Interaction between Politics and the Crypto Assets Market: Analysis of the Trump Meme Coin Incident
Recently, Economics Letters published a research article titled "From Zero to Hero: The Spillover Effects of Meme Coins in the Crypto Assets Market." The study provides an in-depth analysis of an event where a political figure issued a Meme coin, revealing the heterogeneous volatility spillover effects driven by market sentiment and fundamentals. This event highlights the increasingly important role of political factors in shaping the Crypto Assets market and investor behavior.
Introduction
The impact of political dynamics on the financial markets is increasing day by day, and the Crypto Assets market has become an important area at the intersection of politics and finance. The 2024 U.S. presidential election further highlights this relationship, as a certain Republican candidate has unprecedentedly turned to support digital assets. He claims to make the U.S. the "crypto capital of the world," placing Crypto Assets at the core of his economic agenda, leading to market expectations of a more favorable policy stance during his potential term.
These are expected to be realized on January 18, 2025, when the politician issued their official Meme coin on a certain blockchain. Within 24 hours, the price of this token skyrocketed by 900%, with a trading volume reaching 18 billion USD, surpassing the market value of the largest Meme coin at that time by 4 billion USD.
The next day, the issuance of another Meme coin related to his family further fueled market speculation. These events are not only speculative in nature but also constitute a significant exogenous shock, the effects of which extend beyond the realm of financial speculation, sending signals of broader regulatory and political agendas.
This study aims to examine how this event acts as both a political signal and a financial event impacting the Crypto Assets market. The research focuses on three key questions:
How does the release of this Meme coin affect the returns and volatility of major Crypto Assets?
Did this event trigger a financial contagion effect in the Crypto Assets market?
Does this impact exhibit heterogeneity, manifested in different responses of Crypto Assets based on their technological foundations, uses, or speculative appeal?
To answer these questions, this article 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 ranked Crypto Assets by market capitalization for empirical analysis and found that after the release of the Meme coin, there was a significant volatility spillover effect among the Crypto Assets, indicating the presence of financial contagion in the market. The event triggered a major shift in market dynamics, with certain Crypto Assets recording the largest gains due to their infrastructure and strategic associations. Meanwhile, mainstream Crypto Assets such as Bitcoin and Ethereum exhibited strong resilience, with their cumulative abnormal returns (CARs) and variance stabilizing in the later stages of the event. In contrast, other Meme coins like Dogecoin and Shiba Inu experienced depreciation, and funds likely shifted towards newly issued Meme coins.
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Indeed, the issuance of this Meme coin occurred in a highly politically polarized environment in the United States, and the brand itself is closely related to strong political sentiments, thereby increasing investor sensitivity and exacerbating market reactions. For some investors, this endorsement symbolizes a unique speculative opportunity, giving rise to a strong "herding effect"; while other investors, aware of the controversial image, recognize the political and regulatory risks and adopt a more cautious stance. This polarization explains the observed high volatility and differentiated market reactions – 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 mainly focuses on the spillover between crypto assets internally or the spillover between crypto assets 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 the contagion mechanisms related to politically connected tokens, remain a gap in research.
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. Additionally, unlike previous studies that focused primarily on negative shocks ( such as the collapse of Bitcoin prices, the collapse of Terra-Luna, or the bankruptcy of certain exchanges or banks ), this study 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 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 the dynamics of financial contagion.
Data and Methods
2.1 Data and Sample Selection
This study uses proprietary data on the close mid-price ( close mid-price ), covering the 10 most representative crypto assets 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 comes from a centralized exchange in the United States, which is an exchange widely used in previous research, with specific data obtained from the LSEG Tick History database.
This dataset contains a total of 20,160 observations, with a time period from January 11, 2025, to January 25, 2025, covering the symmetric time frame of one week before and after the release of the Meme coin on January 18, 2025, (, which facilitates comparative analysis before and after the event.
According to the methods in existing literature, this study uses the following formula to calculate the Crypto Assets return rate:
Yield = ln)Pt ∕Pt−1(
Among them, Pt represents the price of digital assets at time t.
The event time is defined as January 18, 2025, Coordinated Universal Time ) UTC ( 2:44 AM, which marks the first official announcement of the new Meme coin release. Cumulative abnormal returns are calculated to assess the information cascade effect. This article calculates the average benchmark returns for each crypto asset 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 derive excess returns against 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 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 as follows:
[Mathematical formula omitted here]
Among them,
[Mathematical formula omitted here]
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, a contagion effect test is conducted. Considering the potential Type I error issue when using high-frequency data, this paper adopts a stricter significance level of α = 0.001.
