{"title":"高频交易","authors":"S. Chakravarty, Palash Sarkar","doi":"10.1108/978-1-78973-893-320201015","DOIUrl":null,"url":null,"abstract":"HREE innovations in electronic trading of stocks and options have been in the headlines recently: high-frequency trading, flash trades, and dark pools. Technical improvements such as these are usually assumed to raise efficiency, but these innovations challenge such assumptions and may pose some public interest concerns because of their effect on stability. Studying market microstructures illuminates the processes through which prices are determined. Markets often appear to be magic black boxes. Supply and demand go into the box and an invisible hand pulls out the price—much like a magician producing a rabbit from a hat. But important things happen inside those boxes. In the case of electronic trading of securities and derivatives, the microstructure inside the box includes the mechanisms for submitting buy and sell orders (that is, bid and offer quotes) into a market, viewing of those quotes by market participants, and executing trades by matching orders to buy and sell. If this is done in an immediate and transparent manner that enables all market participants to see and trade at the same prices, then reality approaches the ideal of the efficient-market hypothesis. When markets become segmented and informational advantages are built into market mechanisms, efficiency is impaired and fairness undermined. This article explores these financial policy issues to explain how they impact pricing efficiency at the market microstructure level and to discuss how corrective regulation can improve efficiency. 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High-frequency trading (HFT), also called black box trading, uses high-speed computers governed by algorithms (or instructions to the computer) to analyze data, identify investment opportunities, and manage order flow to the markets. An HFT firm can submit a thousand orders a minute to an exchange and just as quickly cancel them and …","PeriodicalId":329471,"journal":{"name":"An Introduction to Algorithmic Finance, Algorithmic Trading and Blockchain","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-frequency Trading\",\"authors\":\"S. Chakravarty, Palash Sarkar\",\"doi\":\"10.1108/978-1-78973-893-320201015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"HREE innovations in electronic trading of stocks and options have been in the headlines recently: high-frequency trading, flash trades, and dark pools. 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If this is done in an immediate and transparent manner that enables all market participants to see and trade at the same prices, then reality approaches the ideal of the efficient-market hypothesis. When markets become segmented and informational advantages are built into market mechanisms, efficiency is impaired and fairness undermined. This article explores these financial policy issues to explain how they impact pricing efficiency at the market microstructure level and to discuss how corrective regulation can improve efficiency. High-frequency trading, flash trading, and dark pools all have their origin in two key marketplace innovations—electronic trading and the closely related alternative trading systems (ATS). Electronic trading has quickly come to dominate traditional trading, both on exchanges and in over-the-counter markets. Computer systems automatically match buy and sell orders that were themselves submitted through computers. Floor trading at stock and derivatives exchanges has been eliminated in all but the largest and most prominent markets, such as the New York Stock Exchange (NYSE), and even in those markets floor trading coexists with electronic trading. ATS are computer-automated order-matching systems that offer exchange-like trading opportunities at lower costs but are often subject to lower disclosure requirements and different trading rules. High-frequency trading (HFT), also called black box trading, uses high-speed computers governed by algorithms (or instructions to the computer) to analyze data, identify investment opportunities, and manage order flow to the markets. 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High-frequency Trading
HREE innovations in electronic trading of stocks and options have been in the headlines recently: high-frequency trading, flash trades, and dark pools. Technical improvements such as these are usually assumed to raise efficiency, but these innovations challenge such assumptions and may pose some public interest concerns because of their effect on stability. Studying market microstructures illuminates the processes through which prices are determined. Markets often appear to be magic black boxes. Supply and demand go into the box and an invisible hand pulls out the price—much like a magician producing a rabbit from a hat. But important things happen inside those boxes. In the case of electronic trading of securities and derivatives, the microstructure inside the box includes the mechanisms for submitting buy and sell orders (that is, bid and offer quotes) into a market, viewing of those quotes by market participants, and executing trades by matching orders to buy and sell. If this is done in an immediate and transparent manner that enables all market participants to see and trade at the same prices, then reality approaches the ideal of the efficient-market hypothesis. When markets become segmented and informational advantages are built into market mechanisms, efficiency is impaired and fairness undermined. This article explores these financial policy issues to explain how they impact pricing efficiency at the market microstructure level and to discuss how corrective regulation can improve efficiency. High-frequency trading, flash trading, and dark pools all have their origin in two key marketplace innovations—electronic trading and the closely related alternative trading systems (ATS). Electronic trading has quickly come to dominate traditional trading, both on exchanges and in over-the-counter markets. Computer systems automatically match buy and sell orders that were themselves submitted through computers. Floor trading at stock and derivatives exchanges has been eliminated in all but the largest and most prominent markets, such as the New York Stock Exchange (NYSE), and even in those markets floor trading coexists with electronic trading. ATS are computer-automated order-matching systems that offer exchange-like trading opportunities at lower costs but are often subject to lower disclosure requirements and different trading rules. High-frequency trading (HFT), also called black box trading, uses high-speed computers governed by algorithms (or instructions to the computer) to analyze data, identify investment opportunities, and manage order flow to the markets. An HFT firm can submit a thousand orders a minute to an exchange and just as quickly cancel them and …
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Prelims Portfolio Optimisation High-frequency Trading Measures of Risk Applications of Blockchain
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