Stablecoins as Dry Powder: A Copula-Based Risk Analysis of Cryptocurrency Markets

2026-03-24

AI Summary

This study investigates the structural role of stablecoins as a channel for systemic risk transmission in cryptocurrency markets. For the first time, stablecoins are conceptualized as “dry powder” capital, and an analytical framework based on Copula models is developed to quantify their influence—across multiple time scales—on market volatility and trading activity. The approach integrates time-series analysis of volatility and trading volume with causal inference techniques. Empirical results demonstrate that incorporating a stablecoin factor significantly reduces the mean squared error in volatility forecasting and enhances risk management effectiveness within volatility-targeting strategies. These findings offer novel insights for both portfolio allocation in crypto assets and regulatory oversight of digital financial markets.

Technology Category

• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Reasoning under Uncertainty: Causality
• Cognitive Modeling & Cognitive Systems: Other Foundations of Cognitive Modeling & Systems

Application Category

• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies
• Security and Privacy: Cryptocurrency and smart contracts
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Stablecoins serve as the fundamental infrastructure for Decentralised Finance (DeFi), acting as the primary bridge between fiat currencies and the digital asset ecosystem. While peg stability is well-documented, the structural role stablecoins play in transmitting systemic risk to the broader market remains under-explored. This study uses copula-based approaches to quantify the transmission of volatility and activity from stablecoin to cryptocurrency markets. We demonstrate in-sample causality across daily, weekly, and monthly horizons. Furthermore, we show that incorporating stablecoin factors significantly reduces Mean Squared Error in cryptocurrency forecasting. Specifically, we link stablecoin volume and upside volatility to broader market volatility, indicating its role as dry powder. Finally, we establish economic value by demonstrating reduced risk in a cryptocurrency volatility targeting model when stablecoin factors are employed.

Problem

• stablecoins
• systemic risk
• cryptocurrency markets
• volatility transmission
• dry powder

Innovation

• copula-based analysis
• stablecoin risk transmission
• volatility forecasting
• DeFi infrastructure
• dry powder