What are the Most Popular Algo Trading Strategies?

In today's dynamic financial landscape, investing and trading have become increasingly accessible. You can now participate in financial markets even with a modest capital. Trading— the strategic buying and selling of stocks, derivatives (futures & options), commodities, and other assets— offers a potential path to making an extra income. Today, traders have two choices: trade manually or deploy algo trading strategies. Let us explain… 

Manual trading is the traditional method where trades are completely executed based on human instincts and strategies. Meanwhile, algo trading is a method of executing orders in the financial markets using automated or pre-defined trading instructions. The 'algorithm' places orders based on specific rules and criteria, including price, timing, and quantity instructions

You can choose either method based on your trading goals and expected outcomes.

Also read: Manual Trading vs Algo Trading: Which is Better?

A trading strategy is a baseline for any method, and in this article, we will explore the popular algo trading strategies used in the Indian markets. We will give an overview of the different strategies, their advantages, disadvantages, and characteristics.

What are Algo Trading Strategies?

Trading strategies are systematic approaches used by traders (or investors) to buy and sell financial instruments. They're essentially plans that guide decision-making in the market based on pre-defined criteria. These strategies typically aim to maximise profits while managing risk. The first and most important step in algo trading is to create or develop a trading strategy (or select/deploy strategies crafted by experts). 

Here’s a Simple Example:

One effective strategy in stock trading is using the Simple Moving Average (SMA) crossover. [SMA is a technical indicator which calculates the average of selected prices, usually closing prices, by the number of periods in that range.] This involves tracking two different SMAs, such as the 50-day and 200-day SMAs, to identify potential buy and sell signals. Calculating and monitoring these averages manually can be challenging and time-consuming. So you can easily convert it into an algo trading strategy!

For example, if you wish to trade in 'Reliance' stock, you can use an algorithm to calculate its 50-day and 200-day SMAs. You can set a condition to trigger a buy signal when the 50-day SMA crosses above the 200-day SMA. Similarly, the algo can trigger a sell signal if the 50-day SMA falls below the 200-day SMA. This automated approach makes it easier to capitalise on this strategy without the hassle of manual calculations.

Such algo trading strategies will help traders execute emotion-free trades. It will help reduce human error, thereby reducing losses.

A reliable strategy will help in managing risk by limiting position sizing and defining entry & exit points. Traders with a strong strategy can monitor their performance and modify it whenever necessary. You can develop your own strategies or choose pre-defined strategies from algo trading platforms based on your analysis, goals, and objectives. If you are curious about such strategies, don't worry, let's dive into some of the popular ones used across the globe!

Popular Algo Trading Strategies:

Mean Reversion Strategy

In this strategy, trades are initiated/executed when asset prices are at extremes and later exited when prices restore to the mean (average price). It’s based on the idea that asset prices and other market indicators tend to fluctuate around a long-term average or "mean" value.

• This is a preferred strategy to implement if prices fluctuate in extremes for a prolonged period.  When prices reach these extreme levels (either high or low), traders initiate their positions:
  
  - If prices are extremely high, they might sell (short).
  - If prices are extremely low, they might buy (long).

• Traders generally execute quick trades in short timeframes, as a result of the high frequency of entry and exit points. They aim to close their positions when prices move back towards the average.

• Equity curves of mean reversion strategies usually show quick profitable trades followed by occasional larger losses. However, this is mainly due to the reliance on temporary price deviation from previous averages. [Also known as “profit and loss“ curves, equity curves are the graphical representation of change in value over time.]

• For timing mean reversion entries, market timing tools like standard deviation, local price averages, and moving averages are essential. [moving average is calculated based on the mean of a given set of prices over a period of time.]

• For instance, consider the simple moving average of IRFC is ₹174 and its extremes are ₹192, and ₹112. If the price moves to ₹110, the algorithms buy it hoping it will go back to its average of ₹174. After buying at ₹110, the stock goes back to its moving average. Traders can close a profit in this case. Similarly, if the stock price goes above the upper limit, the algorithm exits and bounces a profit for the trader. 

Trend-Following Strategy

This involves booking profits by following the trends and market movements. There are three main types of trends in the stock market: uptrend (when the asset price is rising in value), downtrend (when price is decreasing), and sideways trend (when price remains static/in a range).

• Traders must design the algorithm to analyse the price movements over a particular period according to their strategy and goals to book maximum profits. 

• Traders use technical indicators like moving averages, Bollinger bands, and Ichimoku cloud to identify trend patterns.
  
• It’s very important to have a risk management strategy as this method of trading has a low win ratio. [Win ratio is a metric to track the trader's success. It is calculated by dividing total winning trades by total number of trades x 100.]
  
