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High-frequency trading strategies may use properties derived from market data feeds to identify orders that are posted at sub-optimal prices. Such orders may offer a profit to their counterparties that high-frequency traders can try to obtain. Examples of these features include the age of an order [54] or the sizes of displayed orders. [55]
Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. [1] This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been ...
Crowded trades occur when similar investment strategies — usually fueled by complex trading models —send investors all into the same stocks. ... The latest example: ... to see data driven ...
As a trading strategy, statistical arbitrage is a heavily quantitative and computational approach to securities trading. It involves data mining and statistical methods, as well as the use of automated trading systems. Historically, StatArb evolved out of the simpler pairs trade [3] strategy, in which stocks are put into pairs by fundamental or ...
Here is how those types stack up: Income strategies. These include covered calls and cash-secured puts involve selling options to collect premiums upfront. This generates income, but also caps ...
Hedge fund. A hedge fund is a pooled investment fund that holds liquid assets and that makes use of complex trading and risk management techniques to improve investment performance and insulate returns from market risk. Among these portfolio techniques are short selling and the use of leverage and derivative instruments. [ 1 ]
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