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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.
Around 2005, copy trading and mirror trading emerged as forms of automated algorithmic trading. These systems allowed traders to share their trading histories and strategies, which other traders could replicate in their accounts. One of the first companies to offer an auto-trading platform was Tradency in 2005 with its "Mirror Trader" software.
To tackle these issues, FIX Protocol Limited established the Algorithmic Trading Working Group in Q3 2004. [1] The initial focus of the group was to solve the first of these issues, which it did by defining a new group of fields, the StrategyParametersGrp, made up of FIX tags 957 through 960 – these tags were formally introduced with the release of FIX 5.0 in Q4 2006.
Systematic trading (also known as mechanical trading) is a way of defining trade goals, risk controls and rules that can make investment and trading decisions in a methodical way. [ 1 ] Systematic trading includes both manual trading of systems, and full or partial automation using computers.
In capital markets, low latency is the use of algorithmic trading to react to market events faster than the competition to increase profitability of trades. For example, when executing arbitrage strategies the opportunity to "arb" the market may only present itself for a few milliseconds before parity is achieved.
The effects of algorithmic and high-frequency trading are the subject of ongoing research. High frequency trading causes regulatory concerns as a contributor to market fragility. [ 56 ] Regulators claim these practices contributed to volatility in the May 6, 2010, Flash Crash [ 62 ] and find that risk controls are much less stringent for faster ...
Today, pairs trading is often conducted using algorithmic trading strategies on an execution management system. These strategies are typically built around models that define the spread based on historical data mining and analysis. The algorithm monitors for deviations in price, automatically buying and selling to capitalize on market ...
Le Bon's important work, The Crowd: A Study of the Popular Mind, discusses the role of "crowds" (also known as crowd psychology) and group behavior as they apply to the fields of behavioral finance, social psychology, sociology and history. Selden's 1912 book Psychology of The Stock Market applies the field of psychology directly to the stock ...