Algorithmic trading, also known as algo-trading or black-box trading, is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading was developed so that high volume trades and market orders could be executed in the best possible way.

Algorithmic trading makes use of complex formulas, combined with mathematical models and human oversight, to make decisions to buy or sell financial securities on an exchange. Algorithms are programmed to move in and out of trades to generate profits at a speed and frequency that is impossible for a human trader.

The main advantage of algorithmic trading is its speed and accuracy. Trades can be executed at the best possible prices and instantly, reducing the risk of manual errors in placing the trades. Algorithmic trading also allows for faster and more efficient trading, as it eliminates the need for traders to physically be present to enter or exit trades.

Moreover, algorithmic trading enhances liquidity and reduces the impact of large trades. By breaking up large orders into many small ones, algorithmic trading systems can minimize the impact of large trades on the market. This also increases the opportunities for traders as they can trade in different markets around the world without constant monitoring.

However, like any other system, algorithmic trading also has its drawbacks. One of the major concerns is the lack of transparency. Since these algorithms are proprietary and closely guarded by their owners, the strategies and tactics used are not disclosed to the public, making it difficult for regulators to monitor them.

Another concern is system overloads and network failures. With millions of trades being executed every second, there is a risk of overload on the systems and networks, leading to outages. This can result in significant losses if not managed properly.

Furthermore, algorithmic trading may cause flash crashes and other market disruptions. Since these systems are designed to execute trades based on certain patterns, they can exacerbate market trends, leading to extreme market volatility.

Despite these challenges, the use of algorithmic trading is on the rise. According to a report by the Financial Times, more than three-quarters of shares traded on US exchanges come from automatic trading systems. The trend is not just limited to the US; markets around the world are seeing an increase in algorithmic trading.

In conclusion, algorithmic trading offers numerous benefits such as increased speed and accuracy, enhanced liquidity, and reduced impact of large trades. However, it also poses certain risks like lack of transparency, system overloads, and potential market disruptions. As technology continues to advance, it’s crucial for regulatory bodies to keep pace and develop robust frameworks to manage the risks associated with algorithmic trading while harnessing its benefits.