Examination of Arbitrage Opportunities at Chinese Financial Market
| dc.contributor.advisor | Tichý, Tomáš | |
| dc.contributor.author | Dai, Jingpeng | |
| dc.contributor.referee | Kresta, Aleš | |
| dc.date.accepted | 2022-05-23 | |
| dc.date.accessioned | 2022-09-01T07:18:23Z | |
| dc.date.available | 2022-09-01T07:18:23Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The 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.abstract | The 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.department | 154 - Katedra financí | cs |
| dc.description.result | velmi dobře | cs |
| dc.format.extent | 1883104 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | OSD002 | |
| dc.identifier.sender | S2751 | |
| dc.identifier.thesis | DAI0006_EKF_N0412A050005_2022 | |
| dc.identifier.uri | http://hdl.handle.net/10084/146679 | |
| dc.language.iso | en | |
| dc.publisher | Vysoká škola báňská – Technická univerzita Ostrava | cs |
| dc.rights.access | openAccess | |
| dc.subject | statistical arbitrage; positive arbitrage | en |
| dc.subject | reverse arbitrage | en |
| dc.subject | GARCH model | en |
| dc.subject | OLS model | en |
| dc.subject | Stock Index Futures | en |
| dc.subject | CSI 300ETF | en |
| dc.subject | statistical arbitrage; positive arbitrage | cs |
| dc.subject | reverse arbitrage | cs |
| dc.subject | GARCH model | cs |
| dc.subject | OLS model | cs |
| dc.subject | Stock Index Futures | cs |
| dc.subject | CSI 300ETF | cs |
| dc.thesis.degree-grantor | Vysoká škola báňská – Technická univerzita Ostrava. Ekonomická fakulta | cs |
| dc.thesis.degree-level | Magisterský studijní program | cs |
| dc.thesis.degree-name | Ing. | |
| dc.thesis.degree-program | Finance | cs |
| dc.title | Examination of Arbitrage Opportunities at Chinese Financial Market | en |
| dc.title.alternative | Examination of Arbitrage Opportunities at Chinese Financial Market | cs |
| dc.type | Diplomová práce | cs |
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