Pho-tōng hong-hiám (ing-gú: Volatility risk) sī iû-î hong-hiám in-sòo ê pho-tōng-sìng [en] piàn-huà jî-lâi tì-sú tâu-tsu tsoo-ha̍p kè-siàu piàn-huà ê hong-hiám. Pho-tōng hong-hiám thong-siông sik-iōng teh ián-sing kang-kū ê taut-su tsoo-ha̍p, kî-tiong i-ê ki-tshóo tsu-sán ê pho-tōng sìng sī kè-siàu tsú-iàu íng-hióng in-sòo.

Tuì pho-tōng ê bín-kám-sìng

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Tsún-tsat tâu-tsu tsoo-ha̍p (hi̍k-tsiá tsu-sán) kè-siàu tuì pho-tōng piàn-huà ê bín-kám sìng ê tsí-piau sī vega [en], tsik-sī tâu-tsu tsoo-ha̍p kè-ta̍tsiong-tuì teh piáu-ti̍t tsu-sán pho-tōng ê piàn-huà.[1][2]

Hong-hiám kuán-lí

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Tsit tsióng hong-hiám ē-tàng sú-iōng sik-tòng ê kim-iông kang-kū lâi kuán-lí, Tsia ê kang-kū ê kè-siàu kài-tsāi teh ū-tīng kim-iông tsu-sán (kóo-phiò, siong-phín, lī-lu̍t tíng-tíng) ê pho-tōng sìng. Pí-jû kóo-phiò ê VIX kî-huè ha̍p-iok, hi̍k-tsiá lī-lu̍t ê siōng-ham-hān, hā-hān í-ki̍p tiāu-kî kî-khuân.[3][4]

Hong-hiám kuán-lí sī tâu-tsu kuat-tshik kuè-tîng tiong hun-sik hām/hi̍k-tsiá giām-siu ê phuè-tì kah sik-pia̍t. Pún-tsit siōng, Teh ta̍k-pái tâu-tsu-tsiá hi̍k-tsiá tâu-tsu tsoo-ha̍p king-lí phîng-kóo tâu-tsu tang-tiong ê tsiâm-tsāi sún-sit ê sî-tsūn, tō-ē huat-sing tsit-tsióng tsōng-hóng. Teh it-tīng ê tâu-tsu bo̍k-piau tsi-hā, ē tshut-hiān ha̍p-sik ê kái-kuat hong-àn (hi̍k-tsiá bô kái-kuat hong-àn) lâi phîng-kóo tâu-tsu-tsiá ê bo̍k-piau kap hāu-lu̍t.[5]

Put-tong ê hong-hiám kuán-lí ē tuì kong-si kah kò-jîn sán-sing hū-bīn ê íng-hióng.Pí-jû, khai-sí tī 2008-nî ê king-tsè sue-thè tsiânn-tuā ê thîng-tōo siōng sī iû-î kim-iông ki-kòo ê sìn-iōng hong-hiám kuán-lí song-sán tsō-sîng ê.[6][7]

Tsù-kái

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  1. Ploeg, Antoine Petrus Cornelius van der (2006). Stochastic Volatility and the Pricing of Financial Derivatives. Tinbergen Institute Research Series (ēng Eng-gí). Amsterdam, Netherlands: Rozenberg Publishers. pp. 25–26. ISBN 978-90-5170-577-5. 
  2. Huang, Declan Chih-Yen (2002) [1998]. "The Information Content of the FTSE100 Index Option Implied Volatility and Its Structural Changes With Links to Loss Aversion". Chū Knight, John L.; Satchell, Stephen. Forecasting Volatility in the Financial Markets. Butterworth - Heinemann Finance (ēng Eng-gí). Oxford and Woburn, MA: Butterworth-Heinemann. pp. 375–376. ISBN 978-0-7506-5515-6. 
  3. Neftci, Salih N. (2004). Principles of Financial Engineering. Academic Press Advanced Finance Series (ēng Eng-gí). San Diego, CA and London: Academic Press. pp. 430–431. ISBN 978-0-12-515394-2. 
  4. Xekalaki, Evdokia; Degiannakis, Stavros (2010). ARCH Models for Financial Applications (ēng Eng-gí). Chichester, UK: John Wiley & Sons. pp. 341–343. ISBN 978-0-470-68802-1. 
  5. Whaley, Robert (2008). "Volatility Derivatives". Chū Fabozzi, Frank J. Handbook of Finance, Financial Markets and Instruments (ēng Eng-gí). Hoboken, NJ: John Wiley & Sons. pp. 193–194. ISBN 978-0-470-39107-5. 
  6. Saunders, Anthony; Allen, Linda (2010). Credit Risk Management In and Out of the Financial Crisis: New Approaches to Value at Risk and Other Paradigms (ēng Eng-gí). Hoboken, NJ: John Wiley & Sons. pp. 3–4. ISBN 978-0-470-62236-0. 
  7. Mačerinskienė, Irena; Ivaškevičiūtė, Laura; Railienė, Ginta (2014). "The Financial Crisis Impact on Credit Risk Management in Commercial Banks". KSI Transactions on KNOWLEDGE SOCIETY. 7 (1): 5–15. 

Tsham-ua̍t

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  • Derivative
  • Implied volatility
  • Chhī-tiûⁿ hong-hiám [en] (tshī-tiûnn hong-hiám)
  • Risk management
  • Standard deviation
  • Value at risk method
  • Volatility risk premium

Guā-pōo liân-kiat

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