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題名 How volatility model specification affects volatility targeting performance: Evidence from Taiwan
作者 楊曉文
Huang, Jr-Wei;Yang, Sharon S.
貢獻者 金融系
關鍵詞 Conditional volatility targeting strategy; Taiwan capitalization weighted stock index; Model risk
日期 2026-06
上傳時間 13-Aug-2026 14:03:55 (UTC+8)
摘要 Investors show growing interest in portfolio risk management involving volatility-adjusted allocations. This study develops and assesses a framework for implementing such strategies in Taiwan's equity market, with particular emphasis on how modeling decisions affect investment outcomes. We build on previous research—especially, the conditional approach proposed by Bongaerts et al. (2020) and the ARMA-GARCH framework with jump components discussed by Maheu and McCurdy (2004) and Huang et al. (2024)— by examining the outcomes when different log-return-generating processes are chosen to make predictions. Empirical analysis based on the Taiwan Capitalization Weighted Stock Index shows that this combined specification provides better portfolio performance when it is employed in conjunction with a conditional volatility-targeting allocation rule. A cross-sectional analysis of financial, semiconductor, and food industry indices reveals that conditional volatility targeting strategies have different effects in different sectors. These findings underscore the importance of tailoring volatility models to the underlying distributional characteristics of market log-returns.
關聯 Pacific-Basin Finance Journal, Vol.99, Article:103195
資料類型 article
DOI https://doi.org/10.1016/j.pacfin.2026.103195
dc.contributor 金融系
dc.creator (作者) 楊曉文
dc.creator (作者) Huang, Jr-Wei;Yang, Sharon S.
dc.date (日期) 2026-06
dc.date.accessioned 13-Aug-2026 14:03:55 (UTC+8)-
dc.date.available 13-Aug-2026 14:03:55 (UTC+8)-
dc.date.issued (上傳時間) 13-Aug-2026 14:03:55 (UTC+8)-
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=184475-
dc.description.abstract (摘要) Investors show growing interest in portfolio risk management involving volatility-adjusted allocations. This study develops and assesses a framework for implementing such strategies in Taiwan's equity market, with particular emphasis on how modeling decisions affect investment outcomes. We build on previous research—especially, the conditional approach proposed by Bongaerts et al. (2020) and the ARMA-GARCH framework with jump components discussed by Maheu and McCurdy (2004) and Huang et al. (2024)— by examining the outcomes when different log-return-generating processes are chosen to make predictions. Empirical analysis based on the Taiwan Capitalization Weighted Stock Index shows that this combined specification provides better portfolio performance when it is employed in conjunction with a conditional volatility-targeting allocation rule. A cross-sectional analysis of financial, semiconductor, and food industry indices reveals that conditional volatility targeting strategies have different effects in different sectors. These findings underscore the importance of tailoring volatility models to the underlying distributional characteristics of market log-returns.
dc.format.extent 108 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Pacific-Basin Finance Journal, Vol.99, Article:103195
dc.subject (關鍵詞) Conditional volatility targeting strategy; Taiwan capitalization weighted stock index; Model risk
dc.title (題名) How volatility model specification affects volatility targeting performance: Evidence from Taiwan
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.pacfin.2026.103195
dc.doi.uri (DOI) https://doi.org/10.1016/j.pacfin.2026.103195