The Trinomial Tree Method in Pricing European Gold Option with Volatility Forecasting Using the GARCH (1,1) Model

<table width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>This study enhances the pricing accuracy of European gold options by integrating GARCH (1,1)-based volatility forecast into the trinomial tree method. GARCH (1,1) captures key characteristics of financial return series, such as heteroscedasticity and volatility clustering, while the trinomial tree offers greater flexibility than traditional models by allowing three price movements at each node. This integration provides a more realistic and robust framework for option pricing under dynamic market conditions. Using gold price data from October 2017 to October 2024, the model forecast annualized volatilities of 16.59%, 17.33%, and 17.66% for one, two, and three months. For call options, prices increase with longer maturities, ranging from Rp194,048 to Rp207,385. Conversely, put options become more valuable when the strike price exceeds the market prices, reaching up to Rp107,778. The proposed model offers practical value for more accurate pricing and investment strategies.</p></td></tr></tbody></table>

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Publication Details

Journal
ZERO Jurnal Sains Matematika dan Terapan
Published
2025-08-04
DOI
https://doi.org/10.30829/zero.v9i1.25455
Primary Topic
Market Dynamics and Volatility
Type
article
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article

The Trinomial Tree Method in Pricing European Gold Option with Volatility Forecasting Using the GARCH (1,1) Model

Rini Oktavia, Intan Syahrini, Difa Tazkya
1 links
ZERO Jurnal Sains Matematika dan Terapan
Market Dynamics and Volatility
article

The Trinomial Tree Method in Pricing European Gold Option with Volatility Forecasting Using the GARCH (1,1) Model

Rini Oktavia, Intan Syahrini, Difa Tazkya
article en

Abstract

<table width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>This study enhances the pricing accuracy of European gold options by integrating GARCH (1,1)-based volatility forecast into the trinomial tree method. GARCH (1,1) captures key characteristics of financial return series, such as heteroscedasticity and volatility clustering, while the trinomial tree offers greater flexibility than traditional models by allowing three price movements at each node. This integration provides a more realistic and robust framework for option pricing under dynamic market conditions. Using gold price data from October 2017 to October 2024, the model forecast annualized volatilities of 16.59%, 17.33%, and 17.66% for one, two, and three months. For call options, prices increase with longer maturities, ranging from Rp194,048 to Rp207,385. Conversely, put options become more valuable when the strike price exceeds the market prices, reaching up to Rp107,778. The proposed model offers practical value for more accurate pricing and investment strategies.</p></td></tr></tbody></table>

ZERO Jurnal Sains Matematika dan TerapanVol. 9(1)
Universitas Syiah Kuala (ID)
Openalex Percentile: Top 71%
Market Dynamics and Volatility
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The Trinomial Tree Method in Pricing European Gold Option with Volatility Forecasting Using the GARCH (1,1) Model — Rini Oktavia, Intan Syahrini, et al. · ZERO Jurnal Sains Matematika dan Terapan (2025) | TGRS Research Map | TGRS