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Examples of strategies used in algorithmic trading include systematic trading, market making, inter-market spreading, arbitrage, or pure speculation, such as trend following. Many fall into the category of high-frequency trading (HFT), which is characterized by high turnover and high order-to-trade ratios. [7]
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.
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]
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 ...
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.
TerraUSD, once the third-largest stablecoin by market cap, is a stark example of the pitfalls of algorithmic stablecoins. TerraUSD relied on a complex system of arbitrage and other ...