Are volatility estimators robust with respect to modeling assumptions?

Are volatility estimators robust with respect to modeling assumptions?

We consider microstructure as an arbitrary contamination of the underlying latent securities price, through a Markov kernel Q. Special cases include additive error, rounding and combinations thereof. Our main result is that, subject to smoothness conditions, the two scales realized volatility is robust to the form of contamination Q. To push the limits of our result, we show what happens for so...

Robust Estimators are Hard to Compute

In modern statistics, the robust estimation of parameters of a regression hyperplane is a central problem. Robustness means that the estimation is not or only slightly affected by outliers in the data. In this paper, it is shown that the following robust estimators are hard to compute: LMS, LQS, LTS, LTA, MCD, MVE, Constrained M estimator, Projection Depth (PD) and Stahel-Donoho. In addition, a...

Analyzing Cortical Network Dynamics with Respect to Different Connectivity Assumptions

Current studies of cortical network dynamics are usually based on purely random wiring. Generally, these studies are focused on a local scale, where about 10 percent of all possible connections are realized. Neuronal connections in the cortex, however, show a more complex spatial pattern composed of local and long-range patchy connections. Here, we ask to what extent the assumption of such geom...

a comparison of teachers and supervisors, with respect to teacher efficacy and reflection

supervisors play an undeniable role in training teachers, before starting their professional experience by preparing them, at the initial years of their teaching by checking their work within the proper framework, and later on during their teaching by assessing their progress. but surprisingly, exploring their attributes, professional demands, and qualifications has remained a neglected theme i...

Bridge Homogeneous Volatility Estimators