Result
3.1 volatility spillover effect
The analysis results reveal the interrelationships between crypto assets. After the event occurred, the interconnectedness between assets significantly increased. This finding supports the hypothesis that "the event triggered a volatility spillover effect." At the same time, the volatility of the stable logarithmic returns increased, reflecting a phenomenon of rising market instability and accelerated adjustment speed. The returns of various crypto assets experienced severe fluctuations during the event, further emphasizing the systemic impact of this event.
The dynamic conditional covariance results estimated by the BEKK-MGARCH model indicate that the 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 asset pairs like ETH, SOL, and LINK, where the covariance significantly increases, showing stronger interconnection and a higher degree of market integration. In contrast, although SHIB and DOT also reached a significant level of 0.01, their impact was weaker. Additionally, some assets like LTC and XRP showed a decline in covariance after the event, indicating that the spillover effects are not uniformly distributed across all assets. Overall, the results highlight the structural impact of this Meme coin issuance event on the entire Crypto Assets market.
!7384156
3.2 Information Cascading Effect
The analysis of the cumulative abnormal returns ### CARs ( further reveals the information cascade effect triggered by the issuance of the Meme coin. The results indicate that this event has a significant structural impact on market dynamics, manifested as asset-specific response 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 a political figure who may be elected as the next 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 after the event occurs, three key dynamics are particularly prominent:
SOL has performed excellently, surpassing all other assets, which is likely related to its direct technical relationship as the blockchain supporting the Meme coin.
LINK also performed strongly, which may be related to its association with the large American technology company Oracle.
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 the effects of cascading speculation.
!7384157
At the same time, DOGE and other Meme coins like SHIB appear particularly weak, showing a clear asset substitution effect, where speculative funds have shifted from old Meme coins to newly issued tokens. Although AVAX and DOT have solid technical foundations, they have also not been immune to this trend of capital transfer, showing signs of value loss.
The issuance of this Meme coin broke the pre-event market co-movement pattern due to this exogenous shock. Before the event occurred, there was a high level of co-movement among various assets; however, after the event took place, the CARs of different assets displayed severe divergence, 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.
!7384158
Conclusion
This study examines the impact of the issuance of crypto assets related to political figures ), such as President Trump (, 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 its direct technical association with the Meme coin, SOL has benefited significantly. Assets that share the same underlying blockchain infrastructure have also been boosted by riding the "coattails" of this event.
!7384159
At the same time, mainstream crypto assets such as Bitcoin and Ethereum, due to their core position in the market, have demonstrated stronger stability and played a role similar to that of an anchor in this incident, stabilizing the overall market structure. This indicates that investor sentiment is no longer solely dependent on fundamental technical factors, but has also begun to significantly.
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Interaction between politics and the crypto market: Trump Meme coin triggers heterogeneous fluctuation spillover
Interaction between Politics and the Crypto Assets Market: Analysis of the Trump Meme Coin Incident
Recently, Economics Letters published a research article titled "From Zero to Hero: The Spillover Effects of Meme Coins in the Crypto Assets Market." The study provides an in-depth analysis of an event where a political figure issued a Meme coin, revealing the heterogeneous volatility spillover effects driven by market sentiment and fundamentals. This event highlights the increasingly important role of political factors in shaping the Crypto Assets market and investor behavior.
Introduction
The impact of political dynamics on the financial markets is increasing day by day, and the Crypto Assets market has become an important area at the intersection of politics and finance. The 2024 U.S. presidential election further highlights this relationship, as a certain Republican candidate has unprecedentedly turned to support digital assets. He claims to make the U.S. the "crypto capital of the world," placing Crypto Assets at the core of his economic agenda, leading to market expectations of a more favorable policy stance during his potential term.
These are expected to be realized on January 18, 2025, when the politician issued their official Meme coin on a certain blockchain. Within 24 hours, the price of this token skyrocketed by 900%, with a trading volume reaching 18 billion USD, surpassing the market value of the largest Meme coin at that time by 4 billion USD.
The next day, the issuance of another Meme coin related to his family further fueled market speculation. These events are not only speculative in nature but also constitute a significant exogenous shock, the effects of which extend beyond the realm of financial speculation, sending signals of broader regulatory and political agendas.
This study aims to examine how this event acts as both a political signal and a financial event impacting the Crypto Assets market. The research focuses on three key questions:
To answer these questions, this article 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 ranked Crypto Assets by market capitalization for empirical analysis and found that after the release of the Meme coin, there was a significant volatility spillover effect among the Crypto Assets, indicating the presence of financial contagion in the market. The event triggered a major shift in market dynamics, with certain Crypto Assets recording the largest gains due to their infrastructure and strategic associations. Meanwhile, mainstream Crypto Assets such as Bitcoin and Ethereum exhibited strong resilience, with their cumulative abnormal returns (CARs) and variance stabilizing in the later stages of the event. In contrast, other Meme coins like Dogecoin and Shiba Inu experienced depreciation, and funds likely shifted towards newly issued Meme coins.
