Variance-Ratio Statistics and High-Frequency Data

Variance-ratio tests are routinely employed to assess the variation in return volatility over time and across markets. However, such tests are not statistically robust and can be seriously misleading within a high-frequency context. We develop improved inference procedures using a Fourier Flexible Form regression framework. The practical significance is illustrated through tests for changes in the FX intraday volatility pattern following the removal of trading restrictions in Tokyo. Contrary to earlier evidence, we find no discernible changes outside of the Tokyo lunch period. We ascribe the difference to the fragile finite-sample inference of conventional variance-ratio procedures and a single outlier.