AN APPLICATION TO FORECAST VOLATILITY IN THE LIMA STOCK MARKET

A method is proposed to analyze data generated by a family of stochastic processes called autoregressive conditional heteroscedastic processes (ARCH), which are widely used to predict volatility of financial time series. An ARCE model is used to predict the volatility of the Atacocha mining company...

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Bibliographic Details
Published inPesquimat Vol. 7; no. 1
Main Authors Adolfo Elescano Rojas, Ysela Dominga Agüero Palacios
Format Journal Article
LanguageSpanish
Published Universidad Nacional Mayor de San Marcos 01.09.2014
Subjects
heterocedasticidad condicional
Modelos ARCH
retornos financieros
riesgo
series financieras
volatilidad
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Summary:A method is proposed to analyze data generated by a family of stochastic processes called autoregressive conditional heteroscedastic processes (ARCH), which are widely used to predict volatility of financial time series. An ARCE model is used to predict the volatility of the Atacocha mining company stock price based on the data from 1992 to 2003.
ISSN:1560-912X
1609-8439
DOI:10.15381/pes.v7i1.9318