Monte Carlo-Expected Tail Loss for Analyzing Risk of Commodity Futures Based on Holt-Winters Model

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%.

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Publication Details

Journal
Pattimura International Journal of Mathematics (PIJMath)
Published
2025-05-01
DOI
https://doi.org/10.30598/pijmathvol4iss1pp7-16
Citations
2
Primary Topic
Stock Market Forecasting Methods
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article
Field-Weighted Citation Impact
4.21
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article

Monte Carlo-Expected Tail Loss for Analyzing Risk of Commodity Futures Based on Holt-Winters Model

Wisnowan Hendy Saputra
2 citations
Pattimura International Journal of Mathematics (PIJMath)
Stock Market Forecasting Methods
4.21
article

Monte Carlo-Expected Tail Loss for Analyzing Risk of Commodity Futures Based on Holt-Winters Model

Wisnowan Hendy Saputra
article en
2 citations

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%.

Pattimura International Journal of Mathematics (PIJMath)Vol. 4(1)
Sepuluh Nopember Institute of Technology (ID)
Openalex Percentile: Top 7%
Stock Market Forecasting Methods
4.21
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