Understanding Regressions with Observations Collected at High Frequency over Long Span

Speaker: Dr Ye Lu

Affiliation: University of Sydney

Online via Zoom: https://uqz.zoom.us/j/87417665612

Abstract

In this paper, we analyze regressions with observations collected at small time intervals over a long period of time. For the formal asymptotic analysis, we assume that samples are obtained from continuous time stochastic processes, and let the sampling interval δ shrink down to zero and the sample span T increase up to infinity. In this setup, we show that the standard Wald statistic diverges to infinity and the regression becomes spurious as long as δ → 0 sufficiently fast relative to T → ∞. Such a phenomenon is indeed what is frequently observed in practice for the type of regressions considered in the paper. In contrast, our asymptotic theory predicts that the spuriousness disappears if we use the robust version of the Wald test with an appropriate long-run variance estimate. This is supported, strongly and unambiguously, by our empirical illustration.

About the presenter's meeting

Dr Lu is willing to have (30-min) 1-to-1 meeting with our colleagues and graduate students on the seminar day. Anyone who wants to meet with her on June 30th can contact Dr Fu Ouyang to book a time slot.