Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets
Financial market liquidity is a popular research topic. Investor-driven research uses the turnover rate to measure liquidity and generally finds that the higher the stock turnover rate, the lower the returns. However, the traditional financial liquidity theory has been impacted by new machine-driven...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co. Ltd.
2025-03-01
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| Series: | Data Science and Management |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666764924000365 |
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| author | Qing Zhu Chenyu Han Yuze Li |
| author_facet | Qing Zhu Chenyu Han Yuze Li |
| author_sort | Qing Zhu |
| collection | DOAJ |
| description | Financial market liquidity is a popular research topic. Investor-driven research uses the turnover rate to measure liquidity and generally finds that the higher the stock turnover rate, the lower the returns. However, the traditional financial liquidity theory has been impacted by new machine-driven quantitative trading models. To explore high machine-driven liquidity and the impact of high turnover rates on returns, this study establishes a dual-market quantitative trading system, introduces a variational modal decomposition (VMD)-bidirectional gated recurrent unit (BiGRU) model for data prediction, and uses the back-end Hong Kong foreign exchange market to develop a quantitative trading strategy using the same rotating funds in the U.S. and Chinese stock markets. The experimental results show that given a principal amount of 210,000.00 CNY, the final predicted net return is 226,538.30 CNY, a net return of 107.86%, which is 40.6% higher than the net return of a single Chinese market. We conclude that, under machine-driven trading, increasing liquidity and turnover increase returns. This study provides a new perspective on liquidity theory that is useful for future financial market research and quantitative trading practices. |
| format | Article |
| id | doaj-art-024492404850490baf61513a929be661 |
| institution | Kabale University |
| issn | 2666-7649 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Data Science and Management |
| spelling | doaj-art-024492404850490baf61513a929be6612025-02-06T05:12:54ZengKeAi Communications Co. Ltd.Data Science and Management2666-76492025-03-01814858Dual-market quantitative trading: The dynamics of liquidity and turnover in financial marketsQing Zhu0Chenyu Han1Yuze Li2International Business School, Shaanxi Normal University, Xi’an, 710061, China; Shaanxi Logistics Group Logistics Science and Technology Innovation Integrated Development Research Center of Xi’an Jiaotong University, Xi’an, 710049, China; Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China; Corresponding author. International Business School, Shaanxi Normal University, Xi’an, 710061, China.International Business School, Shaanxi Normal University, Xi’an, 710061, ChinaQuestrom School of Business, Boston University, Boston, 02215, United StatesFinancial market liquidity is a popular research topic. Investor-driven research uses the turnover rate to measure liquidity and generally finds that the higher the stock turnover rate, the lower the returns. However, the traditional financial liquidity theory has been impacted by new machine-driven quantitative trading models. To explore high machine-driven liquidity and the impact of high turnover rates on returns, this study establishes a dual-market quantitative trading system, introduces a variational modal decomposition (VMD)-bidirectional gated recurrent unit (BiGRU) model for data prediction, and uses the back-end Hong Kong foreign exchange market to develop a quantitative trading strategy using the same rotating funds in the U.S. and Chinese stock markets. The experimental results show that given a principal amount of 210,000.00 CNY, the final predicted net return is 226,538.30 CNY, a net return of 107.86%, which is 40.6% higher than the net return of a single Chinese market. We conclude that, under machine-driven trading, increasing liquidity and turnover increase returns. This study provides a new perspective on liquidity theory that is useful for future financial market research and quantitative trading practices.http://www.sciencedirect.com/science/article/pii/S2666764924000365LiquidityMachine learningDual-market algorithmic tradingReturn |
| spellingShingle | Qing Zhu Chenyu Han Yuze Li Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets Data Science and Management Liquidity Machine learning Dual-market algorithmic trading Return |
| title | Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets |
| title_full | Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets |
| title_fullStr | Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets |
| title_full_unstemmed | Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets |
| title_short | Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets |
| title_sort | dual market quantitative trading the dynamics of liquidity and turnover in financial markets |
| topic | Liquidity Machine learning Dual-market algorithmic trading Return |
| url | http://www.sciencedirect.com/science/article/pii/S2666764924000365 |
| work_keys_str_mv | AT qingzhu dualmarketquantitativetradingthedynamicsofliquidityandturnoverinfinancialmarkets AT chenyuhan dualmarketquantitativetradingthedynamicsofliquidityandturnoverinfinancialmarkets AT yuzeli dualmarketquantitativetradingthedynamicsofliquidityandturnoverinfinancialmarkets |