Algorithmic Trading Explained

Algorithmic Trading is an automated trading method based on predetermined rules that can be programmed into software applications, enabling more precise trades while potentially increasing diversification and potentially decreasing risk. Furthermore, algorithmic trading may also provide cost savings since human traders no longer exist and their associated expenses need not be considered when trading.

Due to advances in technology and faster transmission speeds of information across borders, algorithmic trading has grown increasingly popular over time. Many firms provide this form of trading as services ranging from high-frequency trading (HFT) and portfolio management using algorithms.

Some algorithms focus on specific markets, like stocks or commodities. Others adopt specific strategies such as mean reversion - this method involves buying stock when its average price drops and selling when its average rises above its previous average price.





Another frequent application of algorithms is in optimizing trade execution. To do this, they often adjust order sizes based on real-time market trading volume in order to minimize implementation shortfall (the difference between decision price and actual execution price). Furthermore, other algorithms utilize "sniffers" which detect bid and ask prices matching orders with traders using matching bid-ask price searches.

No matter the purpose of an algorithm, its proper testing and implementation are critical to its success. Otherwise, algo trading company in india could occur that could negatively impact a trader's account, even potentially "black swan" events which can bring unpredicted losses.