000			01894nam a2200229 a 4500
999			_c28760 _d28760
001			63606
020			_a 978-3319249254
082			_a.
100			_aGrabchak, Michael _958718
245	1	0	_aTempered stable distributions : _bstochastic models for multiscale processes _cMichael Grabchak
260			_aHeidelberg : _bSpringer, _cc2016.
300			_axii, 118 p. ; _c24 cm.
490	1		_aSpringer briefs in mathematics
505	0		_aIntroduction.- Preliminaries.- Tempered Stable Distributions.- Limit Theorems for Tempered Stable Distributions.- Multiscale Properties of Tempered Stable Levy Processes.- Parametric Classes.- Applications​.- Epilogue.- References.
520			_aThis brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.
650		7	_aFinance _925
650		7	_aMathematics _9984
650		7	_aEconomics, Mathematical _917931
650		7	_aProbabilities _95449
856			_uhttps://uowd.box.com/s/tsxocw67f638sosi2wjho6dr0tt84g3j _zLocation Map
942			_cREGULAR _2ddc