Erschienen in:Stevens Institute of Technology School of Business Research Paper
Umfang:
1 Online-Ressource (39 p)
Sprache:
Englisch
DOI:
10.2139/ssrn.3352622
Identifikator:
Entstehung:
Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 11, 2019 erstellt
Beschreibung:
In this paper, we propose a new non-parametric density estimator derived from the theory of frames and Riesz bases. In particular, we propose the so-called bi-orthogonal density estimator based on the class of B-splines, and derive its theoretical properties including the asymptotically optimal choice of bandwidth. Detailed theoretical analysis and comparisons of our estimator with existing local basis and kernel density estimators are presented. The estimator is particularly well suited for high frequency data analysis in financial and economic markets