Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models

The existence of extreme volatility due to increased price changes causes gre- ater risks and uncertainties to be faced. To minimize risk, it is necessary to predict volatility and risk measures. The model that can be used to predict vo- latility is a combination of ARMA(1,1) and GARCH(1,1) model...

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Main Author:	Astri Retno Ismaeni, Nur
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/39118
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:39118
spelling	id-itb.:391182019-06-24T09:23:24ZEnergy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models Astri Retno Ismaeni, Nur Indonesia Theses energy, realized volatility historis volatility, Value-at-Risk, ARMA(1,1)- GARCH(1,1) model. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/39118 The existence of extreme volatility due to increased price changes causes gre- ater risks and uncertainties to be faced. To minimize risk, it is necessary to predict volatility and risk measures. The model that can be used to predict vo- latility is a combination of ARMA(1,1) and GARCH(1,1) models. ARMA(1,1)- GARCH(1,1) model is effective to be used in the mean of energy stock prices and asymmetric volatility that coincide with the leverage effect. While in the calculation of risk measures, the method used is Value-at-Risk (VAR). The results obtained in this thesis are that the ARMA(1,1)-GARCH(1,1) mo- del is good enough to be used in modeling volatility, where the ARMA(1,1) -GARCH(1,1) model can capture the empirical characteristics of volatility. Predictions with historical volatility are more accurate than realized volatility. Furthermore, in predicting the energy risk measure, the distribution that is suitable for use is students't distribution. text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
description	The existence of extreme volatility due to increased price changes causes gre- ater risks and uncertainties to be faced. To minimize risk, it is necessary to predict volatility and risk measures. The model that can be used to predict vo- latility is a combination of ARMA(1,1) and GARCH(1,1) models. ARMA(1,1)- GARCH(1,1) model is effective to be used in the mean of energy stock prices and asymmetric volatility that coincide with the leverage effect. While in the calculation of risk measures, the method used is Value-at-Risk (VAR). The results obtained in this thesis are that the ARMA(1,1)-GARCH(1,1) mo- del is good enough to be used in modeling volatility, where the ARMA(1,1) -GARCH(1,1) model can capture the empirical characteristics of volatility. Predictions with historical volatility are more accurate than realized volatility. Furthermore, in predicting the energy risk measure, the distribution that is suitable for use is students't distribution.
format	Theses
author	Astri Retno Ismaeni, Nur
spellingShingle	Astri Retno Ismaeni, Nur Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
author_facet	Astri Retno Ismaeni, Nur
author_sort	Astri Retno Ismaeni, Nur
title	Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
title_short	Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
title_full	Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
title_fullStr	Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
title_full_unstemmed	Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models
title_sort	energy risk measure prediction in arma(1,1)-garch(1,1) volatility models
url	https://digilib.itb.ac.id/gdl/view/39118
_version_	1822925202986631168

Energy Risk Measure Prediction in ARMA(1,1)-GARCH(1,1) Volatility Models

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