bibtype J - Journal Article
ARLID 0507285
utime 20240103222354.9
mtime 20190806235959.9
SCOPUS 84890847491
WOS 000333778400007
DOI 10.1016/j.eneco.2013.12.001
title (primary) (eng) Commodity futures and market efficiency
specification
page_count 8 s.
media_type P
serial
ARLID cav_un_epca*0250426
ISSN 0140-9883
title Energy Economics
volume_id 42
volume 1 (2014)
page_num 50-57
publisher
name Elsevier
keyword Commodities
keyword Long-term memory
keyword Fractal dimension
author (primary)
ARLID cav_un_auth*0256902
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
full_dept Department of Econometrics
share 50
name1 Krištoufek
name2 Ladislav
institution UTIA-B
country CZ
garant K
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101230
name1 Vošvrda
name2 Miloslav
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/2019/E/kristoufek-0507285.pdf
cas_special
project
ARLID cav_un_auth*0377936
project_id GA402/09/0965
agency GA ČR
project
ARLID cav_un_auth*0377937
project_id GAP402/11/0948
agency GA ČR
country CZ
abstract (eng) We analyze the market efficiency of 25 commodity futures across various groups—metals, energies, soft com- modities, grains and other agricultural commodities. To do so, we utilize the recently proposed Efficiency Index to find out that the most efficient among all of the analyzed commodities is heating oil, closely followed by WTI crude oil, cotton, wheat, and coffee. On the other end of the ranking scale we find live cattle and feeder cattle. The efficiency is also found to be characteristic for specific groups of commodities, with energy commod- ities being the most efficient and other agricultural commodities (composed mainly of livestock) the least effi- cient groups. We also discuss contributions of long-term memory, fractal dimension and approximate entropy to the total inefficiency. Last but not least, we come across the nonstandard relationship between the fractal dimension and the Hurst exponent. For the analyzed dataset, the relationship between these two variables is pos- itive, meaning that local persistence (trending) is connected to global anti-persistence. We attribute this behavior to specifics of commodity futures: they may be predictable over a short term and locally, but over a long term they return to their fundamental prices.
result_subspec WOS
RIV AH
FORD0 50000
FORD1 50200
FORD2 50202
reportyear 2020
num_of_auth 2
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0298748
confidential S
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mrcbU14 84890847491 SCOPUS
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mrcbU63 cav_un_epca*0250426 Energy Economics 0140-9883 1873-6181 Roč. 42 č. 1 2014 50 57 Elsevier