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All Journal Jurnal Varian Pattimura International Journal of Mathematics (PIJMath)
Wisnowan Hendy Saputra
Institut Teknologi Sepuluh Nopember
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

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Expansion of Stock Portfolio Risk Analysis Using Hybrid Monte Carlo-Expected Tail Loss Wisnowan Hendy Saputra; Ika Safitri
Jurnal Varian Vol 5 No 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i2.1813

Abstract

Monte Carlo-Expected Tail Loss (MC-ETL) is the new expansion method that combines simulation and calculation to measure investment risk. This study models US stock prices using ARIMA-GARCH and forms an optimized portfolio based on Multi-Objective that aims to analyze the portfolio investment return. The next portfolio return will be simulated using the Monte Carlo (MC) method, measured based on the Expected Tail Loss (ETL) calculation. The optimized portfolio comprises 5 US stocks from 10 years of data, with the biggest capitalization market on February 25, 2021. MSFT has the most considerable weight in the optimized portfolio, followed by GOOG, AAPL, and AMZN, whereas TSLA shares have negligible weight. Based on the simulation result, the optimized portfolio has the smallest ETL value compared to its constituent stocks, which is ±0.029 or about 2.9%. This value means that the optimized portfolio is concluded as an investment choice for investors with a low level of risk.
Monte Carlo-Expected Tail Loss for Analyzing Risk of Commodity Futures Based on Holt-Winters Model Wisnowan Hendy Saputra
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp7-16

Abstract

Future, an agreement to buy or sell an asset at a certain price and a certain time in the future, is one of the market derivatives because the underlying assets influence the price of futures. In general, futures divide into financial futures and commodity futures. Each of the futures has different risks, so risk measures are needed to improve the effectiveness and efficiency of investment management. For example, we have the London Metal Exchange (LME) in the metal scope of commodity futures. Therefore, we propose the Holt-Winters Model for estimating commodity prices in this study. Hereafter, The Expected Tail Loss (ETL) with Monte Carlo process will use to analyze risk measures. We took six commodity futures in LME to implement the method as a sample, such as Zinc, Lead, Aluminum, Copper, Nickel, and Tin. Based on the analysis, each commodity has a different mean ETL value, where Nickel has the most significant risk with an ETL value of 0.036. This value means that the possibility of the expected loss to be borne by investors is 3.6%.
Co-Authors Ika Safitri