<![CDATA[ABSTRACTThe purpose of this study is to analyze volatility, choose the most optimal model andforecast of stock data on companies in various industrial sectors with the automotiveindustry and components sub-sector listed on the Stock Exchange during the period2011-2015. The return of stock data in the automotive sub-sector is modeled by theGARCH model. To see the effect of leverage, the data is re-modeled with the EGARCHand GJR models. Based on the information and probability criteria, it appears that themore optimal models are the GARCH model for AUTO, and GJR for ASII and GJTL.After the leverage effect is seen in the GJR model, then forecasting is done. Forecastingresults are in accordance with their respective optimal models in a 5% confidenceinterval, so it is expected that this model can forecast the price of future stock data.Keywords : Volatiliy, Forecast, GARCH, EGARCH, GJR ABSTRAKTujuan penelitian ini adalah menganalisis volatilitas, memilih model yang palingoptimal dan melakukan forecast data saham pada perusahaan dalam sektor anekaindustri dengan sub sektor industri otomotif dan komponen yang listing di BEI selamaperiode 2011-2015. Data return saham sub sektor otomotif dimodelkan dengan modelGARCH. Untuk melihat adanya leverage effect, data dimodelkan kembali dengan modelEGARCH dan GJR. Berdasarkan information criteria dan likelihood, terlihat bahwamodel yang lebih optimal adalah model GARCH untuk AUTO, dan GJR untuk ASIIdan GJTL. Setelah leverage effect terlihat pada model GJR, kemudian dilakukanforecasting. Hasil forecasting sesuai dengan model optimalnya masing-masing beradadalam confidence interval 5%, sehingga diharapkan model tersebut dapatmenggambarkan harga data saham di masa yang akan datang.Kata Kunci : Volatilitas, Forecast, GARCH, EGARCH, GJR]]>
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