Algo-Trading (Algorithmic Trading)

Understanding Algo-Trading (Algorithmic Trading)

Algo-trading, also known as algorithmic trading, is an automated trading system that executes buy and sell orders based on predefined rules set by a computer program or algorithm. These algorithms take into account factors such as price, timing, and volume to determine the optimal timing for placing orders. When the market conditions align with the algorithm’s criteria, the algo-trading software will execute the corresponding buy or sell order.

For example, a basic illustration of algo-trading could involve buying 10 BTC when the ten-day moving average surpasses the 30-day moving average, and selling 10 BTC when the ten-day moving average falls below the 30-day moving average.

However, in reality, algo-trading involves more intricate rules and conditions to create a profitable trading strategy.

Traders utilize algo-trading for several reasons. It enables faster and more frequent trading across an entire portfolio, which would be challenging to achieve with manual orders. Algo-trading ensures immediate execution of orders, securing the best prices and reducing the risk of slippage. By removing human involvement, algorithmic trading minimizes the potential for errors or emotional reactions to market conditions.

On a larger scale, algo-trading contributes to more liquid markets due to increased order frequency. It also enhances market predictability as algorithms are designed to respond to emerging conditions.

While algo-trading is utilized in various markets, it offers additional advantages in the 24/7 cryptocurrency markets. Traders in these markets face the risk of missing opportunities or incurring losses while they are not actively monitoring the market. Algo-trading serves as a failsafe for manual traders when they are away from their screens.

Algo-trading is suitable for a wide range of trading strategies. Arbitrageurs rely on algorithms to ensure efficient order execution by capitalizing on incremental price differences. Short-term traders and scalpers use algo-trading to profit from small market movements at a high frequency, eliminating the risk of chasing losses. Market makers also employ algo-trading to maintain sufficient liquidity in the market.

Additionally, traders use algo-trading for backtesting specific strategies to determine their consistency in generating profits.

However, there are risks associated with algo-trading, such as system downtime or network outages. Since algorithms are programmed by humans, they are susceptible to human errors. Therefore, thorough backtesting is crucial to ensure the algorithm behaves as intended.

Lastly, algorithms strictly follow their programmed instructions and cannot account for unforeseen “black swan” events that may require human intervention and mitigating actions.

Author:

Alon Rajic is the owner and managing director of Israeli firm Finofin, which operates several personal finance portals, including moneytransfercomparison.com, a renowned guide on international money transfers and currency.

Alon Rajic founded Finofin in 2015 with the aim of simplifying complex financial topics for a wider audience. Prior to that, he served as the head of SEO for XLMedia PLC, a public company specializing in affiliation.

Alon became interested in Bitcoin relatively late and changed his views on cryptocurrency’s viability when institutional investors started getting involved around 2020.