TY  - UNPD
A1  - Kolokolov, Aleksey
A1  - Livieri, Giulia
A1  - Pirino, Davide
T1  - Statistical inferences for price staleness
T2  - SAFE working paper series ; No. 236
N2  - Asset transaction prices sampled at high frequency are much staler than one might expect in the sense that they frequently lack new updates showing zero returns. In this paper, we propose a theoretical framework for formalizing this phenomenon. It hinges on the existence of a latent continuous-time stochastic process pt valued in the open interval (0; 1), which represents at any point in time the probability of the occurrence of a zero return. Using a standard infill asymptotic design, we develop an inferential theory for nonparametrically testing, the null hypothesis that pt is constant over one day. Under the alternative, which encompasses a semimartingale model for pt, we develop non-parametric inferential theory for the probability of staleness that includes the estimation of various integrated functionals of pt and its quadratic variation. Using a large dataset of stocks, we provide empirical evidence that the null of the constant probability of staleness is fairly rejected. We then show that the variability of pt is mainly driven by transaction volume and is almost unaffected by bid-ask spread and realized volatility.
T3  - SAFE working paper - 236 
KW  - staleness
KW  - idle time
KW  - liquidity
KW  - zero returns
KW  - stable convergence
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/48376
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-483762
UR  - https://ssrn.com/abstract=3283628
IS  - November 6, 2018
PB  - SAFE
CY  - Frankfurt am Main
ER  -