ARCH Model in Analysis Patterns of Rupiah Exchange Rates against US Dollar

Iman Firmansyah^1, and Edi Gunadi¹

¹Department of Industrial Engineering, Universitas Pasundan, Bandung, Indonesia

Cite this paper:
Iman Firmansyah and Edi Gunadi. ARCH Model in Analysis Patterns of Rupiah Exchange Rates against US Dollar. Journal of Finance and Economics. 2020; 8(2):61-68. doi: 10.12691/jfe-8-2-3

Abstract

The Indonesian government uses the exchange rate of US dollar (USD) as an indicator in the preparation of the Draft of State Revenue and Expenditure Budget (RAPBN). The reason is that the daily exchange rate of the US dollar is a time series data with significant autocorrelation. Although the variance is relatively small, it cannot be considered constant. So, that the functional relationship model of the variants needs to be examined in addition to the functional relationship model of the exchange value. The study of the functional relationship model of observational values and their variants can simultaneously be analyzed by ARCH model based on daily data between 1 July 2015 - 31 July 2019.

Keywords:
ARCH model constant variant foreign exchange rate Rupiah US dollar

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References:

[1]	Abdullah, S.M., Siddiqua, Salina., Siddiquee, Muhammad. Shahadat Hossain., Hossain, Nazmul. 2017. Modeling and forecasting exchange rate volatility in Bangladesh using GARCH models: a comparison on normal and Student’s t-error distribution. Financial Innovation, 3 (18). 1-19.
[2]	Asmara, C.G. 2019. PDB Tumbuh 5,3% & Dolar di Rp 14.400, Ini Asumsi Makro 2020. Retrieved from https://www.cnbcindonesia.com/news/20190816140954-4- 92531/pdb-tumbuh-53-dolar-di-rp-14400-ini-asumsi-makro-2020.
[3]	Sunarti; Mariani, Scolastika; Sugiman. 2016. Perbandingan Akurasi Model ARCH dan GARCH pada Peramalan Harga Saham Berbantuan Matlab.UNNES Journal of Mathematics, 5 (1).
[4]	Ramzan, Shahla.,Ramzan, Shumila., 2012. Zahid, Faisal., Maqbool. Modeling and Forecasting Exchange Rate Dynamics in Pakistan Using ARCH Family of Models. Electronic Journal of Applied Statistical Analysis, 5 (1). 15-29.
[5]	Ganbold, Batzorig., Akran, Iqra., & Lubis, Fahrozi.2012. Exchange Rate Volatility: A Forecasting Approach of Using the ARCH Family along with ARIMA SARIMA and Semi-Structural-SVAR in Turkey. Retrieved from https://mpra.ub.uni-muenchen.de/8447/MPRA Paper No.84447, posted 10 Feb 2018.
[6]	Dritsaki, Chaido.2019.Modeling the Volatility of Exchange Rate Currency Using GARCH Model, Economia Internazionale, 72 (2). 209-230.
[7]	Forsberg, L., & Bollerslev, T. 2002.Bridging the Gap Between the Distribution of Realized (ECU) Volatility and Arch Modelling (of the Euro): The Garch-NIG Model. Journal of Applied Econometrics, 17. 535-548.
[8]	Kais, Ben.,Mbarek. 2015. Stock Returns and Forecast: Case of Tunisia with ARCH Model. Journal of Finance and Economics, 3 (3). 55-60.
[9]	Bollerslev, Tim. 2008. Glossary to ARCH (GARCH). School of Economics and Management, University of Aarhus, Denmark.
[10]	Engle, R. (2002).New Frontiers for ARCH Model. Journal of Applied Econometrics, 17. 425-446.
[11]	Alberola, Ricardo. 2007. Estimating Volatility Returns Using ARCH Models. An Empirical Case: The Spanish Energy Market. Lecturas de Economía, 66 (enero-junio). 251-276.
[12]	Perelli, R., (2001). Introduction to ARCH & GARCH Models. Handout. Illionis: Department of Economics, University of Illionis.
[13]	Degiannakis. Stravos and Xekalaki, Evdoki. 2004. Autoregresive Conditional Heteroskedasticity (ARCH) Models: A Review. Munich Personal ReFec archive. Retrieved from https://mpra.ub.uni-munchen.de/80487/.
[14]	Brooks, R.D., Faff, R.W., McKenzie, M.D., Mitchell, H. no date. ARCH Models and National Stock Market Returns. Department of Economics and Finance, Royal Melbourne Institute of Technology, Australia.
[15]	Dury, M.E., & Xiao, B. 2018. Forecasting the Volatility of the Chinese Gold Market by ARCH Family Models and Extension to Stable Models. Retrieved from https://hal/archives-ouvertes.fr/hal-01709321.
[16]	Engle, R. F.1982. Autoregressive Conditional Heteroscedasticity with Estimates of The Varians of United Kingdom Inflation. Econometrica, 50 (4).
[17]	Najjar, Dana., AL. 2016. Modelling and Estimation of Volatility Using ARCH/GARCH Models in Jordan’s Stock Market.Asian Journal of Finance & Accounting, 8 (1).152-167.
[18]	Hatane, Saarce., Elsye. 2011. The Predictability of GARCH-Type Models on the Returns Volatility of Primary Indonesian Exported Agricultural Commodities. Jurnal Akuntansi dan Keuangan, 13 (2). 87-97.
[19]	Ciucu, Stefan., Cristian. 2016. Modelling Exchange Rates Using ARCH Family of Models. Challenges of the Knowledge Society.IT in Social Sciences.pp. 982-989.
[20]	Wibowo, T., and Amir, H. 2005. Faktor-Faktor Yang Mempengaruhi Nilai Tukar Rupiah. Journal of Economy and Finance, Fiscal Policy Agency RI, 9 (4).17-41.
[21]	Kandora, Abbas Hasbalrasol Abas & Hamdi, Ahmed Mohammed Abdullah., 2016. Modelling and Forecasting Exchange-rate Volatility with ARCH-type models. IOSR Journal of Mathematics, 12 (2). 29-37.
[22]	Lumsdaine, R., L., and Serena, Ng. (1999). Testing for ARCH in The Presence of A Possibly Misspecified Conditional Mean. Journal of Econometrics, 93. 257-279.