A new measure of volatility using induced heavy moving averages

León-Castro, E; Espinoza-Audelo, LF; Aviles-Ochoa, E; Merigó, JM; Kacprzyk, J

A new measure of volatility using induced heavy moving averages

León-Castro, E Espinoza-Audelo, LF Aviles-Ochoa, E Merigó, JM

Kacprzyk, J

Permalink

Publication Type:: Journal Article
Citation:: Technological and Economic Development of Economy, 2019, 25 (4), pp. 576 - 599
Issue Date:: 2019-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published VersionAdobe PDF (388.38 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	León-Castro, E	en_US
dc.contributor.author	Espinoza-Audelo, LF	en_US
dc.contributor.author	Aviles-Ochoa, E	en_US
dc.contributor.author	Merigó, JM https://orcid.org/0000-0002-4672-6961	en_US
dc.contributor.author	Kacprzyk, J	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Technological and Economic Development of Economy, 2019, 25 (4), pp. 576 - 599	en_US
dc.identifier.issn	2029-4913	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137472
dc.description.abstract	Copyright © 2019 The Author(s). Published by VGTU Pr. The volatility is a dispersion technique widely used in statistics and economics. This paper presents a new way to calculate volatility by using different extensions of the ordered weighted average (OWA) operator. This approach is called the induced heavy ordered weighted moving average (IHOWMA) volatility. The main advantage of this operator is that the classical volatility formula only takes into account the standard deviation and the average, while with this formulation it is possible to aggregate information according to the decision maker knowledge, expectations and attitude about the future. Some particular cases are also presented when the aggregation information process is applied only on the standard deviation or on the average. An example in three different exchange rates for 2016 are presented, these are for: USD/MXN, EUR/MXN and EUR/USD.	en_US
dc.relation.ispartof	Technological and Economic Development of Economy	en_US
dc.relation.isbasedon	10.3846/tede.2019.9374	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A new measure of volatility using induced heavy moving averages	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	25	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	0104 Statistics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	open_access	*
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	25	en_US

Abstract:

Copyright © 2019 The Author(s). Published by VGTU Pr. The volatility is a dispersion technique widely used in statistics and economics. This paper presents a new way to calculate volatility by using different extensions of the ordered weighted average (OWA) operator. This approach is called the induced heavy ordered weighted moving average (IHOWMA) volatility. The main advantage of this operator is that the classical volatility formula only takes into account the standard deviation and the average, while with this formulation it is possible to aggregate information according to the decision maker knowledge, expectations and attitude about the future. Some particular cases are also presented when the aggregation information process is applied only on the standard deviation or on the average. An example in three different exchange rates for 2016 are presented, these are for: USD/MXN, EUR/MXN and EUR/USD.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/137472