Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/64461
Title: Stock Price Modelling Using Generalized Wiener Process and ARIMA Model.
Pemodelan Harga Saham Menggunakan Generalisasi Proses Wiener dan Model ARIMA
Authors: Nugrahani, Endar Hasafah
Budiarti, Retno
Sari, Mutia Indah
Keywords: stock price
generalized Wiener process
ARIMA model
Issue Date: 2011
Abstract: The capital stock of a business entity represents the original capital paid or invested in the business by its founders. Since it is known that the stock price fluctuates in time, it is necessary to have a model to forecast the stock price in the future. In this study, stock price is assumed to follow a continous stochastic process. One of stochastic models that can be used to model the stock price is a model of generalized Wiener process. This model describes the time evolution of stock price as a stochastic variable with constant drift and variance rate. On the other hand, since stock prices data are time series data, so ARIMA model can also be used to model this phenomena and to predict the stock price in the future. Both models are estimated using a chosen set of data. The result is then used to forecast the stock price in the future time. It can be concluded that forecasting study using generalized Wiener process shows a slightly better result than the ARIMA model.
URI: http://repository.ipb.ac.id/handle/123456789/64461
Appears in Collections:UT - Mathematics

Files in This Item:
File SizeFormat 
G11mis1.pdf
  Restricted Access
1.51 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.