Algorithmic trading strategies and their rationale

Algorithmic trading follows instructions that allow investors to place and execute trades automatically. However, this doesn’t mean a trader doesn’t have to do anything to get rewards. The trader’s task is to choose the strategy that will suit their trading style, amount of funds, risk management, and goals. 

Algorithmic trading became allowed in India in 2008 when the SEBI issued a memorable circular stating the country opened its markets to algo-trading. Since 2011, the turnover percentage, based on algo-trading, has increased by over 50% on the BSE’s Equities. 

Below you can find the best algorithmic trading strategies. 

Types of algorithmic trading strategies

Let’s start with key types of algo-trading strategies. 

1. Momentum

Momentum is the basic algorithmic trading system. The idea behind it is to catch a strong market trend. 

• This strategy can be used for simple trades. For instance, you can invest in five shares that perform better than others according to annual performance metrics. 
• You can make the strategy more comprehensive using both relative and absolute momentum. Investors can change the momentum system periodically — for instance, every week, month, quarter, or year. 

2. Mean reversion

There is a common belief that the price reverts to its average value after it’s oversold or overbought. The idea of the mean reversion strategy is to determine the long-term average price and find an oversold or overbought asset. If it’s oversold, you should buy it and sell it when the price reaches the center of the trading range (average price). When the price is overbought, investors sell the asset and buy it when the price reaches the middle point of the trading range. 

3. Seasonality strategies

When trading, it’s important to know the periods with higher and lower returns. For instance, the share market usually has higher returns during summer and at the end of the year. Many investors prefer to sell their losing trades by the end of the year to take advantage of the tax break. September is supposed to be the month with the lowest returns. Also, it’s worth remembering that stock prices fluctuate significantly by the end of a quarter and near the holidays. 

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Sniffing trading algorithms 

Besides standard algorithmic systems, there are so-called sniffing algorithms. They are used to determine whether an algorithm is used by a trader/investor on the other side. For instance, a seller can identify whether a buyer uses any algorithms. This helps detect large order opportunities and enables an investor to have a successful trade by filling the orders at a higher rate. 

Algorithmic trading strategies: examples

Although there are numerous algo-trading techniques, this article covers the most uncommon ones. You can find more strategies here.

1. Dollar-cost averaging 

This approach can be easily implemented in algorithmic trading. The idea is to invest a fixed amount of capital in a certain asset periodically. It’s one of the most effective long-term investing approaches. The logic is that price fluctuations may allow you to buy the asset cheaper than if you were to invest the whole amount at once. 

2. Rebalancing of an index fund 

There are defined periods when index funds rebalance their holdings to par with their respective benchmark indices. The rebalancing offers opportunities for algorithmic traders, who capitalize on expected trades. The rewards depend on the number of stocks in the fund before the rebalancing. Algorithmic trading allows executing trades on time and for the best prices.

Final thoughts

Algorithmic trading is an effective tool that allows an investor to save time, avoid mistakes caused by emotions, and multiply the number of trades. However, to apply an algo-strategy to your trades, you should develop a reliable strategy manually. Remember that any trading approach should be customized according to your goals, investment approach, amount of funds, and the asset you trade. 

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