Estimation of the Value-at-Risk (VaR) Using the TARCH Model by Considering the Effects of Long Memory in Stock Investments

https://doi.org/10.47194/orics.v1i1.22

Authors

Keywords:

Long memory, VaR, TARCH models.

Abstract

Value at Risk (VaR) is one of the standard methods that can be used in measuring risk in stock investments. VaR is defined as the maximum possible loss for a particular position or portfolio in the known confidence level of a specific time horizon. The main topic discussed in this thesis is to estimate VaR using the TARCH (Threshold Autoregressive Conditional Heteroscedasticity) model in a time series by considering the effect of long memory. The TARCH model is applied to the daily log return data of a company's stock in Indonesia to estimate the amount of quantile that will be used in calculating VaR. Based on the analysis, it was found that with a significance level of 95% and assuming an investment of 200,000,000 IDR, the VaR using the TARCH model approach was 5,110,200 IDR per day.

References

Batuparan, S. D.(2001). Kerangka Kerja Risk Management. (www.bexi.co.id/images/_res/perbankan-Kerangka Kerja Risk Management.pdf, accessed on 2 Maret 2008).

Beronilla, L., Nikkin,& Mapa, S. D. (2007). Range-Based GARCH: A New Method of Estimating Value-at-Risk. (www.nscb.gov.ph/ncs/10thNCS/abstracts/Contributed/36_Forecasting/abstract_mapa.pdf, accessed on 2 Maret 2008).

Cryer, J. D. (1986). Time Series Analysis. Boston: PWS-KENT Publishing Company.

Dowd, K. 2002. An Introduction to Market Risk Measurement. Chichester, New York: John Wiley & Sons.

Herrhyanto, N. (2003). Statistika Matematis Lanjutan. Bandung: Pustaka Setia.

Jogiyanto. 2007. Teori Portofolio dan Analisis Investasi. Yogyakarta: BPFE.

Klienbaum, D. G., Kuper, L.L.and Muller, K.E. 1988. Applied Regresssion and Other Multivariabel Methods, Second Edition. Boston: PWS-KENT Publising Company.

Mood, A.M., Graybill, F.A. and Boes, D. C. 1963. Introduction to the Theory of Statistics, Third Edition. New York: McGraw Hill Book Company.

Ruppert, D. 2004. Statistics and Finance an Introduction. New York: Springer.

Redhead, K. 1997. Financial Derivatives: An Introduction to Future, Forwards, Options and Swaps. Prentice Hall Europe.

Sukono, Subartini, B., Napitupulu, H., Hidayat, Y., Putra, A.S., and Bon, A.T. 2019. Value-at-Risk and Modified Value-at-Risk under Asset Liability by Using Time Series Approach. Proceedings of the International Conference on Industrial Engineering and Operations Management, Bangkok, Thailand, March 5-7, 2019, 2106-2117.

Published

2020-02-05

How to Cite

Abdul Halim, N., Supriatna, A., & Prasetyo, A. (2020). Estimation of the Value-at-Risk (VaR) Using the TARCH Model by Considering the Effects of Long Memory in Stock Investments. Operations Research: International Conference Series, 1(1), 34–43. https://doi.org/10.47194/orics.v1i1.22

Issue

Vol. 1 No. 1 (2020): Operations Research International Conference Series (ORICS), March 2020

Section

Articles
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