• To illustrate, from January 11, 2024, a trend began where the railway sector’s stocks like IRFC, RVNL, IRCTC, and RCON surged. Many traders used this strategy to book maximum profits. 

Expand Your Knowledge

📍Bollinger bands consist of 3 bands middle, upper, and lower. The middle band is the 20-day moving average. The upper band is the sum of twice the standard deviation of the price to the moving average. The lower band is the difference of twice the standard deviation to the moving average.

📍Ichimoku cloud consists of 5 lines where each line represents support, trend direction, resistance levels, potential trading signals, and momentum. The cloud (moku) consists of current and historical price action.

Advanced Algo Trading Strategies:

HFT Strategy

High-frequency trading (HFT) involves algorithms to execute orders in very large volumes in high-speed time instances, usually in a fraction of a second. This requires advanced tech, high-speed internet connections, risk management, and regulatory compliance.

• Most retail traders can’t execute an HFT strategy due to its high costs and high speed and frequency infrastructure requirements.

• Traders exploit market inefficiencies for profit by using HFT strategies like statistical arbitrage, news-based trading, and momentum trading.
  
• HFT is controversial due to its practices causing flash crashes, market volatility, or disturbing market stability. 
  
• Retailers should be cautious of the risks of HFT, such as market volatility, market manipulation, and potential exploitation.

Expand Your Knowledge

📍Statistical arbitrage trading:  This strategy involves the use of statistical models to identify and exploit price fluctuations between related financial instruments or assets.

📍News-based trading: Traders create these algorithms to act instantaneously based on the latest news and announcements that may impact the prices in the market.

📌 Momentum trading: Algorithms analyse and execute trades based on short-term momentum trends in the market.

Arbitrage Strategy

The arbitrage strategy involves buying an asset at a lower price and selling it at higher prices in different exchanges/markets. Stock markets, foreign exchanges, commodity markets, and options markets. Traders use price discrepancy as an advantage to make profits.

• The profitability of arbitrage trades depends on transaction fees impacting the overall potential profits. [Transaction fees are the charges imposed on traders to cover the operational costs faced by brokerage firms etc]

• Traders make informed decisions by using APIs for real-time data collection. [API or Application Programming Interface is software used to access real-time data and execute trades on various trading platforms or exchanges.] 

• Decisions made on the chain of trade based on price differences between exchanges are crucial to maximise profits.  

• For example, consider 2 exchanges NSE and BSE, where the trading value of 1 HDFC stock is  ₹2,400 in NSE and  ₹2,430 in BSE. Then the algorithm executes buy trades of HDFC stocks from NSE and sells them in BSE, making a profit of  ₹30 per stock (excluding transaction fees). 

Why is it difficult to deploy?

Unfortunately, an arbitrage strategy is very difficult to deploy and implement due to the need to identify small price changes quickly, handle transaction fees, and meet technological requirements. Along with that rapid price fluctuations and market volatility require an infrastructure to execute precise trades.

How the 9:20 AM Straddle Strategy Popularised Algo Trading in India:

Over the past few years, the 9:20 AM Staddle strategy has gained traction in India due to its appeal of potentially generating consistent returns by capitalising on early volatility in Indian indices (particularly Bank Nifty). This strategy involves selling both call and put options at the same strike price and expiration date at or around 9:20 AM (shortly after the market opens at 9:15 AM) with pre-defined stop losses.

• As per the strategy, orders must get executed at 9:20 AM, allowing for some initial market volatility to settle after the opening bell.
• Generally uses at-the-money (ATM) or near-the-money options for both calls and puts.
• This strategy does well in consolidating and directional markets as well. You may incur losses if you execute the strategy on volatile days with V and W-shaped moves.
• Positions are usually closed within the same trading day (they are held for a short term).
• Often implemented using algo trading systems for precise execution.

The 9:20 AM strategy served as an entry point for many retail traders into the world of algo trading in India as it has a defined entry & exit time, along with stop-loss parameters. While its effectiveness may have diminished over time due to increased adoption, it played a significant role in popularising algo trading among retail traders in the Indian market.

Click here to watch an explainer of the strategy.

Conclusion

Algo trading has shown its potential to build a successful portfolio for traders. These algorithms provide a systematic structure and unique approach to identifying market trends, managing risks, and executing trades with the highest possible accuracy. Although some strategies like HFT are more suitable for institutional traders, retail traders (individuals) can follow a simple trend-following strategy.

The world of algo trading is constantly evolving every day giving infinite opportunities for traders to create and experiment their strategies. However, despite the strategy chosen, the success rate depends on the trader's skill, rigorous backtesting, risk management techniques, and constant modification to optimise them in the ever-changing world of financial markets.