FORECAST STOCK PRICES USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (Case Study on Bluechip Stocks Listed in LQ 45 Index at Indonesian Stock Exchange, 2008-2012)

GETTA ADINDA KUSUMANINGTYAS

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61 kali
17.04.3893
C
Karya Ilmiah - Skripsi (S1) - Reference

Present price (Pt) is necessary to be forecasted in order to help investor and trader to take financial investment decision, to help accountant for the making of financial information and the presentation of financial ratios, and to help auditor in giving views of client’s business continuity and appraising client’s business. This study uses Autoregressive Integrated Moving Average (ARIMA) technical analysis method to forecast and analyze the present price, and is the type of descriptive predictive research, and is using secondary and quantitative data (daily closing-adjusted stock price during 2011 as its data), and pointing at bluechip stocks on 2012 that have been listed on LQ 45 index, Indonesia Stock Exchange since 2008-2012. ARIMA’s models for BMRI is ARIMA (25,1,25), for BBCA is ARIMA (3,1,8), for ASII is ARIMA (25,1,25), for INDF is ARIMA (22,1,22), for AALI is ARIMA (15,1,36), for PGAS is ARIMA (34,1,34), for ANTM is ARIMA (4,1,34) and for INCO is ARIMA (17,1,36). Its forecasting period is a month (January, 1st 2012 – January, 31st 2012) and resulting on 2.4696539% - 14.19859% values in error. Thus, ARIMA can be used as a good forecasting method. Keywords: Stocks, Technical Analysis, ARIMA, LQ 45, Forecast, Bluechip

Subjek

CAPITAL MARKETS
 

Katalog

FORECAST STOCK PRICES USING AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (Case Study on Bluechip Stocks Listed in LQ 45 Index at Indonesian Stock Exchange, 2008-2012)
 
 
Indonesia

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Pengarang

GETTA ADINDA KUSUMANINGTYAS
Perorangan
Brady Rikumahu
 

Penerbit

Universitas Telkom
Bandung
2017

Koleksi

Kompetensi

 

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