Research on the Impact of Politically Connected Tokens on the Crypto Assets Market

Recently, the journal Economics Letters published a research paper titled "From Zero to Hero: Memecoins' Spillover Effect in Cryptocurrency Markets." The paper analyzes an event involving a political figure issuing a Meme coin, revealing the heterogeneous volatility spillover effects driven by market sentiment and fundamentals, as well as how political signals amplify speculative dynamics, highlighting the increasingly important role of political factors in shaping the Crypto Assets market and investor behavior.

Introduction

The impact of political dynamics on financial markets is increasing day by day, and the crypto assets market has become a significant area where politics and finance intersect. The 2024 U.S. presidential election further highlights this relationship, as a certain Republican candidate has unprecedentedly turned to support digital assets. He claims he will make the U.S. the "cryptocurrency capital of the world" and place crypto assets at the core of his economic agenda. As a result, the market anticipates a more favorable policy stance during his potential term.

These are expected to be realized on January 18, 2025, when the candidate issued its official Meme coin on a certain blockchain. Within 24 hours, the coin's price surged by 900%, with trading volume reaching as high as $18 billion, and its market capitalization surpassing that of the largest Meme coin at the time by more than $4 billion. The next day, the issuance of the Meme coin associated with its family members further boosted market speculation. These events are not only speculative in nature but also constitute a significant exogenous shock, whose impact extends beyond financial speculation, signaling 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 Crypto Assets market. The research focuses on three key questions:

1. How does the release of this Meme coin affect the returns and volatility of major Crypto Assets?
2. Did this event trigger a financial contagion effect within the crypto assets market?
3. Does this impact have heterogeneity, manifested in different responses among Crypto Assets based on their technical foundations, uses, or speculative appeal?

To answer these questions, this paper adopts the Baba-Engle-Kraft-Kroner (BEKK) multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model, which is particularly suitable for analyzing the dynamic relationship between volatility and correlation over time.

The study selected the top ten cryptocurrencies by market capitalization for empirical analysis, finding that after the release of the Meme coin, there was 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 certain cryptocurrencies recording the largest gains due to their infrastructure and strategic affiliations. Meanwhile, mainstream cryptocurrencies such as Bitcoin and Ethereum displayed strong resilience, with their Cumulative Abnormal Returns (CARs) and variance stabilizing in the later stages of the event. In contrast, some other Meme coins experienced depreciation, and funds likely shifted towards newly issued Meme coins.

Indeed, the issuance of this Meme coin occurred in a highly politically polarized environment in the United States, and the brand itself is closely associated with strong political sentiments, which increases investor sensitivity and exacerbates market reactions. For some investors, this endorsement symbolizes a unique speculative opportunity, giving rise to a strong "herding effect"; while other investors, due to its controversial image, are aware of the political and regulatory risks and adopt a more cautious stance. This polarization explains the observed high volatility and differentiated market responses—from enthusiasm for expected political support to skepticism about reputation and political uncertainty.

This study is the first to analyze the impact of politically connected tokens on the crypto assets market. It expands the understanding of how political narratives influence decentralized financial markets. Furthermore, unlike previous studies that have largely focused on negative shocks, this research emphasizes the impact of positive shocks driven by political signals on the market. Notably, there is evidence that positive shocks have an even greater impact on the volatility of crypto assets than negative shocks. Ultimately, this study provides significant references for academia, practitioners, and policymakers, revealing the heterogeneity of market responses to politically connected tokens and highlighting how asset characteristics affect financial contagion dynamics.

Data and Methods

2.1 Data and Sample Selection

This study uses proprietary data on the mid-price closing every minute, covering the 10 most representative Crypto Assets among the top 20 by market capitalization: Bitcoin, Ethereum, Ripple, Solana, Dogecoin, Chainlink, Avalanche, Shiba Inu, Polkadot, and Litecoin. The data is sourced from a centralized trading platform in the United States, with specific data obtained from the LSEG Tick History database.

