The impact of algorithmic trading on the market quality in the stock exchange of Thailand
| dc.contributor.advisor | Nattawut Jenwittayaroje | |
| dc.contributor.author | Pavinee Hassavayukul | |
| dc.date.accessioned | 2023-05-12T07:50:02Z | |
| dc.date.available | 2023-05-12T07:50:02Z | |
| dc.date.issued | 2019 | |
| dc.date.issuedBE | 2562 | th |
| dc.description | Thesis (Ph.D. (Business Administration))--National Institute of Development Administration, 2019 | th |
| dc.description.abstract | This dissertation aims to study how the rising algorithmic trading activities in the Stock Exchange of Thailand affects the market quality. I conducted three researches to investigate the impact of algorithmic trading. One is on the impact of algorithmic trading on volatility. Second is on the effect of algorithmic trading on liquidity and third is on the relationship between algorithmic trading and price efficiency. Furthermore, I introduced two new algorithmic trading proxies, namely, algorithmic trading initiated by institutional and foreign investors to investigate the effect of algorithmic trading initiated by these two investors on the market quality. The first research demonstrates how algorithmic trading affects stock volatility in the Stock Exchange of Thailand. The study is based on SET100 stocks from March to December 2016. I implemented the OLS regression to establish the relationship between algorithmic trading and volatility and the two-stage least square regression and the Granger causality test to verify the causal relationship. I showed that on average, algorithmic trading proxy is associated and has a causal relationship with negative volatility. However, individually, algorithmic trading proxy is related to positive volatility. Similarly, algorithmic trading initiated by institutional and foreign investors lower realized and range-based volatility. During the volatile period, algorithmic trading decreases range-based volatility. There is no evidence that algorithmic trading affects realized volatility in the volatile period. The second research investigates the relationship between algorithmic trading and liquidity. In general, I found that algorithmic trading deteriorates liquidity by widening effective spread and lowering share turnover in the short run and reducing liquidity ratio in the long run. I confirmed the result by using the two-stage least square and showed that algorithmic trading causes liquidity to decrease by enlarging effective spread and shrinking share turnover. Information asymmetry is used to explain this phenomenon. An increase in algorithmic trading imposes adverse selection cost onto other investors, causing them to decrease their participation. Algorithmic trading initiated by foreign investors has more profound effect on deteriorating short-run liquidity while algorithmic trading initiated by institutional has more profound effect on decreasing long-run liquidity. During the volatile period, algorithmic trading also associates with lowering liquidity for all measures. The slope coefficient of algorithmic trading during volatile period is higher than during the whole sample except for the share turnover. Therefore, algorithmic traders have less effect on lowering share turnover during the volatile period than during the entire period. The third research determines whether the rise of algorithmic trading enhances price efficiency. There is no evidence that algorithmic trading influences price efficiency. However, when probing further, I found that algorithmic trading initiated by institutional and foreign investors and their interaction terms decrease pricing error, facilitating price efficiency. Furthermore, algorithmic trading initiated by foreign investors has a larger effect on augmenting price efficiency. During the volatile period, algorithmic trading, on the contrary, decreases price efficiency and enlarges price errors. Finally, this dissertation investigates the effect of algorithmic trading on market quality in detail and provides insightful conclusion for policymakers, regulators and investors in order to regulate or react to the increase in algorithmic trading strategies in the Stock Exchange of Thailand. | th |
| dc.format.extent | 235 leaves | th |
| dc.format.mimetype | application/pdf | th |
| dc.identifier.doi | 10.14457/NIDA.the.2019.133 | |
| dc.identifier.other | b207816 | th |
| dc.identifier.uri | https://repository.nida.ac.th/handle/662723737/6419 | |
| dc.language.iso | eng | th |
| dc.publisher | National Institute of Development Administration | th |
| dc.rights | ผลงานนี้เผยแพร่ภายใต้ สัญญาอนุญาตครีเอทีฟคอมมอนส์แบบ แสดงที่มา-ไม่ใช้เพื่อการค้า-ไม่ดัดแปลง 4.0 (CC BY-NC-ND 4.0) | th |
| dc.subject.other | Stock exchanges -- Thailand | th |
| dc.title | The impact of algorithmic trading on the market quality in the stock exchange of Thailand | th |
| dc.type | text--thesis--doctoral thesis | th |
| mods.genre | Dissertation | th |
| mods.physicalLocation | National Institute of Development Administration. Library and Information Center | th |
| thesis.degree.department | NIDA Business School | th |
| thesis.degree.discipline | Business Administration | th |
| thesis.degree.grantor | National Institute of Development Administration | th |
| thesis.degree.level | Doctoral | th |
| thesis.degree.name | Doctor of Philosophy | th |