!7384155
Indeed, the issuance of this Meme coin occurred in a highly politically polarized environment in the United States, and the brand itself is closely related to strong political sentiments, thereby increasing investor sensitivity and exacerbating market reactions. For some investors, this endorsement symbolizes a unique speculative opportunity, giving rise to a strong "herding effect"; while other investors, aware of the controversial image, recognize the political and regulatory risks and adopt a more cautious stance. This polarization explains the observed high volatility and differentiated market reactions – 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 mainly focuses on the spillover between crypto assets internally or the spillover between crypto assets 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 the contagion mechanisms related to politically connected tokens, remain a gap in research.
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. Additionally, unlike previous studies that focused primarily on negative shocks ( such as the collapse of Bitcoin prices, the collapse of Terra-Luna, or the bankruptcy of certain exchanges or banks ), this study 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 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 the dynamics of financial contagion.
Data and Methods
2.1 Data and Sample Selection
This study uses proprietary data on the close mid-price ( close mid-price ), covering the 10 most representative crypto assets 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 comes from a centralized exchange in the United States, which is an exchange widely used in previous research, with specific data obtained from the LSEG Tick History database.
This dataset contains a total of 20,160 observations, with a time period from January 11, 2025, to January 25, 2025, covering the symmetric time frame of one week before and after the release of the Meme coin on January 18, 2025, (, which facilitates comparative analysis before and after the event.
According to the methods in existing literature, this study uses the following formula to calculate the Crypto Assets return rate:
Yield = ln)Pt ∕Pt−1(
Among them, Pt represents the price of digital assets at time t.
The event time is defined as January 18, 2025, Coordinated Universal Time ) UTC ( 2:44 AM, which marks the first official announcement of the new Meme coin release. Cumulative abnormal returns are calculated to assess the information cascade effect. This article calculates the average benchmark returns for each crypto asset 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 derive excess returns against 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 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 as follows:
[Mathematical formula omitted here]
Among them,
[Mathematical formula omitted here]
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, a contagion effect test is conducted. Considering the potential Type I error issue when using high-frequency data, this paper adopts a stricter significance level of α = 0.001.
Result
3.1 volatility spillover effect
The analysis results reveal the interrelationships between crypto assets. After the event occurred, the interconnectedness between assets significantly increased. This finding supports the hypothesis that "the event triggered a volatility spillover effect." At the same time, the volatility of the stable logarithmic returns increased, reflecting a phenomenon of rising market instability and accelerated adjustment speed. The returns of various crypto assets experienced severe fluctuations during the event, further emphasizing the systemic impact of this event.
The dynamic conditional covariance results estimated by the BEKK-MGARCH model indicate that the 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 asset pairs like ETH, SOL, and LINK, where the covariance significantly increases, showing stronger interconnection and a higher degree of market integration. In contrast, although SHIB and DOT also reached a significant level of 0.01, their impact was weaker. Additionally, some assets like LTC and XRP showed a decline in covariance after the event, indicating that the spillover effects are not uniformly distributed across all assets. Overall, the results highlight the structural impact of this Meme coin issuance event on the entire Crypto Assets market.
!7384156
3.2 Information Cascading Effect
The analysis of the cumulative abnormal returns ### CARs ( further reveals the information cascade effect triggered by the issuance of the Meme coin. The results indicate that this event has a significant structural impact on market dynamics, manifested as asset-specific response 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 a political figure who may be elected as the next 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 after the event occurs, three key dynamics are particularly prominent:
!7384157
At the same time, DOGE and other Meme coins like SHIB appear particularly weak, showing a clear asset substitution effect, where speculative funds have shifted from old Meme coins to newly issued tokens. Although AVAX and DOT have solid technical foundations, they have also not been immune to this trend of capital transfer, showing signs of value loss.
The issuance of this Meme coin broke the pre-event market co-movement pattern due to this exogenous shock. Before the event occurred, there was a high level of co-movement among various assets; however, after the event took place, the CARs of different assets displayed severe divergence, 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.
!7384158
Conclusion
This study examines the impact of the issuance of crypto assets related to political figures ), such as President Trump (, 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 its direct technical association with the Meme coin, SOL has benefited significantly. Assets that share the same underlying blockchain infrastructure have also been boosted by riding the "coattails" of this event.
!7384159
At the same time, mainstream crypto assets such as Bitcoin and Ethereum, due to their core position in the market, have demonstrated stronger stability and played a role similar to that of an anchor in this incident, stabilizing the overall market structure. This indicates that investor sentiment is no longer solely dependent on fundamental technical factors, but has also begun to significantly.