. Mature cryptocurrencies such as Bitcoin, Ethereum, Ripple, and Litecoin have gradually stabilized after experiencing a moderate increase, reflecting their market resilience and relative insulation from the effects of cascading speculation.

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At the same time, other Meme coins like DOGE and SHIB appear particularly weak, showing a clear asset substitution effect, where speculative funds are shifting from the old Meme coins to newly issued tokens. Despite AVAX and DOT having a solid technical foundation, they have also not been spared from this trend of capital transfer, showing signs of value loss.

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The research results further clarify how the issuance of this Meme coin as an exogenous shock broke the pre-event market co-movement pattern. Prior to the event, there was a high level of co-movement among the assets; however, after the event, the CARs of different assets exhibited severe divergence, ranging from +20% for Solana to -20% for Dogecoin and Shiba Inu.

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These results reveal that asset-specific narratives, technological relevance, and investors' subjective perceptions can significantly amplify the differential responses of asset returns during major information shocks.

Conclusion

This study examines the impact of cryptocurrency issuance related to political figures on the crypto market, focusing on the volatility spillover effect and the information cascading effect.

Research results indicate that the market's reaction to this event exhibits significant heterogeneity. For example, due to the direct technical association with this Meme coin, SOL has benefited significantly. Additionally, assets sharing the same underlying blockchain infrastructure have also received a boost by riding the "coattails" of this event.

At the same time, mainstream crypto assets like Bitcoin and Ethereum have demonstrated stronger stability due to their core position in the market, playing a similar anchoring role during this event and stabilizing the overall market structure. This indicates that investor sentiment is no longer solely dependent on fundamental technical factors, but is also significantly influenced by geopolitical and policy narratives, especially when these narratives are issued by highly symbolic leaders.

In summary, this article reveals the high sensitivity of the cryptocurrency market to external events, as well as its tendency to be driven by speculative behavior. As digital assets increasingly intertwine with political and economic issues, continuous monitoring of this interaction is essential for understanding market stability.