| dc.contributor.author | León Castro, Ernesto | |
| dc.contributor.author | Espinoza Audelo, Luis Fernando | |
| dc.contributor.author | Avilés Ochoa, Ezequiel | |
| dc.contributor.author | Merigó, José M. | |
| dc.contributor.author | Kacprzyk, Janusz | |
| dc.date.accessioned | 2020-06-12T02:33:52Z | |
| dc.date.available | 2020-06-12T02:33:52Z | |
| dc.date.issued | 2019 | |
| dc.identifier.citation | Technological and Economic Development of Economy, Volume 25, Issue 4: pages: 576–599 | es_CL |
| dc.identifier.issn | 2029-4921 | |
| dc.identifier.uri | http://repositoriodigital.ucsc.cl/handle/25022009/1845 | |
| dc.description | Artículo de publicación SCOPUS | es_CL |
| dc.description.abstract | 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. | es_CL |
| dc.language.iso | es | es_CL |
| dc.publisher | Technological and Economic Development of Economy | es_CL |
| dc.source.uri | https://doi.org/10.3846/tede.2019.9374 | |
| dc.subject | Volatility | es_CL |
| dc.subject | IHOWMA operator | es_CL |
| dc.subject | Exchange rate | es_CL |
| dc.subject | Moving average | es_CL |
| dc.title | A new measure of volatility using induced heavy moving averages | es_CL |
| dc.type | Article | es_CL |