The dataset contains a total of 20,160 observations, with a time interval from January 11, 2025, to January 25, 2025, covering a symmetrical period of one week before and after the release of the Meme coin, facilitating comparative analysis before and after the event.

According to existing literature, this study uses the following formula to calculate Crypto Assets return rates:

Yield = ln(Pt ∕ Pt-1)

Among them, Pt represents the price of the digital asset at time t.

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

2.2 Method

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

Ht = C'C + A'εt-1ε't-1A + B'Ht-1B

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 problem when using high-frequency data, this paper adopts a more stringent significance level of α = 0.001.

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Result

3.1 Volatility Spillover Effect

The preliminary analysis results reveal the interrelationships between Crypto Assets, which are estimated through the BEKK-MGARCH model. In the covariance structure, the interconnections among the assets significantly strengthen in the post-event phase. This finding supports the hypothesis that "events trigger volatility spillover effects." Similarly, the amplitude of the stable logarithmic returns increases, reflecting a rise in market instability and a faster adjustment speed. All right-side panels of the images show that the returns of each Crypto Asset experienced significant fluctuations during this event, further emphasizing the systemic impact of this event.

The dynamic conditional covariance results estimated by the BEKK-MGARCH model indicate that this event indeed triggered financial contagion and volatility spillover effects in the Crypto Assets market. The covariance coefficients in the later stages of most events are significant at the 0.001 significance level, especially among assets such as ETH, SOL, and LINK, where the covariance significantly increased, showing stronger connectivity and a higher degree of market integration. In contrast, SHIB and DOT, while also reaching the significant level of 0.01, showed a weaker impact. Additionally, some assets like LTC and XRP experienced a decrease in covariance after the event, indicating that the spillover effects are not evenly distributed among all assets. Overall, the results highlight the structural impact of this Meme coin issuance event on the entire Crypto Assets market.

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3.2 information cascading effect

The analysis of Cumulative Abnormal Returns (CARs) further reveals the information cascading effect triggered by the issuance of this Meme coin. The results indicate that the event has a significant structural impact on market dynamics, manifesting as asset-specific reaction paths and heightened volatility.

In the pre-event phase, most crypto assets experienced positive returns, possibly driven by speculative expectations or the market's optimistic attitude towards a certain candidate's potential election as the 47th President of the United States. This indicates that, even in the absence of concrete information, investors have shown significant speculative buying behavior, a phenomenon that aligns with the widely documented "fear of missing out" characteristic in the crypto assets market.

In the stage following the event, three key dynamics are particularly prominent:

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

2. LINK has also performed strongly, possibly due to its correlation with large American tech companies.

3. Mature crypto assets such as Bitcoin, Ethereum, Ripple, and Litecoin have gradually stabilized after experiencing moderate increases, reflecting their market resilience and relative insulation from cascading speculative impacts.

At the same time, Meme coins such as DOGE and SHIB appear particularly weak, exhibiting a clear asset substitution effect, where speculative funds have shifted from old Meme coins to newly issued Tokens. Despite AVAX and DOT having solid technical foundations, they have not escaped this trend of capital transfer, showing signs of value loss.

The issuance of this Meme coin resulted in an exogenous shock that broke the market co-movement pattern prior to the event. Before the event, there was a high degree of coordinated volatility among various assets; however, after the event, the CARs of different assets showed significant differentiation, ranging from +20% for Solana to -20% for Dogecoin and Shiba Inu.

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

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Conclusion

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

Research results indicate that the market's response to this event shows significant heterogeneity. For example, SOL has significantly benefited due to its direct technical association with this Meme coin. Moreover, assets sharing the same underlying blockchain infrastructure have also gained a boost by catching a "free ride" on this event.

Meanwhile, mainstream crypto assets such as Bitcoin and Ethereum exhibit stronger stability due to their core position in the market, playing a similar anchoring role in 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 crypto assets market to external events and its tendency to be driven by speculative behavior. As digital assets increasingly intertwine with political and economic issues, continuous monitoring of this interaction becomes particularly important for understanding the impact on market stability.