KFU. Card publication. Short-term fuzzy forecasting of Brent oil prices

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

SHORT-TERM FUZZY FORECASTING OF BRENT OIL PRICES

Form of presentation

Articles in international journals and collections

Year of publication

2015

Язык

английский

Authors, employees of KFU

Ismagilov Ilyas Idrisovich, author

Authors, postgraduates KFU

Khasanova Svetlana Fanilevna, postgraduate kfu

Bibliographic description in the original language

Ismagilov, I.I., Khasanova, S.F. (2015) Short-Term Fuzzy Forecasting of Brent Oil Prices. Asian Social Science, 11 ( 11 ) pp. 60 - 67 .

Annotation

Oil prices movements is very important macroeconomic factor for decision making. The accuracy of results for different types of oil brands depends on models and algorithms. This paper evaluates the effectiveness of using fuzzy sets to forecast daily Brent oil prices. It also contains possible modifications of the proposed method and in comparison with basic methods. The results suggest that Brent oil prices series have short memory because using information about last 2-days prices shows better forecast accuracy. Forecasting based on fixed universe of discourse shows better efficiency and it also proves that oil prices series has short memory. Adding the probability of switching between linguistic terms in defuzzification function could be used to improve accuracy of predictions. Also the approach can take into consideration expert?s opinion about direction of future variation. The effective expert?s work can reduce errors of forecast from 1.5% till 0.76%. But this modification can be used if experts correctly guess the direction of the change in trend in eight out of ten cases and more. The reasonable obtained results can be used by analysts dealing with the prediction of oil prices.

Keywords

Brent, Expert?s opinion, Forecast, Fuzzy logic, Fuzzy sets, Petroleum prices, Prediction, Soft computing, Stock market, Time series

The name of the journal

Asian Social Science

URL

http://www.ccsenet.org/journal/index.php/ass/article/view/48318

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=82938&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Ismagilov Ilyas Idrisovich	ru_RU
dc.contributor.author	Khasanova Svetlana Fanilevna	ru_RU
dc.date.accessioned	2015-01-01T00:00:00Z	ru_RU
dc.date.available	2015-01-01T00:00:00Z	ru_RU
dc.date.issued	2015	ru_RU
dc.identifier.citation	Ismagilov, I.I., Khasanova, S.F. (2015) Short-Term Fuzzy Forecasting of Brent Oil Prices. Asian Social Science, 11 ( 11 ) pp. 60 - 67 .	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=82938&p_lang=2	ru_RU
dc.description.abstract	Asian Social Science	ru_RU
dc.description.abstract	Oil prices movements is very important macroeconomic factor for decision making. The accuracy of results for different types of oil brands depends on models and algorithms. This paper evaluates the effectiveness of using fuzzy sets to forecast daily Brent oil prices. It also contains possible modifications of the proposed method and in comparison with basic methods. The results suggest that Brent oil prices series have short memory because using information about last 2-days prices shows better forecast accuracy. Forecasting based on fixed universe of discourse shows better efficiency and it also proves that oil prices series has short memory. Adding the probability of switching between linguistic terms in defuzzification function could be used to improve accuracy of predictions. Also the approach can take into consideration expert?s opinion about direction of future variation. The effective expert?s work can reduce errors of forecast from 1.5% till 0.76%. But this modification can be used if experts correctly guess the direction of the change in trend in eight out of ten cases and more. The reasonable obtained results can be used by analysts dealing with the prediction of oil prices.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Brent	ru_RU
dc.subject	Expert?s opinion	ru_RU
dc.subject	Forecast	ru_RU
dc.subject	Fuzzy logic	ru_RU
dc.subject	Fuzzy sets	ru_RU
dc.subject	Petroleum prices	ru_RU
dc.subject	Prediction	ru_RU
dc.subject	Soft computing	ru_RU
dc.subject	Stock market	ru_RU
dc.subject	Time series	ru_RU
dc.title	Short-term fuzzy forecasting of Brent oil prices	ru_RU
dc.type	Articles in international journals and collections	ru_RU