{"title":"金融科技与股市行为","authors":"T. Sekmen, M. Hati̇poğlu","doi":"10.4018/978-1-5225-7805-5.CH008","DOIUrl":null,"url":null,"abstract":"This chapter examines the effects of high-frequency trading (HFT) and algorithmic trading (AT) activities, which represent important technological developments in financial markets in the past two decades, on Borsa Istanbul in terms of volatility. To clarify stock market behaviors in terms of volatility, asymmetry, and risk return after the BISTECH transition, the GJR-GARCH-in-Mean and I-GARCH models were used. The dataset consists of the daily stock return series of the main and sub-sector indexes of Borsa Istanbul, covering the period from October 24, 2012 to June 1, 2018. Although there are mixed results for the sub-indexes, it is observed that in the post-BISTECH period, volatility increases significantly in the BIST 100 and BIST 30 indexes, where AT and HFT activities are used more frequently. In particular, the duration of volatility returns to average after shock increases about seven times for BIST 100 and about eight times for the BIST 30 in the post-BISTECH period. Overall, the results indicate that AC and HFT activities may have disruptive effects on financial markets.","PeriodicalId":164577,"journal":{"name":"FinTech as a Disruptive Technology for Financial Institutions","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"FinTech and Stock Market Behaviors\",\"authors\":\"T. Sekmen, M. Hati̇poğlu\",\"doi\":\"10.4018/978-1-5225-7805-5.CH008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This chapter examines the effects of high-frequency trading (HFT) and algorithmic trading (AT) activities, which represent important technological developments in financial markets in the past two decades, on Borsa Istanbul in terms of volatility. To clarify stock market behaviors in terms of volatility, asymmetry, and risk return after the BISTECH transition, the GJR-GARCH-in-Mean and I-GARCH models were used. The dataset consists of the daily stock return series of the main and sub-sector indexes of Borsa Istanbul, covering the period from October 24, 2012 to June 1, 2018. Although there are mixed results for the sub-indexes, it is observed that in the post-BISTECH period, volatility increases significantly in the BIST 100 and BIST 30 indexes, where AT and HFT activities are used more frequently. In particular, the duration of volatility returns to average after shock increases about seven times for BIST 100 and about eight times for the BIST 30 in the post-BISTECH period. Overall, the results indicate that AC and HFT activities may have disruptive effects on financial markets.\",\"PeriodicalId\":164577,\"journal\":{\"name\":\"FinTech as a Disruptive Technology for Financial Institutions\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FinTech as a Disruptive Technology for Financial Institutions\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-5225-7805-5.CH008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FinTech as a Disruptive Technology for Financial Institutions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-5225-7805-5.CH008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This chapter examines the effects of high-frequency trading (HFT) and algorithmic trading (AT) activities, which represent important technological developments in financial markets in the past two decades, on Borsa Istanbul in terms of volatility. To clarify stock market behaviors in terms of volatility, asymmetry, and risk return after the BISTECH transition, the GJR-GARCH-in-Mean and I-GARCH models were used. The dataset consists of the daily stock return series of the main and sub-sector indexes of Borsa Istanbul, covering the period from October 24, 2012 to June 1, 2018. Although there are mixed results for the sub-indexes, it is observed that in the post-BISTECH period, volatility increases significantly in the BIST 100 and BIST 30 indexes, where AT and HFT activities are used more frequently. In particular, the duration of volatility returns to average after shock increases about seven times for BIST 100 and about eight times for the BIST 30 in the post-BISTECH period. Overall, the results indicate that AC and HFT activities may have disruptive effects on financial markets.