RISK MEASURE FOR STOCHASTIC AGGREGATION
Determining risk measure for aggregation may not be separated from the components of aggregation. Components of aggregation is a time series data that may be modeled by using GARCH (1,1). Depedence between the component of aggregation will be an interesting topic to discuss. Joint distribution funct...
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id-itb.:228932017-09-27T11:43:14ZRISK MEASURE FOR STOCHASTIC AGGREGATION JUNIARTY (10112005), LIANA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/22893 Determining risk measure for aggregation may not be separated from the components of aggregation. Components of aggregation is a time series data that may be modeled by using GARCH (1,1). Depedence between the component of aggregation will be an interesting topic to discuss. Joint distribution function in which dependence of each aggregation component are conceived is going to be constructed using Copula. Copula is one method to construct joint distribution function where each of the components has dependence. In addition, the use of copula may detect and model the depedence of the aggregation component in a better way. Value-at-risk and Expected Shortfall may predict the aggregation risk measure with interval prediction concept. Therefore, Value-at-Risk as an interval prediction should have an upper bound and lower bound for the prediction of risk for aggregation text |
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Institut Teknologi Bandung |
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Institut Teknologi Bandung Library |
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Indonesia Indonesia |
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Institut Teknologi Bandung |
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Indonesia |
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Determining risk measure for aggregation may not be separated from the components of aggregation. Components of aggregation is a time series data that may be modeled by using GARCH (1,1). Depedence between the component of aggregation will be an interesting topic to discuss. Joint distribution function in which dependence of each aggregation component are conceived is going to be constructed using Copula. Copula is one method to construct joint distribution function where each of the components has dependence. In addition, the use of copula may detect and model the depedence of the aggregation component in a better way. Value-at-risk and Expected Shortfall may predict the aggregation risk measure with interval prediction concept. Therefore, Value-at-Risk as an interval prediction should have an upper bound and lower bound for the prediction of risk for aggregation |
| format |
Final Project |
| author |
JUNIARTY (10112005), LIANA |
| spellingShingle |
JUNIARTY (10112005), LIANA RISK MEASURE FOR STOCHASTIC AGGREGATION |
| author_facet |
JUNIARTY (10112005), LIANA |
| author_sort |
JUNIARTY (10112005), LIANA |
| title |
RISK MEASURE FOR STOCHASTIC AGGREGATION |
| title_short |
RISK MEASURE FOR STOCHASTIC AGGREGATION |
| title_full |
RISK MEASURE FOR STOCHASTIC AGGREGATION |
| title_fullStr |
RISK MEASURE FOR STOCHASTIC AGGREGATION |
| title_full_unstemmed |
RISK MEASURE FOR STOCHASTIC AGGREGATION |
| title_sort |
risk measure for stochastic aggregation |
| url |
https://digilib.itb.ac.id/gdl/view/22893 |
| _version_ |
1821120911122628608 |