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All Journal ARBITRASE: JOURNAL OF ECONOMICS AND ACCOUNTING Journal of Trends Economics and Accounting Research
Beno Jange
STMIK Dharmapala Riau, Pekanbaru
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Prediksi Harga Saham Bank BCA Menggunakan Prophet Beno Jange
Journal of Trends Economics and Accounting Research Vol 2 No 1 (2021): September 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (432.549 KB)

Abstract

This study aims to test the Prediction of Bank BCA Stock Price using the Prophet. Prophet is a model for generating forecasts based on historical data. The data in this study is the stock price data of Bank BCA for 4 (four) years, namely from 01-01-2017 to 31-12-2020. The results of this study indicate a fairly good prediction accuracy with a MAPE of 5.37 percent with hyper parameter tunings; predictions are a little less good for several months in 2020 due to the effects of holidays caused by the Covid-19 pandemic and large-scale social restrictions (PSBB)
Prediksi Harga Saham Bank BCA Menggunakan XGBoost Beno Jange
ARBITRASE: Journal of Economics and Accounting Vol. 3 No. 2 (2022): November 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/arbitrase.v3i2.495

Abstract

This study aims to determine the prediction of Bank BCA's stock price using XGBoost. XGBoost is an open source implementation of Gradient Boosting for generating forecasts based on historical data that is fast and scalable. The data in this study is stock price data of Bank BCA for 4 (four) years, namely from 01-01-2017 to 31-12-2020. The technical indicators used in this study are the Simple Moving Average (SMA), Exponential Moving Average (EMA), Moving Average Convergence/Divergence (MACD) and Relative Strength Index (RSI). The results show that the Exponential Moving Average technical indicator greatly influences the prediction results. The results of this study also show a fairly good prediction accuracy with MAPE of 4.01 percent with hyper parameter settings; but the predictions are slightly less good in March 2020 due to the Covid-19 pandemic case.
Prediksi Volatilitas Indeks Harga Saham Gabungan Menggunakan GARCH Beno Jange
ARBITRASE: Journal of Economics and Accounting Vol. 4 No. 1 (2023): Juli 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/arbitrase.v4i1.1122

Abstract

This study aims to determine the Volatility Prediction of the Indonesia Composite Index using GARCH. GARCH is a model for generating forecasts based on historical data using a function of its own past lag plus past innovations. This study uses quantitative methods. The data in this study are JKSE data for 11 (eleven) years, from 01-01-2012 to 31-12-2022. The volatility prediction is carried out for a year, namely in 2022. The results of this study indicate that the prediction accuracy is quite good with a MAPE of 17.26 percent. It was also found that volatility was quite pronounced, which rose significantly in May 2022 due to the effect of the absence of restrictions on the Eid holiday and decreased significantly in July 2022 due to the government extending the implementation of restrictions on community activities (PPKM) throughout Indonesia and dropping even more sharply due to the government increasing prices of Pertalite in September 2022.
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