Sentiment Without Structure: Differential Market Responses to Infrastructure vs Regulatory Events in Cryptocurrency Markets

TL;DR

The paper investigates whether cryptocurrency markets react differently to infrastructure failures versus regulatory enforcement by introducing a four-category event framework (Infrastructure/Regulatory × Positive/Negative) and applying an event-study design to 31 qualifying events across BTC, ETH, SOL, and ADA. It employs both a Constant Mean and a Market Model with block bootstrap inference to account for cross-sectional correlation, using a 250-day estimation window and a $[-5, +30]$ event window, with extensive robustness checks. The primary finding is a null difference between infra- and regulatory-negative events, with mean CARs of $-7.6 ext{%}$ and $-11.1 ext{%}$ respectively and a difference of $+3.6$ pp (CI wide; $p=0.81$), suggesting markets respond similarly to these shock types when valence is controlled. The study demonstrates methodological improvements and highlights the need for larger samples, pre-registered hypotheses, and potentially intraday data to test the theoretical distinction between bounded infrastructure uncertainty and unbounded regulatory uncertainty. Overall, the results are exploratory and indicate that, within the current sample, enforcement capacity as a mechanism does not exhibit a clear, statistically significant dominance over infrastructure shocks in crypto markets.

Abstract

We investigate differential market responses to infrastructure versus regulatory events in cryptocurrency markets using event study methodology with 4-category event classification. From 50 candidate events (2019-2025), 31 meet our impact and estimation-data criteria across 4 cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Solana (SOL), and Cardano (ADA). We employ constant mean and market-adjusted models with event-level block bootstrap confidence intervals (CIs) that properly account for cross-sectional correlation. Our primary comparison focuses on negative-valence events: infrastructure failures (10 events identified; 8 with sufficient estimation data for analysis) versus regulatory enforcement (7 events). We find infrastructure failures produce mean Cumulative Abnormal Return (CAR) of -7.6% (bootstrap 95% CI: [-25.8%, +11.3%]) and regulatory enforcement produces mean CAR of -11.1% (CI: [-31.0%, +10.7%]). The difference in mean CARs of +3.6 percentage points (pp) has CI [-25.3%, +30.9%], p = 0.81. This is a null finding: markets respond similarly to both shock types when controlling for event valence. Robustness checks confirm: (1) consistent negative sign across all window specifications ([0, +1] to [-5, +30]), (2) results survive leave-one-out exclusion of FTX and Terra, (3) market model with BTC/equal-weighted (EW) proxy attenuates but does not flip results. The 4-category classification addresses prior conflation of upgrades with failures. Interpretation note: This exploratory analysis should be treated as hypothesis-generating; any post-hoc theoretical framing requires prospective testing with larger samples.