Algorithmic execution is prevalent in almost every instance of institutional risk-taking. More quantitatively-focused investors such as systematic hedge funds, market makers, and high-frequency traders develop proprietary execution algorithms explicitly designed to serve their investment strategies. Other investors, such as pension funds, mutual funds, and discretionary hedge funds utilize trade execution algorithms made available, for example, through investment bank trading desks. The reasons algorithmic execution has become best practice in traditional markets are many, starting with the aim of entering and Algorithmic execution is prevalent in almost every instance of institutional risk-taking. More quantitatively-focused investors such as systematic hedge funds, market makers, and high-frequency traders develop proprietary execution algorithms explicitly designed to serve their investment strategies. Other investors, such as pension funds, mutual funds, and discretionary hedge funds utilize trade execution algorithms made available, for example, through investment bank trading desks. The reasons algorithmic execution has become best practice in traditional markets are many, starting with the aim of entering and
Algorithmic execution is prevalent in almost every instance of institutional risk-taking. More quantitatively-focused investors such as systematic hedge funds, market makers, and high-frequency traders develop proprietary execution algorithms explicitly designed to serve their investment strategies. Other investors, such as pension funds, mutual funds, and discretionary hedge funds utilize trade execution algorithms made available, for example, through investment bank trading desks. The reasons algorithmic execution has become best practice in traditional markets are many, starting with the aim of entering and
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