From Meme Coins to the Crypto Assets Market: The Spillover Effects of Political Signals

Recently, a study published in Economics Letters analyzed the impact of Trump's issuance of Meme coins on the Crypto Assets market. The study revealed the volatility spillover effect driven by both market sentiment and fundamentals, as well as how political signals amplified speculative dynamics, highlighting the important role of political factors in shaping the Crypto Assets market and investor behavior.

Introduction

The impact of political dynamics on financial markets is becoming increasingly significant, and the Crypto Assets market has emerged as an important area where politics and finance intersect. The 2024 U.S. presidential election further highlights this relationship, as Republican candidate Trump has unprecedentedly shifted to support digital assets. He claims he will make the U.S. the "crypto capital of the earth" and place Crypto Assets at the core of his economic agenda, leading the market to anticipate a more friendly policy stance in the future.

These are expected to be realized on January 18, 2025. Trump issued his official Meme coin ($TRUMP) on the Solana blockchain. Within 24 hours, the price of $TRUMP surged by 900%, with a trading volume of 18 billion USD, surpassing the market value of the largest Meme coin DOGE by 4 billion USD at that time. The next day, the issuance of the Meme coin $MELANIA related to the First Lady further fueled market speculation. These events are not only speculative in nature but also constitute a significant exogenous shock, with impacts that extend 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, focusing on three key issues:

1. How does the release of $TRUMP affect the returns and volatility of major Crypto Assets?

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

3. Does this impact exhibit heterogeneity, manifesting as different Crypto Assets responding differently based on their technological foundation, use cases, 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 of volatility and correlation over time.

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The empirical study selected the top ten crypto assets by market capitalization and found that after the release of the Trump 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 Solana and Chainlink recording the largest gains due to their infrastructure and strategic connections. In contrast, mainstream crypto assets like 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 such as Dogecoin and Shiba Inu experienced depreciation, and funds likely shifted towards $TRUMP.

The issuance of $TRUMP occurred in an environment of high political polarization in the United States, and the Trump brand itself is closely related to strong political emotions, thereby increasing investors' sensitivity and exacerbating market reactions. For some investors, Trump's endorsement symbolizes a unique speculative opportunity, giving rise to a strong "herd effect"; while others are aware of the political and regulatory risks due to his controversial image 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.

In recent years, the contagion effect in the Crypto Assets market has increasingly drawn attention due to its significant implications for financial stability, risk management, and portfolio diversification. Existing research has mainly focused on the spillover between Crypto Assets themselves or between Crypto Assets and traditional financial assets, revealing patterns of interconnectedness, contagion risk, and volatility transmission. However, most of this research has concentrated on financial or technical triggers, such as market crashes, liquidity constraints, or blockchain innovations. Political signals, especially regarding the contagion mechanisms associated with politically connected tokens, remain an area of research gap.

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 research that primarily focused on negative shocks, this study focuses on the impact of positive shocks driven by political signals on the market. Notably, there is evidence suggesting that positive shocks have an even greater impact on the volatility of Crypto Assets 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 the closing mid-price per minute, covering the most representative 10 of the top 20 crypto assets by market capitalization: Bitcoin ( BTC ), Ethereum ( ETH ), Ripple ( XRP ), Solana ( SOL ), Dogecoin ( DOGE ), Chainlink ( LINK ), Avalanche ( AVAX ), Shiba Inu ( SHIB ), Polkadot ( DOT ), and Litecoin ( LTC ). The data comes from a centralized trading platform in the United States, obtained from the LSEG Tick History database.

The dataset contains a total of 20,160 observations, with a time range from January 11, 2025, to January 25, 2025, covering a symmetrical time period of one week before and after the official release of Trump's Meme coin on January 18, 2025, (, facilitating comparative analysis before and after the event.

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

Yield = ln)Pt ∕Pt−1(

In which Pt represents the price of the digital asset at time t.

The event time is defined as January 18, 2025, Coordinated Universal Time ) UTC ( at 2:44 AM, which is the official release of the new U.S. 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 sample period. Then, the benchmark is subtracted from the actual returns during the sample period to derive the excess returns over the market benchmark, and CARs are obtained through accumulation.

) 2.2 Method

Use the BEKK-MGARCH model to analyze the impact of the launch of Trump's 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 as follows:

rt|It-1 ~ N###0, Ht(

Ht = C'C + A'εt-1ε't-1A + B'Ht-1B

Among them,

εt = rt - μt

H represents the unconditional covariance matrix. The parameter matrix satisfies a, b > 0, and a + b < 1, to ensure the model's stability and positive definiteness. Subsequently, the contagion effect test is conducted. Considering the potential first type error issue when using high-frequency data, this paper adopts a stricter significance level α = 0.001.

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Result

) 3.1 Volatility Overflow Effect

Preliminary analysis results reveal the interrelationships between crypto assets. In the post-event phase, the interconnections between assets significantly strengthened, supporting the hypothesis that "the event triggered a volatility spillover effect." At the same time, the magnitude of fluctuations in stable logarithmic returns increased, reflecting the phenomenon of rising market instability and accelerated adjustment speed. The returns of all assets experienced severe fluctuations during this event, further emphasizing the systemic impact of this event.

The estimation results of dynamic conditional covariance indicate that the event indeed triggered financial contagion and volatility spillover effects in the Crypto Assets market. Most covariance coefficients in the later stages of the events are significant at the 0.001 level, especially among assets such as ETH, SOL, and LINK, where the covariance significantly increased, showing stronger interconnectedness and a higher degree of market integration. In contrast, although SHIB and DOT also reached a significance level of 0.01, their impact is weaker. 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 the cumulative abnormal returns ### CARs ( further reveals the information cascading effect triggered by the issuance of the Trump Meme coin. The results indicate that the event has a significant structural impact on market dynamics, manifested as asset-specific reaction paths and increased volatility.

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

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

1. SOL has performed exceptionally well, surpassing all other assets, which is likely related to its direct technical relationship as the blockchain supporting Trump's Meme coin.

2. LINK has also performed strongly, possibly related to its association with a large technology company.

3. Mature Crypto Assets such as Bitcoin, Ethereum, Ripple, and Litecoin have gradually stabilized after experiencing a moderate rise, reflecting their market resilience and relative insulation from cascading speculative impacts.

At the same time, DOGE and other Meme coins like SHIB appeared particularly weak, showing a clear asset substitution effect, where speculative funds shifted from old Meme coins to the newly issued Trump token. Although AVAX and DOT have solid technical foundations, they too have not been spared from this trend of capital transfer, showing signs of value loss.

The issuance of the Trump Meme coin has disrupted the market co-movement pattern that existed before the event. Prior to the event, there was a high degree of co-movement among various assets; however, after the event, the CARs of different assets experienced severe 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 responses of 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 information cascade effect.

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

At the same time, 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, 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, as well as its tendency to