Original title: Speculative Swells and the Memecoin Aftermath
Original author: Stanford Blockchain Club
Original translation: Peisen, BlockBeats
Editor’s Note:
This article uses the Base network as an example to explore in depth how the launch of the meme coin BRETT in early 2024 triggered a significant market event, leading to a shift in user behavior and trading patterns. Through the analysis of supply and demand, the study reveals the subtle interaction between rising gas fees and trading activity, demonstrating the far-reaching impact of this catalyst event on network users.
This paper not only quantifies the impact of the BRETT event on transaction behavior through regression models, but also further explores how this external shock amplifies users’ sensitivity to transaction costs, leading to a sharp drop in demand. This phenomenon reflects the vulnerability of blockchain networks in the face of unexpected events and their rapidly changing nature.
introduction
For most people, unexpected disruptions in supply chains offer little benefit. For researchers, however, these disruptions provide valuable opportunities to understand market dynamics that are difficult to untangle under normal circumstances. For example, because prices and quantities are direct manifestations of supply and demand, it can be difficult to tell whether supply, demand, or a combination of both is affecting the market. This leads to the old saying: "Don't reason from price changes alone." But when one of these factors suddenly changes in a predictable way, sometimes you can draw conclusions from it.
For example, a study from the NBER used the supply shock caused by COVID-19 to understand demand dynamics, showing how such sudden external shocks can be a significant redistributive force affecting employment and sales in the U.S. economy. By analyzing behavioral changes during rare market events, researchers are able to turn crises into opportunities for deeper economic insights.
Blockchain networks operate with inherent capacity limitations similar to production lines. Each block has a fixed capacity for transaction data, making space a scarce resource. As transaction demand increases, competition for block space increases, which can lead to network congestion.
In March of this year, Ethereum implemented the EIP-4844 proposal, which aims to increase network capacity and reduce Layer-2 transaction costs, allowing networks like Arbitrum and Optimism to enjoy significant gas fee reductions. However, shortly after the implementation of the proposal, the Base network's gas price surged, exceeding the level before the launch of EIP-4844.
Base has seen a significant increase in user activity during this period, driven primarily by DeFi trading activity. This surge was particularly unexpected given that Base's ecosystem has historically leaned toward consumer-oriented applications. Originally incubated by the Coinbase team, Base has benefited from extensive marketing and branding efforts to build a chain that encourages creators, developers, and community participation. As a result, the ecosystem is primarily composed of consumer applications, with the most successful applications, such as Friend.tech, being consumer-oriented.
The reversal in Base user activity and the sudden surge in transaction volume can likely be attributed to a supply shock triggered by an unexpected external event, which affected the system’s supply chain. Such shocks can significantly alter availability and costs, fundamentally changing user behavior and network dynamics.
Catalyst Hunting
To constitute a true supply shock, the event must be exogenous, unexpected, and strong enough to disrupt established market dynamics.
One of the most notable changes after the implementation of the EIP-4844 proposal was the sudden increase in decentralized exchange (DEX) trading volume, which has expanded beyond typical stablecoins and ETH to new token categories. Previously, transactions on the Base network were mainly concentrated in these categories, with meme coins accounting for an average of less than 15% of all DEX weekly trading volume.
Historically, meme coin crazes are often triggered by a "beacon" token that attracts significant market interest and sets new trading benchmarks. This phenomenon is likely driven by factors such as information waterfalls. On platforms such as Crypto Twitter, successful trading stories are amplified, while failures are often ignored, leading to a skewed perception of potential gains. When traders observe and imitate the behavior of others, assuming that they have valuable information, a self-reinforcing cycle is formed. This quickly drives up the price of meme coins and often leads to wild market fluctuations.
For example, on Solana, the market cap of the dogwifhat (WIF) token surged from less than $1 million to billions of dollars in a matter of months in late 2023. The success of WIF sparked a meme coin frenzy on Solana, with an increase in meme coin issuance and the development of meme coin infrastructure.
Although meme coins have existed since the launch of the Base network, no meme coin had attracted widespread market attention until March of this year. The initial launch of the Mainnet was driven by a meme coin trading frenzy. Thousands of users flocked to Base to trade meme coins before the network officially launched. As new applications were launched, trading activity for these tokens gradually decreased. Inspired by the characters in the popular Pepe-themed books, the BRETT token was launched in late February to early March and quickly rose to prominence on Base, reaching a market cap of $350 million before the emergence of large-scale meme trading activity. Its rapid rise not only deviated from typical market trends, but also triggered a broader trading boom across the network.
