Local mispricing and microstructural noise: A parametric perspective

Andersen, Torben G.; Archakov, Ilya; Cebiroğlu, Gökhan; Hautsch, Nikolaus

doi:10.1016/j.jeconom.2021.06.006

Cited by 13 publications

(3 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, we believe that mixed semimartingales with H > 1 2 have the potential to serve as a semiparametric model of return persistence, which has been documented in high-frequency data in a series of recent work (see e.g. [4,5,15,28]). We shall leave it to future work to examine this direction of research.…”

mentioning

confidence: 88%

Rate-optimal estimation of mixed semimartingales

Chong¹,

Delerue²,

Mies³

2022

Preprint

View full text Add to dashboard Cite

Consider the sum Y = B + B(H) of a Brownian motion B and an independent fractional Brownian motion B(H) with Hurst parameter H ∈ (0, 1). Surprisingly, even though B(H) is not a semimartingale, Cheridito proved in [Bernoulli 7 (2001) that Y is a semimartingale if H > 3/4. Moreover, Y is locally equivalent to B in this case, so H cannot be consistently estimated from local observations of Y . This paper pivots on a second surprise in this model: if B and B(H) become correlated, then Y will never be a semimartingale, and H can be identified, regardless of its value. This and other results will follow from a detailed statistical analysis of a more general class of processes called mixed semimartingales, which are semiparametric extensions of Y with stochastic volatility in both the martingale and the fractional component. In particular, we derive consistent estimators and feasible central limit theorems for all parameters and processes that can be identified from high-frequency observations. We further show that our estimators achieve optimal rates in a minimax sense. The estimation of mixed semimartingales with correlation is motivated by applications to high-frequency financial data contaminated by rough noise.

show abstract

mentioning

confidence: 88%

Rate-optimal estimation of mixed semimartingales

Chong¹,

Delerue²,

Mies³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The issue was further highlighted by the May 2010 "flash crash" in the S&P 500 e-mini futures market analyzed by Kirilenko et al (2017), while the more general phenomenon of "drift burst" was studied systematically in the volatility measurement setting by Christensen et al (2019). Finally, the presence of relatively frequent and randomly occurring instances of persistent return serial correlation is identified in Andersen et al (2020).…”

Section: Introductionmentioning

confidence: 99%

“…For extensive discussion of such heterogeneous and incomplete information rationales behind the observed return persistence, seeAndersen et al (2020).…”

mentioning

confidence: 99%