Sustainable risk management: fuzzy approach to volatility and application on ftse 100 index

Peker, Sinem; Tvaronavičienė, Manuela; Aktan, Bora

doi:10.9770/jesi.2014.2.1(4)

Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/146743

Sustainable risk management: fuzzy approach to volatility and application on ftse 100 index

Details

Publication Type (CRIS)

Straipsnis kitoje duomenų bazėje / Article in other database (S4)

Publication Type (eLABa)

Straipsnis kitoje DB / Article in other DB (S3)

VILNIUS TECH Research Priorities and Topics

Socioekonominių sistemų universalaus tvarumo tyrimai / Universal sustainability research (VE05)

Lithuanian Intelligent Specialization

Įtrauki ir kūrybinga visuomenė / Inclusive and creative society (L103)

Author(s)

Author	Affiliation
Peker, Sinem	Yasar University, Turkey
Tvaronavičienė, Manuela	Ekonomikos inžinerijos katedra / Department of Economics Engineering (1149)
Aktan, Bora	University of Bahrain, Isa Town, Kingdom of Bahrain

Title

Sustainable risk management: fuzzy approach to volatility and application on ftse 100 index

[en]

Sinem Peker, Manuela Tvaronavičienė, Bora Aktan

Is part of

Entrepreneurship and sustainability issues

Published In

Year	Volume	Start Page	End Page
2014	2	30	36

Publisher

Vilnius : Entrepreneurship and Sustainability Center

Referenced in Database(s)(DBs)

Index Copernicus

Extent

p. 30-36

URI

URI
https://hdl.handle.net/20.500.14911/146743

DOI

10.9770/jesi.2014.2.1(4)

Cited references

Science / Art Area

Socialiniai mokslai / Social sciences (S)

Field of Science / Art

Ekonomika / Economics (S004)

Keywords (en)

Abstract (en)

In this paper, a fuzzy volatility labeling algorithm is offered to detect the periods with abnormal activities on daily share returns. Considering the vagueness in the switches of the time periods, the membership functions of high and normal volatility classes are introduced. In the assignments, both the density structure and membership degree are used. It is believed that this algorithm may be helpful to construct different estimation models for the time periods with normal and abnormal activities. Authors offer algorithm, which can be used as a tool for sustainable risk management.