Value at Risk Analysis for Investment Decisions Using Historical Simulation

  • Ridwan Maronrong
  • Pristina Hermastuti
  • Saifi Maulana Iksan Abdul Ajis Muntahak
Keywords: CAPM, Construction Sector Index, Historical Simulation, Property and Real Estate, Value at Risk

Abstract

This study aims to determine the value at risk for investment decisions in empirical research on the Building Construction Sector, which is included in the LQ45 index listed on the IDX for the 2016-2020 period. This study uses a descriptive quantitative research approach, and the data used are secondary data, with data sources coming from www.idx.co.id and www.finance.yahoo.com. This study used a purposive sampling technique. The analytical method used in this research is the Value at Risk Historical Simulation approach at a 99% alpha level using stock prices and the prices of the Construction, Property, and Real Estate Sector Index for the 2016-2020 period. The portfolio measurement method uses the Capital Asset Pricing Model (CAPM) model of 3 issuers listed in the LQ45 index: In this study, the proportion of the same investment in each stock is 33.33%. This study uses a regression test to determine the relationship between sector stock returns and the returns index tool used to measure investment risk with the help of software Microsoft Excel 2019. The results of the VaR calculation show that the most negligible risk of the three stocks during the 2016-2020 period is WSKT shares, and the most prominent risk is PTPP shares, with VaR values of 34.71% and 36.72%, respectively. Investors with a risk-averse preference can invest their funds in WSKT shares, and investors with a risk taker can invest their funds in PTPP shares. The highest 5-year portfolio VaR results were PTPP shares of Rp 12,239,066, and the lowest was WSKT shares of Rp 11,571,282. The results Significance F of three stocks for five years indicate a significant influence between sector stock returns and returns index.

References

Abrami, Rizkar, and Bambang Santoso Marsoem, Optimal Portfolio Formation with Single Index Model Approach on Lq-45 Stocks on Indonesia Stock Exchange, International Journal of Innovative Science and Research Technology, 2021, VI. www.ijisrt.com.
Amin, Farah Azaliney Mohd, Nurulhazwan Izumi Othman, Mohamad Khairil Amri Khairuddin, and Muhammad Haikal Muhaimin Hazahar, 'Measuring Value at Risk for Kijang Emas Investment Using Historical Simulation Approach, International Journal of Academic Research in Business and Social Sciences, 9.9 (2019). https://doi.org/10.6007/ijarbss/v9-i9/7003.
Amin, Farah Azaliney Mohd, Siti Fatimah Yahya, Siti Ainazatul Shazlin Ibrahim, and Mohammad Shafiq Mohammad Kamari, 'Portfolio Risk Measurement Based on Value at Risk (VaR),' in AIP Conference Proceedings (American Institute of Physics Inc., 2018), MCMLXXIV. https://doi.org/10.1063/1.5041543.
Astuti, Putri Endah, and Tri Gunarsih, ‘Value at Risk Analysis in Risk Measurement and Optimum Portofolio Formation in Banking Shares JBTI : Jurnal Bisnis : Teori Dan Implementasi, 12.2 (2021), 103–14. https://doi.org/10.18196/jbti.v12i2.12263.
Bodie, Z., Kane A., & Marcus, A. J. (2014). Dasar-Dasar Investasi (9th ed.). Jakarta : Salemba Empat.
Djohanputro (2012). Manajemen Risiko Korporat Terintegrasi (11st ed). Jakarta: PPM.
Günay, Samet, 'Value at Risk (VaR) Analysis for Fat Tails and Long Memory in Returns,' Eurasian Economic Review, 7.2 (2017), 215–30. https://doi.org/10.1007/s40822-017-0067-z.
Iasha, Dian, Ahmad Faisol, and Universitas Lampung, Capital Asset Pricing Model sebagai Penentu Portofolio Optimal pada Indeks Saham LQ-45 (Lampung, 2020).
Intan Sari, Widya, ‘Analisis Pengaruh Inflasi, Suku Bunga SBI, Nilai Tukar Terhadap Return LQ 45 Dan Dampaknya Terhadap Indeks Harga Saham Gabungan (IHSG) Di Bursa Efek Indonesia (BEI) ARTICLES INFORMATION ABSTRACT’, Jurnal Sekuritas, 3.1 (2019).
Mostafa, Fahed, Tharam Dillon, and Elizabeth Chang, Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk, by Poland Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, 2017th edn (Australia: Springer Nature, 2017), DCXCVII. https://doi.org/DOI 10.1007/978-3-319-51668-4.
Naufal, Muhamad, Nur Ridha, and Moh Khoiruddin, Management Analysis Journal Konsistensi pengukuran Value at Risk pada Saham Syariah dengan Metode Historis, Management Analysis Journal, 2018, VII. http://maj.unnes.ac.id.
Sultra, I Wayan Eka, Muhammad Rifai Katili, and Muhammad Rezky Friesta Payu, ‘Metode Simulasi Historis untuk Perhitungan Nilai Value at Risk pada Portofolio dengan Model Markowitz’, Euler : Jurnal Ilmiah Matematika, Sains Dan Teknologi, 9.2 (2021), 94–102. https://doi.org/10.34312/euler.v9i2.11518.
Salsabila, A, and S Hasnawati, 'Value At Risk and Expected Returns of Portfolio (Companies Listed on LQ45 Index Period 2013–2016)', KnE Social Sciences, 3.10 (2018). https://doi.org/10.18502/kss.v3i10.3407.
Sarpong, Peter Kwasi, Jones Osei, and Samuel Amoako, Historical Simulation (HS) Method on Value-at-Risk & Its Approaches, Dama International Journal of Researchers (Ghana: www.damaacademia.com Historical, 2018), III. www.damaacademia.com.
Susanti, Dwi, Sukono Sukono, and Maria Jatu Verrany, 'Value-at-Risk Estimation Method Based on Normal Distribution, Logistics Distribution and Historical Simulation', Operations Research: International Conference Series, 1.1 (2020), 13–18. https://doi.org/10.47194/orics.v1i1.19.
Sugiyono. (2018). Metode Penelitian Kuantitatif. Bandung: Alfabeta.
Published
2023-04-15
How to Cite
Maronrong, R., Hermastuti, P., & Abdul Ajis Muntahak, S. M. I. (2023). Value at Risk Analysis for Investment Decisions Using Historical Simulation. Selangor Science & Technology Review (SeSTeR), 7(1), 12-21. Retrieved from https://sester.journals.unisel.edu.my/ojs/index.php/sester/article/view/315