@article{725829,
      recid = {725829},
      author = {Belomestny, Denis,},
      title = {Lévy matters IV estimation for discretely observed Lévy  processes / [electronic resource] :},
      pages = {1 online resource (xv, 286 pages) :},
      abstract = {The aim of this volume is to provide an extensive account  of the most recent advances in statistics for discretely  observed Lévy processes. These days, statistics for  stochastic processes is a lively topic, driven by the needs  of various fields of application, such as finance, the  biosciences, and telecommunication. The three chapters of  this volume are completely dedicated to the estimation of  Lévy processes, and are written by experts in the field.  The first chapter by Denis Belomestny and Markus Rei€  treats the low frequency situation, and estimation methods  are based on the empirical characteristic function. The  second chapter by Fabienne Comte and Valery Genon-Catalon  is dedicated to non-parametric estimation mainly covering  the high-frequency data case. A distinctive feature of this  part is the construction of adaptive estimators, based on  deconvolution or projection or kernel methods. The last  chapter by Hiroki Masuda considers the parametric  situation. The chapters cover the main aspects of the  estimation of discretely observed Lévy processes, when the  observation scheme is regular, from an up-to-date  viewpoint.},
      url = {http://library.usi.edu/record/725829},
      doi = {https://doi.org/10.1007/978-3-319-12373-8},
}