If you are considering trading or you have been doing so for quite some time, you will know that you have many different options available to you. One of the key decisions you need to make is whether to make human or automated trades. The latter, known as algorithmic trading, has become very popular because of its speed and the fact that it eliminates human error and human emotions. However, there are many different algorithmic trading strategies that you can use, which we are going to cover in further detail below.

Algorithmic Trading

Why has algorithmic trading become so popular?

Before we take a look at the different strategies you can use for algorithmic trading, let’s take a look at the benefits associated with this approach and the reasons why it has become so popular:

  • Trades are conducted at the best possible prices
  • Human errors that are caused due to emotion are reduced or eliminated altogether
  • Trade order placement is accurate and instant
  • You can back-test your trades
  • Transaction costs are lowered
  • There is less chance of mistakes being made because of manual input
  • Automated checks can be conduction on a number of different markets at the same time

Some of the algorithmic trading strategies you can use

It is not hard to see why algorithmic trading has become the preferred choice for a lot of traders. But, what sort of strategy are you going to use? Let’s take a look at some of the most popular options in further detail below.

  • Trend-following strategies: This is undoubtedly the most common strategy that is used by traders today. This involves following trends in price level movements, channel breakouts, moving averages, and other technical indicators. This is one of the most straightforward and easiest strategies to implement using the trading software because you do not need to make any price forecasts or predictions.
  • Implementation shortfall – This is a strategy that is designed to lower the execution expense of an order by making a trade in the market real-time. This means that the cost of the order is reduced and that the trader makes the most of the opportunity cost of delayed execution.
  • Percentage of volume (POV) – This involves the algorithm continuing to send partial orders until the trader order has been fully filled. It does this using a participation ratio that has already been defined and in accordance with the volume that has been traded in the market.
  • Time-weighted average price (TWAP) – Another strategy to consider is TWAP. This breaks up a big order and releases small chunks of it that have been determined dynamically. Evenly divided time slots are used from the start and end time in order to release these small trade chunks. The purpose of this is to ensure the order is executed closer to the average price between the start and end time, which lowers the market impact.
  • Index funding rebalancing: Index funds have specific rebalancing periods to bring their holidays on par with their related benchmark indices. For algorithmic traders, this presents a great opportunity to make a profit. This is because you can make money on expected traders that provide 20 to 80 basis points, depending on the quantity of stocks in the index fund, prior to the index rebalancing.
  • Arbitrage opportunities: The final trading strategy we are going to look at is taking advantage of arbitrage opportunities. This means purchasing a dual-listed stock at a lower price in one market and then selling it in another market at a higher price.

Hopefully, you now have a better understanding regarding algorithmic trading and the different strategies that are available. There is no denying that there are lots of clear benefits associated with this approach, but nothing is bulletproof, especially in the world of trading. You need to define your strategy and plan beforehand, and you need to stick with it. You also need to continue to analyse all of your trades so you can see where you are getting it wrong and where mistakes are being made so you can adjust your indicators if needed.

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