Examination of Arbitrage Opportunities at Chinese Financial Market

dc.contributor.advisorTichý, Tomáš
dc.contributor.authorDai, Jingpeng
dc.contributor.refereeKresta, Aleš
dc.date.accepted2022-05-23
dc.date.accessioned2022-09-01T07:18:23Z
dc.date.available2022-09-01T07:18:23Z
dc.date.issued2022
dc.description.abstractThe purpose of this thesis is to study arbitrage opportunities in Chinese financial markets and study how to use stock index futures and CSI 300ETF for arbitrage. This thesis uses a variety of arbitrage strategies to study arbitrage opportunities, such as geographic arbitrage, futures arbitrage, time arbitrage and other arbitrage strategies, and focuses on statistical arbitrage opportunities in China's financial market. This thesis uses two statistical arbitrage models, namely the least squares OLS constant volatility model and GARCH time-varying volatility model, select the 1-minute high-frequency trading data closing prices of stock index futures IF2101 and Huatai-Pinebridge CSI 300 ETF. Judging from the combination of traditional data and Sharpe ratio, using the GARCH model for forward arbitrage results is the best. Therefore, it is recommended that arbitragers prefer the GARCH model for the positive arbitrage operation, followed by the OLS model for the reverse arbitrage operation when conducting statistical arbitrage in China.en
dc.description.abstractThe purpose of this thesis is to study arbitrage opportunities in Chinese financial markets and study how to use stock index futures and CSI 300ETF for arbitrage. This thesis uses a variety of arbitrage strategies to study arbitrage opportunities, such as geographic arbitrage, futures arbitrage, time arbitrage and other arbitrage strategies, and focuses on statistical arbitrage opportunities in China's financial market. This thesis uses two statistical arbitrage models, namely the least squares OLS constant volatility model and GARCH time-varying volatility model, select the 1-minute high-frequency trading data closing prices of stock index futures IF2101 and Huatai-Pinebridge CSI 300 ETF. Judging from the combination of traditional data and Sharpe ratio, using the GARCH model for forward arbitrage results is the best. Therefore, it is recommended that arbitragers prefer the GARCH model for the positive arbitrage operation, followed by the OLS model for the reverse arbitrage operation when conducting statistical arbitrage in China.cs
dc.description.department154 - Katedra financícs
dc.description.resultvelmi dobřecs
dc.format.extent1883104 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.otherOSD002
dc.identifier.senderS2751
dc.identifier.thesisDAI0006_EKF_N0412A050005_2022
dc.identifier.urihttp://hdl.handle.net/10084/146679
dc.language.isoen
dc.publisherVysoká škola báňská – Technická univerzita Ostravacs
dc.rights.accessopenAccess
dc.subjectstatistical arbitrage; positive arbitrageen
dc.subjectreverse arbitrageen
dc.subjectGARCH modelen
dc.subjectOLS modelen
dc.subjectStock Index Futuresen
dc.subjectCSI 300ETFen
dc.subjectstatistical arbitrage; positive arbitragecs
dc.subjectreverse arbitragecs
dc.subjectGARCH modelcs
dc.subjectOLS modelcs
dc.subjectStock Index Futurescs
dc.subjectCSI 300ETFcs
dc.thesis.degree-grantorVysoká škola báňská – Technická univerzita Ostrava. Ekonomická fakultacs
dc.thesis.degree-levelMagisterský studijní programcs
dc.thesis.degree-nameIng.
dc.thesis.degree-programFinancecs
dc.titleExamination of Arbitrage Opportunities at Chinese Financial Marketen
dc.title.alternativeExamination of Arbitrage Opportunities at Chinese Financial Marketcs
dc.typeDiplomová prácecs

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