bibtype J - Journal Article
ARLID 0346486
utime 20240103193754.2
mtime 20100914235959.9
WOS 000282241600043
DOI 10.1016/j.physa.2010.06.054
title (primary) (eng) Monte Carlo-based tail exponent estimator
specification
page_count 12 s.
serial
ARLID cav_un_epca*0257423
ISSN 0378-4371
title Physica. A : Statistical Mechanics and its Applications
volume_id 389
volume 21 (2010)
page_num 4863-4874
publisher
name Elsevier
keyword Hill estimator
keyword α-stable distributions
keyword Tail exponent estimation
author (primary)
ARLID cav_un_auth*0242028
name1 Baruník
name2 Jozef
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101217
name1 Vácha
name2 Lukáš
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
institution UTIA-B
full_dept Department of Econometrics
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2010/E/barunik-0346486.pdf
cas_special
project
project_id GA402/09/0965
agency GA ČR
ARLID cav_un_auth*0253176
project
project_id GD402/09/H045
agency GA ČR
ARLID cav_un_auth*0253998
project
project_id GP402/08/P207
agency GA ČR
ARLID cav_un_auth*0241655
research CEZ:AV0Z10750506
abstract (eng) In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. Our proposed method is not sensitive to the choice of tail size and works well also on small data samples. The new estimator also gives unbiased results with symmetrical confidence intervals.
reportyear 2011
RIV AH
permalink http://hdl.handle.net/11104/0187507
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mrcbU63 cav_un_epca*0257423 Physica. A : Statistical Mechanics and its Applications 0378-4371 1873-2119 Roč. 389 č. 21 2010 4863 4874 Elsevier