DOI: https://doi.org/10.14710/medstat.13.1.1-12

COMPARISON OF ARIMA, TRANSFER FUNCTION AND VAR MODELS FOR FORECASTING CPI, STOCK PRICES, AND INDONESIAN EXCHANGE RATE: ACCURACY VS. EXPLAINABILITY

*Taly Purwa orcid scopus  -  Badan Pusat Statistik (BPS) Provinsi Bali, Indonesia
Ulin Nafngiyana  -  Badan Pusat Statistik (BPS) Kabupaten Trenggalek, Indonesia
Suhartono Suhartono orcid scopus  -  Department of Statistics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember (ITS), Indonesia
Open Access Copyright (c) 2020 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
The Consumer Price Index (CPI), stock prices and the rupiah exchange rate to the US dollar are important macroeconomic variables which their movements show the economic performance and can affect the monetary and fiscal policies of Indonesia. This makes forecasting effort of these variables become important for policy planning. While many previous studies only focus on examining the effect among macroeconomic variables, this study uses ARIMA (univariate method), transfer function and VAR (multivariate methods) to measure the forecasting accuracy and also observing the effect between these macroeconomic variables. The results showed that the multivariate methods gave better explanation about the relationship between variables than the simple one. Otherwise, the results of accuracy comparison showed that the multivariate methods did not always yield better forecast than the simple one, and these conditions in line with the results and conclusions of M3 and M4 competition.

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Keywords: CPI; Stock Price; Exchange Rate; ARIMA; Transfer Function; VAR

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