Algo Trading Strategies Explained: Trend-Following, Mean Reversion and Arbitrage

Key Takeaways

1. Algo trading strategies generally fall into three broad types: trend-following, mean reversion and arbitrage.
2. Trend-following strategies aim to trade in the direction of an existing price trend, while mean reversion strategies look for prices to move back towards an average.
3. Arbitrage strategies look for price differences between related markets or instruments, but trading costs and execution delays can affect potential gains.
4. Each strategy has its own risks and may perform differently under changing market conditions. Algorithmic trading does not guarantee profits.
5. Retail algo trading in India must follow SEBI’s framework and applicable broker and stock-exchange requirements.

Every algo follows a set of rules. But what logic sits behind them? Before you use any algo, it helps to know which family of algo trading strategies it belongs to.

Algorithmic trading uses a computer program to generate or place orders when predefined conditions are met. The program follows the rules built  into it, but its results also depend on market conditions, data quality and order execution. These rules may be based on one of the  three broad ideas: follow the trend, expect a return to the average, or capture a price gap.

Through this blog, you can understand how trend-following, mean reversion and arbitrage work, where each one fits, and what risks a trader should keep in mind.

What Are Algo Trading Strategies?

Algo trading strategies are pre-defined rules that decide when to buy, sell and exit, based on price, time, volume or the link between two instruments.

Once coded and activated, an algo can generate or place orders when its conditions are met, depending on how it is designed. This reduces the need for manual order placement, but the strategy still needs to be monitored and reviewed.

In India, algorithmic trading for retail traders must follow SEBI’s framework and the applicable stock-exchange requirements. As per SEBI's circular on safer participation of retail investors in algorithmic trading, dated February 4, 2025, algos require  broker involvement, need exchange approval and carry a unique identifier for each algo order.

Trend-Following Strategy

A trend-following strategy assumes that a price moving strongly in one direction is likely to keep moving that way for some time. The algo enters after the trend shows up and exits when it weakens.

Common rules used in trend-following:

• Moving average crossover: A strategy may generate a buy signal when a short-term moving average crosses above a long-term moving average. A cross below may signal an exit or a sell trade, depending on the strategy rules.
• Breakout: Buy when the price moves above a recent high, or sell when it falls below a recent low.
• Momentum filters: Indicators such as ADX can help assess the strength of a trend. Other rules or indicators may be used to identify its direction.

Where it struggles: In a sideways market, prices keep crossing the moving averages back and forth. This can trigger many small losing trades, often called whipsaws.

Mean Reversion Strategy

Mean reversion works on the opposite idea. When a price moves too far from its average, it is expected to come back closer to it.

Common rules used in mean reversion:

• Bollinger Bands: A strategy may look for buying opportunities when the price approaches the lower band and selling or exit opportunities near the upper band. These signals need to be assessed under the strategy’s rules because the price can continue moving beyond either band.
• RSI levels: A strategy may use an oversold RSI reading as a potential buy signal and an overbought reading as a potential sell or exit signal. These readings do not guarantee a price reversal.
• Pairs trading: Track two related stocks whose prices have historically moved in a similar pattern. If the gap between them moves outside its usual range, a strategy may buy one and sell the other, expecting the gap to narrow. The relationship may change, so the gap may not return to its previous range.

Where it struggles: If a stock keeps falling because of a real change, such as weak results, the price may not return to its old average. Without a stop-loss, losses may grow.

Arbitrage Strategy

Arbitrage strategies look for price differences between the same or related instruments in different markets or contracts. They aim to benefit from these differences, but execution delays, trading costs and changes in prices can affect the outcome.

Common types of arbitrage:

• Cash-futures arbitrage: Buy a stock in the cash market and sell its futures when the futures price is sufficiently above the cash price to account for applicable costs. The two prices generally converge as the futures contract approaches expiry, but costs and execution affect the result.
• Inter-exchange arbitrage: Identify a price difference for the same stock on NSE and BSE. A strategy may buy on the exchange quoting the lower price and sell on the one quoting the higher price, subject to execution, liquidity and applicable costs.
• Statistical arbitrage: Use data models to spot pricing gaps across a group of related stocks.

Where it struggles: Price gaps can narrow or disappear before the orders are executed, and some may persist or widen. Brokerage, taxes and slippage can reduce the potential gain or turn it into a loss.

Here's a simple way to compare the three:

How to Choose Between These Algo Trading Strategies

The choice depends on a few practical factors:

• Market state: Trend-following strategies are designed to respond to sustained price moves, while mean reversion strategies look for prices or spreads to move back towards an average. Neither approach works in every market condition.
• Capital: The capital required depends on the instruments traded, position size, margin requirements and transaction costs. Arbitrage strategies may need substantial capital when the potential gain per trade is small.
• Time frame: The holding period depends on the strategy. Some arbitrage opportunities may last only briefly, while trend-following strategies can operate over intraday or longer periods.
• Cost: Strategies with frequent trades are more sensitive to brokerage, taxes and slippage.

Many traders backtest and paper trade a strategy before using real money to see how it behaves across market phases. However, backtesting and paper trading cannot guarantee future results. 

Common Doubts About Algorithmic Trading Strategies

Can one algo use more than one strategy?

Yes. Some algos switch between approaches based on market conditions, which adds complexity.

Is arbitrage risk-free?

No. Arbitrage carries execution risk, cost risk and the risk of the price gap not closing as expected.

Do algo trading strategies guarantee profits?

No. Algorithmic trading only automates a set of rules. If the rules do not suit the market, the algo can still make losses.

How mastertrust Helps With Algorithmic Trading

mastertrust offers a trading and demat account on mastertrust.co.in for trading in Stocks, F&O and Commodity, along with resources for algorithmic trading. 

If you are new to automation, you can learn how to develop your first algo trading strategy and how to paper trade your algo strategy before going live.

Before deploying an algo, check the applicable broker and exchange requirements, including any approval or registration requirements for your strategy.

Final Thoughts

Trend-following rides momentum, mean reversion trades the pullback, and arbitrage chases small price gaps.

Knowing which family your algo belongs to helps you judge when it may struggle and how much risk it carries.

Frequently Asked Questions (FAQ)

1. What are the main types of algo trading strategies?

The three main types are trend-following, mean reversion and arbitrage. Most other strategies are variations or combinations of these.

2. Which strategy is suitable for beginners?

Moving average crossover rules are one example of a strategy that beginners can learn about. Before using one with real money, understand its entry and exit rules, test it across different market conditions, and account for trading costs and potential losses.

3. Is algorithmic trading legal for retail traders in India?

Yes. Retail investors can participate in algorithmic trading in India through arrangements that comply with SEBI’s framework and the applicable stock-exchange requirements. These requirements depend on the type of algo and how it is accessed.

4. What is the biggest risk in mean reversion?

The price may keep moving away from its average because of a real change in the stock, leading to larger losses without a stop-loss.

5. Why does arbitrage need low costs?

The profit on each arbitrage trade is small. Brokerage, taxes and slippage can easily wipe it out.

6. Can I trade algo strategies in F&O through mastertrust?

You can trade Stocks, F&O and Commodity through a mastertrust account. Check the platform and exchange rules applicable to the algo you plan to use.