2020•Indonesian Capital Market ReviewOpen access

Volatility Forecasts Jakarta Composite Index (JCI) and Index Stock Volatility Sector with Estimated Time Series

Muhammad Rifki Bahtiar

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Abstract

This study aims to explore the comparative ability of forecasting models and the time series volatility of capital markets in Indonesia using JCI daily index data and sectoral indices from January 2010 to December 2014. The use of ARCH-family ARCH model (1.1) and GARCH (1.1) used to capture symmetrical effects, while TGARCH (1.1), EGARCH (1.1), APGARCH (1.1) on asymmetric effects. The results show that JCI return has an asymmetrical effect and the closest forecasting model is EGARCH (1.1). Returns for AGRI, MINING, BASICIND, INFRA, FIN, TRADE indices also have asymmetrical effects but are modeled with TGARCH (1.1). Meanwhile, the MISCIND, CONSUMER, PROPERTY indexes have a symmetrical effect and are modeled with GARCH (1.1). These models can explain forecasting closest to the real as well as provide guidance investors in the Indonesia capital market as one of the emerging markets

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What this paper is about

This study aims to explore the comparative ability of forecasting models and the time series volatility of capital markets in Indonesia using JCI daily index data and sectoral indices from January 2010 to December 2014. The use of ARCH-family ARCH model (1.1) and GARCH (1.1) used to capture symmetrical effects, while TGARCH (1.1), EGARCH (1.1), APGARCH (1.1) on asymmetric effects. The results show that JCI return has an asymmetrical effect and the closest forecasting model is EGARCH (1.1). Returns for AGRI, MINING, BASICIND, INFRA, FIN, TRADE indices also have asymmetrical effects but are modeled with TGARCH (1.1). Meanwhile, the MISCIND, CONSUMER, PROPERTY indexes have a symmetrical effect and are modeled with GARCH (1.1). These models can explain forecasting closest to the real as well as provide guidance investors in the Indonesia capital market as one of the emerging markets

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Available abstract

This study aims to explore the comparative ability of forecasting models and the time series volatility of capital markets in Indonesia using JCI daily index data and sectoral indices from January 2010 to December 2014. The use of ARCH-family ARCH model (1.1) and GARCH (1.1) used to capture symmetrical effects, while TGARCH (1.1), EGARCH (1.1), APGARCH (1.1) on asymmetric effects. The results show that JCI return has an asymmetrical effect and the closest forecasting model is EGARCH (1.1). Returns for AGRI, MINING, BASICIND, INFRA, FIN, TRADE indices also have asymmetrical effects but are modeled with TGARCH (1.1). Meanwhile, the MISCIND, CONSUMER, PROPERTY indexes have a symmetrical effect and are modeled with GARCH (1.1). These models can explain forecasting closest to the real as well as provide guidance investors in the Indonesia capital market as one of the emerging markets

Key concepts: Composite index, Volatility (finance), Economics, Financial economics, Econometrics, Index (typography), Stock market index, Volatility risk premium

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