Testing for an Explosive Bubble using High-Frequency Volatility

TL;DR

This paper introduces a new statistical test using high-frequency volatility data to detect explosive bubbles in financial markets, with applications to cryptocurrencies and stocks, and includes a real-time date-stamping strategy.

Contribution

It develops a nuisance-parameter-free explosive bubble test based on high-frequency data and proposes a real-time date-stamping method for identifying explosive regimes.

Findings

The test has good size and power properties in simulations.

The method successfully detects explosive behavior in real market data.

The real-time date-stamping strategy is consistent under certain conditions.

Abstract

Based on a continuous-time stochastic volatility model with a linear drift, we develop a test for explosive behavior in financial asset prices at a low frequency when prices are sampled at a higher frequency. The test exploits the volatility information in the high-frequency data. The method consists of devolatizing log-asset price increments with realized volatility measures and performing a supremum-type recursive Dickey-Fuller test on the devolatized sample. The proposed test has a nuisance-parameter-free asymptotic distribution and is easy to implement. We study the size and power properties of the test in Monte Carlo simulations. A real-time date-stamping strategy based on the devolatized sample is proposed for the origination and conclusion dates of the explosive regime. Conditions under which the real-time date-stamping strategy is consistent are established. The test and the date-stamping strategy are applied to study explosive behavior in cryptocurrency and stock markets.