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In finance, stock investment could be one of the interested alternatives that can be selected by the investor. Stock prices are highly volatile, it would gives advantages or disadvantages. It would be very profitable if an investor can estimate the value of stock returns for the...
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| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/20237 |
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| Institution: | Institut Teknologi Bandung |
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id-itb.:202372017-09-27T11:43:13Z#TITLE_ALTERNATIVE# ARIFIANI (NIM : 10111081), KARINA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/20237 In finance, stock investment could be one of the interested alternatives that can be selected by the investor. Stock prices are highly volatile, it would gives advantages or disadvantages. It would be very profitable if an investor can estimate the value of stock returns for the next few days. This final project will analyze the investment that contains a pair of different stocks, then analyze the dependency between joint stocks return and predict returns for the next few days. Stock returns are modeled by using time series analysis, both stationare and non-stationare, then using epsilon as a random variable. Bivariate Gaussian Copula is used to construct a joint distribution function of a joint stocks epsilon and analyze their dependency. Then, validation will be done to ensure whether model fitted in with real data or not using a fitting test. Data needed in the analysis process is the closing price that will be processed according to the model. text |
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Institut Teknologi Bandung |
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Indonesia Indonesia |
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Institut Teknologi Bandung |
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Indonesia |
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In finance, stock investment could be one of the interested alternatives that can be selected by the investor. Stock prices are highly volatile, it would gives advantages or disadvantages. It would be very profitable if an investor can estimate the value of stock returns for the next few days. This final project will analyze the investment that contains a pair of different stocks, then analyze the dependency between joint stocks return and predict returns for the next few days. Stock returns are modeled by using time series analysis, both stationare and non-stationare, then using epsilon as a random variable. Bivariate Gaussian Copula is used to construct a joint distribution function of a joint stocks epsilon and analyze their dependency. Then, validation will be done to ensure whether model fitted in with real data or not using a fitting test. Data needed in the analysis process is the closing price that will be processed according to the model. |
| format |
Final Project |
| author |
ARIFIANI (NIM : 10111081), KARINA |
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ARIFIANI (NIM : 10111081), KARINA #TITLE_ALTERNATIVE# |
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ARIFIANI (NIM : 10111081), KARINA |
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ARIFIANI (NIM : 10111081), KARINA |
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#TITLE_ALTERNATIVE# |
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| url |
https://digilib.itb.ac.id/gdl/view/20237 |
| _version_ |
1822019158889463808 |