The initial success of the BRETT token attracted speculative traders through a potential copycat effect, attracting a new group of users who are more focused on meme trading rather than participating in network applications. While this group has a narrower focus, it is worth exploring the ripple effects of this meme craze on the existing user base of the Base ecosystem, especially how their typical behaviors changed as a result of this event. Although it is impossible to confirm that the observed congestion was directly caused by the BRETT token event based on surface data alone, it prompted us to conduct further more detailed analysis to accurately assess its direct impact on user behavior and demand.
Experimental design
The main goal of this experiment is to analyze the supply and demand dynamics on the Base network, focusing on the interaction between gas fees (supply) and transaction activity (demand) before, during, and after the BRETT event. A key part of this analysis is to separate the impact of the BRETT launch from general market behavior.
To gain a clear insight into market dynamics, we will exclude trading activity directly related to the BRETT token. Our analysis will focus on addresses that were already active before the token went live in late February, allowing us to assess a persistent user base that is not influenced by speculative interest in new tokens. This approach ensures that our study of broader user behavior on the Base network is unbiased and not disproportionately influenced by users who are primarily focused on BRETT.
Model design
In this study, we used a regression model with a core binary variable to analyze the impact of the BRETT launch. The variables in the model and their functions were chosen to reflect the subtle impact of this market event.
The model is defined as follows:
in:
Average Gas Usage (Q): represents the average Gas usage over time, which is a key indicator of transaction complexity and network load.
Impact indicator (D): A binary variable that indicates whether the BRETT token event has occurred (0 before launch, 1 after launch).
Gas Fee (P): Indicates the Gas price at the time, in gwei.
· Interaction term (DP): used to capture the interactive effect between the BRETT shock and Gas price.
Transaction Count (T): represents the number of transactions at a given time. It is used to understand how changes in transaction volume affect network congestion and gas usage.
It is important to note that this model is relatively simple in its current form and is primarily intended to reveal changes in demand associated with this particular catalyst. The model does not account for endogeneity that may come from baseline conditions or other underlying trends, which may obscure true causality and demand elasticity prior to the event. For example, there may be omitted variables and there may be simultaneous causality between gas usage and fees, which, combined with other noise, may affect the accuracy of our initial estimates.
Nonetheless, the model allows us to determine whether the BRETT shock leads to a significant change in trading behavior on the Base network that is independent of direct BRETT trading activity.
Regression results
By analyzing the hour-by-hour non-BRETT-related user groups from early January to late May 2024, we can draw the following conclusions about the launch of the BRETT token and its first surge:
After the launch of the BRETT token, users showed a significant behavioral shift in response to rising Gas prices. The regression model shows a significant negative interaction term (₃=−0.333), which indicates that the increase in Gas fees after the launch of the token is likely to have suppressed users' trading behavior.
Specifically, the interaction term shows that after the meme event, for every one standard deviation increase in gas price (Δ=1.2×10⁵ gwei), gas usage (Δ) will decrease by 41,200 gwei, equivalent to 79% of the typical hourly standard deviation. In other words, the model predicts that during high congestion events, for every one standard deviation increase in gas price, demand will decrease by approximately 0.79 standard deviations.
Overall, the introduction of the meme coin “beacon” BRETT had a negative knock-on effect on Base’s initial user base. The congestion caused by the catalyst exacerbated this group’s sensitivity to rising gas prices, making them more averse to transaction costs — even if those costs were close to pre-EIP-4844 levels.
Zoom in
BRETT’s impact on Base demonstrates the broader fragility and adaptive behavior of users in the crypto ecosystem. The incident highlights how emerging tokens, especially unexpected events, can significantly affect trading metrics, user behavior, and network stability, reflecting the rapidity of dynamic changes within the blockchain operating framework.
This event highlights the delicate relationship between supply (in this case, network fees) and user demand, which is not a simple linear relationship. Demand can shift suddenly, as in the BRETT event, or evolve gradually as the ecosystem matures. These changes highlight the complex interplay between network adjustments and user reactions, which are not always predictable and can vary widely in response to external shocks or anticipated network upgrades.
Looking ahead, as more exogenous events or known upgrades occur, understanding these underlying dynamics becomes critical. Identifying patterns and potential user reactions to changes within the ecosystem can help predict more realistic user dynamics and reactions.
