000129591 001__ 129591
000129591 005__ 20240104102230.0
000129591 0247_ $$2doi$$a10.1080/14697688.2010.516766
000129591 0248_ $$2sideral$$a68236
000129591 037__ $$aART-2012-68236
000129591 041__ $$aeng
000129591 100__ $$0(orcid)0000-0001-5629-7526$$aBlasco, Natividad$$uUniversidad de Zaragoza
000129591 245__ $$aDoes herding affect volatility? Implications for the Spanish stock market
000129591 260__ $$c2012
000129591 5060_ $$aAccess copy available to the general public$$fUnrestricted
000129591 5203_ $$aAccording to rational expectation models, uninformed or liquidity trading make market price volatility rise. This paper sets out to analyse the impact of herding, which may be interpreted as one of the components of uninformed trading, on the volatility of the Spanish stock market. Herding is examined at the intraday level, considered the most reliable sampling frequency for detecting this type of investor behavior, and measured using the Patterson and Sharma (Working Paper, University of Michigan–Dearborn, 2006) herding intensity measure. Different volatility measures (historical, realized and implied) are employed. The results confirm that herding has a direct linear impact on volatility for all of the volatility measures considered, although the corresponding intensity is not always the same. In fact, herding variables seem to be useful in volatility forecasting and therefore in decision making when volatility is considered a key factor.
000129591 536__ $$9info:eu-repo/grantAgreement/ES/MEC/ECO2009-12819-C03-01$$9info:eu-repo/grantAgreement/ES/MEC/ECO2009-12819-C03-02$$9info:eu-repo/grantAgreement/ES/MEC/SEJ2006-14809-C03-01$$9info:eu-repo/grantAgreement/ES/MEC/SEJ2006-14809-C03-03/ECON
000129591 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000129591 590__ $$a0.824$$b2012
000129591 591__ $$aECONOMICS$$b162 / 333 = 0.486$$c2012$$dQ2$$eT2
000129591 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b58 / 93 = 0.624$$c2012$$dQ3$$eT2
000129591 591__ $$aBUSINESS, FINANCE$$b49 / 88 = 0.557$$c2012$$dQ3$$eT2
000129591 591__ $$aSOCIAL SCIENCES, MATHEMATICAL METHODS$$b28 / 45 = 0.622$$c2012$$dQ3$$eT2
000129591 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000129591 700__ $$aCorredor, Pilar
000129591 700__ $$0(orcid)0000-0001-8760-9350$$aFerreruela, Sandra$$uUniversidad de Zaragoza
000129591 7102_ $$14002$$2230$$aUniversidad de Zaragoza$$bDpto. Contabilidad y Finanzas$$cÁrea Economía Finan. y Contab.
000129591 773__ $$g12, 2 (2012), 311-327$$pQuant. financ.$$tQuantitative Finance$$x1469-7688
000129591 8564_ $$s240398$$uhttps://zaguan.unizar.es/record/129591/files/texto_completo.pdf$$yPostprint
000129591 8564_ $$s1192441$$uhttps://zaguan.unizar.es/record/129591/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000129591 909CO $$ooai:zaguan.unizar.es:129591$$particulos$$pdriver
000129591 951__ $$a2024-01-04-09:03:15
000129591 980__ $$aARTICLE