What Is Algo-Trading (Algorithmic Trading)? with example 

Algo-trading, also known as algorithmic trading, is an automated trading system where buy and sell orders are placed according to the rules of a computer program or algorithm. 

The algorithm may be configured to consider price, but it may also look at other factors such as timing and volume. As soon as the market conditions fulfill the criteria of the algorithm, the algo-trading software will place a buy or sell order accordingly. 

A simple example could be the following:

Buy 10 BTC when the ten-day moving average exceeds the 30-day moving average; 

Sell 10 BTC when the ten-day moving average falls below the 30-day moving average.

However, in reality, algo-trading involves many more complex rules and conditions to build a formula for profitable trading. 

There are many reasons why traders use algo-trading — it offers the opportunity for faster and more frequent trading across an entire portfolio that wouldn’t be possible with manual orders. 

Because orders are instant, algo-trading secures the best prices and reduces the risk of slippage. Algorithmic trading takes the human element out of the equation, reducing the risk of mistakes or emotional reactions to market conditions. 

On a macro level, algo-trading creates more liquid markets thanks to a higher order frequency. It also makes markets more predictable because algorithms are programmed to respond to emerging conditions. 

Although algo-trading is used across many markets, it offers even more benefits in the 24/7 cryptocurrency markets, where traders risk missing opportunities or incurring loss risks while they’re asleep. Therefore, even those who prefer manual trading can use algo-trading as a failsafe for when they’re away from their screens. 

Algo-trading can be suitable for a wide range of trading strategies. Arbitrageurs who rely on incremental price differences can use an algorithm to ensure order efficiency. Short-term traders and scalpers who aim to capture profits from smaller market movements use algo-trading to ensure they can execute at a high enough frequency to be profitable, and eliminate the risk of chasing losses. Market makers also use algo-trading to ensure that there’s sufficient depth of liquidity in the market. 

Traders also use algo-trading for backtesting a particular strategy in order to check if it’s able to return a consistent profit. 

There are some risks with algo-trading, particularly around issues such as system downtime or network outages. Algorithms are also programmed by humans, so they can be subject to human errors, meaning that backtesting is critical to ensure the algorithm behaves as expected. 

Finally, an algorithm will always do exactly what it’s programmed to do and cannot account for unanticipated “black swan” events that may call for a more human intervention and mitigating actions.