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<http://digilib.unila.ac.id/id/eprint/54526> <http://purl.org/dc/terms/title> "PERAMALAN VOLATILITAS DATA RETURN KURS RUPIAH\r\nTERHADAP DOLLAR DENGAN METODE INTEGRATED\r\nGENERALIZED AUTOREGRESSIVE CONDITIONAL\r\nHETEROSCEDASTICITY (IGARCH)"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://digilib.unila.ac.id/id/eprint/54526> <http://purl.org/ontology/bibo/abstract> "The purpose of this study is to apply one of the ARCH / GARCH models, namely\r\nIntegrated Generalized Autoregressive Conditional Heteroscedasticity (IGARCH)\r\nin predicting volatility in returning data on the Rupiah Rate against the US Dollar\r\nfor the next five periods. In time series data, sometimes the behaviour of variance\r\nof the time series data are not constant or heteroschedasticity. One of the models\r\nto deal with this tipe of problem, we can use IGARCH model. IGARCH model\r\ncan be used to forecast volatility. Based on the results of the analysis obtained the\r\nbest model is MA ([24]) IGARCH (3.2) and with the results of the variance\r\nforecast obtained volatility for the next five periods which indicates that high\r\nvolatility cannot be used. However, the estimated level of use of the\r\nIGARCH(3,2) model is relatively low.\r\nKeywords: Heteroschedasticity, Volatility, IGARCH\r\n\r\n\r\nTujuan dari penelitian ini adalah mengaplikasikan salah satu model\r\nARCH/GARCH yaitu Integrated Generalized Autoregressive Conditional\r\nHeteroscedasticity (IGARCH) dalam meramalkan volatilitas pada data return\r\nKurs Rupiah terhadap US Dollar untuk lima periode ke depan. Didalam data time\r\nseries, terkadang didapat varians yang tidak konstan atau heteroschedasticity.\r\nSalah satu model untuk menyelesaikan kondisi ini adalah model IGARCH. Model\r\nIGARCH dapat digunakan untuk meramalkan volatilitas. Berdasarkan hasil\r\nanalisis diperoleh bahwa model terbaik adalah MA([24]) IGARCH(3,2) dan\r\ndengan mengakarkan hasil ramalan variansnya diperoleh volatilitas untuk lima\r\nperiode kedepan yang menunjukan bahwa tidak terjadi volatilitas tinggi. Akan\r\ntetapi tingkat peramalan menggunakan model IGARCH relatif rendah.\r\nKata Kunci : Heteroskedastisitas, Volatilitas, IGARCH"^^<http://www.w3.org/2001/XMLSchema#string> .
<http://digilib.unila.ac.id/id/eprint/54526> <http://purl.org/dc/terms/date> "2019-08-19" .
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