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Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.Financial markets with fully electronic execution and similar electronic communication networks developed in the late 1980s and 1990s. S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US

This type of trading is what is driving the new demand for low latency proximity hosting and global exchange connectivity.Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close.In the past several years algo trading has been gaining traction with both retails and institutional traders.at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders.MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7; In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.

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Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.

Financial markets with fully electronic execution and similar electronic communication networks developed in the late 1980s and 1990s. S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US

This type of trading is what is driving the new demand for low latency proximity hosting and global exchange connectivity.Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close.In the past several years algo trading has been gaining traction with both retails and institutional traders.at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders.MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7; In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.

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Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.Financial markets with fully electronic execution and similar electronic communication networks developed in the late 1980s and 1990s. S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US$0.0625) to US$0.01 per share, may have encouraged algorithmic trading as it changed the market microstructure by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered.(See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010." Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange's “designated order turnaround” system (DOT, and later Super DOT), which routed orders electronically to the proper trading post, which executed them manually.

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Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.

Financial markets with fully electronic execution and similar electronic communication networks developed in the late 1980s and 1990s. S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US$0.0625) to US$0.01 per share, may have encouraged algorithmic trading as it changed the market microstructure by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.

As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered.

(See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010." Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange's “designated order turnaround” system (DOT, and later Super DOT), which routed orders electronically to the proper trading post, which executed them manually.

This increased market liquidity led to institutional traders splitting up orders according to computer algorithms so they could execute orders at a better average price.

These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.

]].01 per share, may have encouraged algorithmic trading as it changed the market microstructure by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.

As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered.

(See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010." Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange's “designated order turnaround” system (DOT, and later Super DOT), which routed orders electronically to the proper trading post, which executed them manually.

This increased market liquidity led to institutional traders splitting up orders according to computer algorithms so they could execute orders at a better average price.

These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.

.01 per share, may have encouraged algorithmic trading as it changed the market microstructure by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered.(See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010." Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange's “designated order turnaround” system (DOT, and later Super DOT), which routed orders electronically to the proper trading post, which executed them manually.

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This type of trading is what is driving the new demand for low latency proximity hosting and global exchange connectivity.

Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close.

In the past several years algo trading has been gaining traction with both retails and institutional traders.

at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders.

MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7; In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.

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This type of trading is what is driving the new demand for low latency proximity hosting and global exchange connectivity.Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close.In the past several years algo trading has been gaining traction with both retails and institutional traders.at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders.MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7; In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.

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