AN APPLICATION TO FORECAST VOLATILITY IN THE LIMA STOCK MARKET
DOI:
https://doi.org/10.15381/pes.v7i1.9318Keywords:
ARCH models, financial time series, volatility, conditional heteroscedasticity, financial returns, riskAbstract
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.
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Copyright (c) 2004 Adolfo Elescano Rojas, Ysela Dominga Agüero Palacios
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