Peramalan Harga Saham Perusahaan Selular Di Indonesia Menggunakan Metode Vector Autoregressive (VAR)

Tianto, Reza (2014) Peramalan Harga Saham Perusahaan Selular Di Indonesia Menggunakan Metode Vector Autoregressive (VAR). Other thesis, Insititut Teknologi Sepuluh Nopember.

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Abstract

Peramalan harga saham perusahaan selular di Indonesia dengan metode Multivariate Time series sangat berguna dalam dunia investasi keuangan. Dalam penelitian ini metode dalam melakukan peramalan harga data saham perusahan menggunakan Vector Autoregressive (VAR). Variabel data saham pada penelitian ini adalah harga saham milik PT Telkom IndonesiaTbk. (TLKM), PT XL Axiata Tbk. (EXCL), PT Indosat Tbk. dan PT Smart Telecom Tbk. (FREN). Dengan metode multivariate time series tidak hanya dapat meramalkan harga saham perusahaan selular, tapi juga bisa menjelaskan hubungan antar saham perusahaan selular.Berdasarkan hasil pengamatan EXCL dan FREN dapat mempengaruhi ISAT tetapi harga saham EXCL dan TLKM tidak dapat dipengaruhi oleh harga saham manapun.
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Forecasting cellular company’s stock price in Indonesia with Multivariate Time series methods are useful in the world of financial investments. In this study the method to forecast the price of the company share data using a Vector Autoregressive (VAR). Share data variables in this study is the stock price of PT Telkom Indonesia Tbk. (TLKM), PT XL Axiata Tbk. (EXCL), PT Indosat Tbk. and PT Smart Telecom Tbk. (FREN). With the method of multivariate time series not only can predict the cellular company's stock price, but also could explain the relationship between the company's stock selular. Under the observations, EXCL and FREN can affect any stock prices except TLKM. EXCL can not be influenced by the price of any stock.

Item Type:	Thesis (Other)
Additional Information:	RSSt 519.55 Tia p-2014
Uncontrolled Keywords:	Investasi, Harga SahamTime Series,Time Series, VAR, Stock Price
Subjects:	H Social Sciences > HG Finance > HG4910 Investments
Divisions:	Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	28 Dec 2023 04:20
Last Modified:	28 Dec 2023 04:20
URI:	http://repository.its.ac.id/id/eprint/105323

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