Masters of the Market: Unleashing Algorithmic Wizardry in Finance

Masters of the Market: Unleashing Algorithmic Wizardry in Finance

Jaspreet Kaur, Ercan Ozen
Copyright: © 2024 |Pages: 28
DOI: 10.4018/979-8-3693-1746-4.ch006
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Abstract

The inexorable advance of algorithms is driving a revolutionary change in the financial world, which is causing significant upheaval. This chapter goes into the complex realm of algorithmic trading, charting its history from the manual execution of trades to the complex methods used by today's financial whizzes. The chapter sheds light on the effect that algorithms have on the microstructure of markets and highlights the contribution that algorithms make to the development of prices, the dynamics of liquidity, and the overall efficiency of markets.
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Background And Context: Significance Of Algorithmic Trading In Finance

Using computer algorithms for automating the procedure of trading financial products in the stock exchange, the forex market, or other kinds of markets is known as algorithmic trading, sometimes referred to as algo trading or black-box trading. It involves executing transactions automatically with the use of preset criteria and procedures. The emergence of algorithmic trading, which is now a common occurrence in contemporary financial markets, is directly related to changes in market structure, technological breakthroughs, and the complexity of financial products (Auer et al., 2023).

Development of Trading Algorithms: Over time, algorithmic trading has seen substantial change. Trading was mostly done manually in the early days of financial markets, with traders executing orders on the trading floor. Algorithmic trading became more popular with the introduction of computers and computerised trading platforms. The 1987 stock market crisis and the events that followed brought attention to the necessity of automated systems capable of reacting quickly to market conditions. The creation and acceptance of algorithmic trading tactics resulted from this.

Developments in connectivity, processing power, and data availability have all contributed to the rise of algorithmic trading. A branch of algorithmic trading known as high-frequency trading (HFT) was created by traders who wanted to profit from incredibly brief price swings.

Technology and Facilities: A lot of cutting-edge technology, such as potent computers, fast data feeds, and complex algorithms, are necessary for algorithmic trading. With the help of this technology, traders may quickly execute orders, find trading opportunities, and analyse enormous volumes of data. Co-location services have grown in popularity as a way for trading companies to cut down on latency and have a performance advantage over exchange servers (Barzykin et al. 2023).

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