Patterns of 50 ETF Options Implied Volatility in China: On Implied Volatility Functions

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dc.contributor.authorLi, Pengshi
dc.contributor.authorLin, Yan
dc.contributor.authorZhong, Yuting
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2021-03-16T10:51:27Z
dc.date.available2021-03-16T10:51:27Z
dc.description.abstractThe aim of this study is to examine the volatility smile based on the European options on Shanghai stock exchange 50 ETF. The data gives evidence of the existence of a well-known U-shaped implied volatility smile for the SSE 50 ETF options market in China. For those near-month options, the implied volatility smirk is also observed. And the implied volatility remains high for the short maturity and decreases as the maturity increases. The patterns of the implied volatility of SSE 50 ETF options indicate that in-the-money options and out-of-the-money options are more expensive relative to at-the-money options. This makes the use of at-the-money implied volatility for pricing out-of- or in-the-money options questionable. In order to investigate the implied volatility, the regression-based implied volatility functions model is considered employed to study the implied volatility in this study as this method is simple and easy to apply in practice. Several classical implied volatility functions are investigated in this paper to find whether some kind of implied volatility functions could lead to more accurate options pricing values. The potential determinants of implied volatility are the degree of moneyness and days left to expiration. The empirical work has been expressed by means of simple ordinary least squares framework. As the study shows, when valuing options, the results of using volatility functions are mixed. For far-month options, using at-the-money implied volatility performs better than other volatility functions in option valuation. For near-month options, the use of volatility functions can improve the valuation accuracy for deep in-the-money options or deep out-of-the-money options. However, no particular implied volatility function performs very well for options of all moneyness level and time to maturity.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2021-1-009
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/159934
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAndreou, P. C., Charalamous, C., & Martzoukous, S. H. (2015). Assessing the performance of symmetric and asymmetric implied volatility functions. Review of Quantitative Finance and Accounting, 42(3), 373–397. https://doi.org/10.1007/S11156-013-0346-z
dc.relation.isbasedonBhat, A. P. (2018). The economic determinants of the implied volatility function for currency options: Evidence from India. International Journal of Emerging Market, 13(6), 1798–1819. https://doi.org/10.1108/IJoEM-08-2017-0308
dc.relation.isbasedonDerman, E., & Kani, I. (1994). Riding on a smile. Risk, 7(02), 32–39. Retrieved from https://www.researchgate.net/publication/239059413
dc.relation.isbasedonDumas, B., Fleming, J., & Whaley, R. E. (1998). Implied volatility functions: Empirical tests. The Journal of Finance, 53(6), 2059–2106. https://doi.org/10.1111/0022-1082.00083
dc.relation.isbasedonEngström, M. (2002). Do Swedes smile? On implied volatility functions. Journal of Multinational Financial Management, 12(4–5), 285–304. https://doi.org/10.1016/s1042-444x(02)00012-9
dc.relation.isbasedonHilliard, J., & Zhang, H. (2019). Regulatory Soft Interventions in the Chinese Market: Compliance Effects and Impact on Option Market Efficiency. The Financial Review, 54(2), 265–301. https://doi.org/10.1111/fire.12189
dc.relation.isbasedonHull, J. (2012). Options, futures and other derivatives. London: Pearson.
dc.relation.isbasedonMacBeth, J. D., & Merville, L. J. (1979). An empirical examination of the Black-Scholes call option pricing model. The Journal of Finance, 34(5), 1173–1186. https://doi.org/10.2307/2327242
dc.relation.isbasedonNarain, Nigam, N. K., & Pandey, P. (2016). Behavior and determinants of implied volatility in Indian market. Journal of Advance in Management Research, 13(3), 271–291. https://doi.org/10.1108/JAMR-09-2015-0062
dc.relation.isbasedonPeña, I., Rubio, G., & Serna, G. (1999). Why do we smile? On the determinants of the implied volatility function. Journal of Banking & Finance, 23(8), 1151–1179. https://doi.org/10.1016/s0378-4266(98)00134-4
dc.relation.isbasedonPeña, I., Rubio, G., & Serna, G. (2001). Smiles, Bid-ask Spreads and Option Pricing. European Financial Management, 7(3), 351–374. https://doi.org/10.1111/1468-036X.00160
dc.relation.isbasedonRosenberg, J. (2000). Implied Volatility Functions: A Reprise. The Journal of Derivatives, 7(3), 51–64. https://doi.org/10.3905/jod.2000.319124
dc.relation.isbasedonRouah, F. D., & Vainberg, G. (2012). Option Pricing Models and Volatility Using Excel-VBA. New Jersey, NJ: John Wiley & Sons. https://doi.org/10.1002/9781119202097
dc.relation.isbasedonRubinstein, M. (1985). Nonparametric Tests of Alternative Option Pricing Models Using All Reported Trades and Quotes on the 30 Most Active CBOE Option Classes from August 23, 1976 through August 31, 1978. The Journal of Finance, 40(2), 455–480. https://doi.org/10.2307/2327895
dc.relation.isbasedonRubinstein, M. (1994). Implied Binomial Trees. The Journal of Finance, 49(3), 771–818. https://doi.org/10.2307/2329207
dc.relation.isbasedonSoini, V., & Lorentzen, S. (2019). Option prices and implied volatility in the crude oil market. Energy Economics, 83, 515–539. https://doi.org/10.1016/j.eneco.2019.07.011
dc.relation.isbasedonTanha, H., & Dempsey, M. (2015). Do Aussie markets smile? Implied volatility functions and determinants. Applied Economics, 47(30), 3143–3163. https://doi.org/10.1080/00036846.2015.1013606
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectimplied volatilityen
dc.subjectsmile patternsen
dc.subjectimplied volatility functionsen
dc.subject.classificationG10
dc.subject.classificationG13
dc.titlePatterns of 50 ETF Options Implied Volatility in China: On Implied Volatility Functionsen
dc.typeArticleen
local.accessopen
local.citation.epage145
local.citation.spage135
local.facultyFaculty of Economics
local.filenameEM_1_2021_9
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue1
local.relation.volume24
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