Application ofgarchmethodologyto the closing priceon thelimasto ck exchange
DOI:
https://doi.org/10.15381/idata.v15i2.6377Keywords:
Forecasting, time series heteroscedasticity, autoregressive models, GARCH methodology.Abstract
The article presents a methodology that uses the time series, for forecasting indices closing prices, which made the stock market centers. The behavior response to a current generated on the expectation value of change in the preceding moment, ie an expected value conditioned by the variance of previous period. The GARCH model is the key part of the investigation. It presents a clear and detailed each of the activities undertaken to quantify market risk. ARIMA methodology is applied to predict the yields of the series, which generally have a variance is not constant over time, ie the existence of heteroscedasticity present and should be used generalized autoregressive conditional heteroskedasticity, for the company under study.
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Copyright (c) 2012 Eduardo Raffo Lecca, Luis Raez Guevara, Carlos Quispe Atúncar
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