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Algorithmic Trading, May 8, 2024

Common Strategies Used in Algorithmic Trading

Explore common strategies employed in algorithmic trading, including trading range (mean reversion), Volume-Weighted Average Price (VWAP), etc. Let’s discuss how these strategies are used in algorithmic trading.

In today’s fast paced world, we all are trying to do something extraordinary with the limited available time. However, not each one of us is able to do so. In the last few years, there has been a lot of talk about algo trading, investing in the stock market and other such subsidiaries. 

The only problem here is that not all of us are aware of all the required information, tactics, strategies, and other necessary information. Hence, we often lay back on the investment and let it slide by. On the other hand, the algo trading industry has been revolutionizing itself in order to offer the users with better opportunities. 

In recent years, since algo trading platform has made a lot of buzz, there is still some ambiguity around the topic. With this blog here, we are going to discuss some of the most common strategies that are used in algorithmic trading India and other parts of the world as well. 

Understanding Algo Trading Basics

There are various synonyms used for algo trading such as algorithmic trading, black-box trading, or automated trading. In general it uses a computer based program that can place a trade based on a set of mathematical functions or algorithms. Hence, the name. 

This trade is said to generate profits at a frequency which a human cannot possibly execute and obtain. These mathematical functions or defined sets are based on different information such as price, quantity, timing, or any other contributing factors. 

Keeping all this under consideration various algo trading software or algo trading platform are being developed which can function better as they eliminate human emotions. Here are a few more benefits of integrating auto algo trading: 

  • Trades are executed at the best price possible for maximum profit
  • Limits the transaction costs
  • Better decision making based on given information and facts
  • Reduces the chance of human error and offers better results
  • It also offers you backtesting which leverages historical trading data to check the viability of the trading strategy being implemented 
  • Keeps a check on different market conditions 
  • Timely trades are executed to avoid any significant price difference. 

Commonly Used Auto Algo Trading Strategies

As we have already mentioned above, every algo trading platform or algo trading software functions based on certain strategies which helps in better functionality. Here are some of the most commonly used strategies:  

  • Mathematical Model-Based

It involves different mathematical models such as the Delta-Neutral Trading strategy. This strategy allows the traders to trade on a combination of options and underlying securities. In general Delta Neutral is a portfolio strategy which consists of various positions having offset positive and negative deltas in a comparing ratio. 

This comparing ratio consists of variation in the price of an asset to the change in the price of its underlying derivative. This results in an overall delta of the asset in a total zero. 

  • Trading Range (Mean Reversion)

The Mean Reversion strategy of algo trading is based on the concept stating: low and high prices of any assets are temporary which reverts to their average or mean value periodically. To implement an algorithm based on identifying and defining the price can allow placing the trades automatically, leveraging the algorithm based strategies. 

It further consists of placing trades automatically when the price of the asset is higher or lower than its defined range for maximum benefit. 

  • Volume-Weighted Average Price (VWAP)

The VWAP strategy divides a large order into smaller orders and releases these dynamically determined small orders to the market. This is done by leveraging the stock-specific historical volume profiles. 

With this strategy the aim is to place the order and execute the algo trading which is close to the volume-weighted average price of the asset. 

  • Time-Weighted Average Price (TWAP)

Similar to VWAP, this approach also breaks the larger order into smaller orders and releases them in the market on evenly distributed time slots starting from the opening to the closing time of the market. 

This allows them to execute the order which is close to the average price between the starting and ending times and reduces the market impact. 

  • Percentage of Volume (PoV)

Under this approach, partial orders are being sent by the time the trade order is not fulfilled completely. This is done by defining the participation ratio and the trade volumes in the markets. 

Further implementing the “step strategy” it sends an order with a user-defined percentage of market volume and this can increase or decrease the participation rate as well. This increase or decrease can also impact the participation rate when the price reaches at a fixed user-defined level.

  • Implementation Shortfall 

This strategy of auto algo trading aims to minimize the execution cost of any order by enabling trading off in the real-time market. This helps to save cost on the order and offers benefit from delayed execution. 

This further increases the participation rate when the stock price changes in favor and decreases the participation rate when the stock price is moving in the other direction.

  • Index Fund Rebalancing

With this process index funds have a set or defined time period of rebalancing which can bring their holdings to par with their respective benchmark indices. This process creates a set of profitable opportunities for all algo trading users or traders who can further capitalize on expected trades offering 20-80 points profit. This amount of profit point further depends on the number of stocks in the index fund prior to index fund rebalancing.

These trades are usually initiated via different algo trading platform or algo trading software systems which ensures timely execution with best possible prices.  

From the above mentioned algo trading strategies, one can benefit using different algo trading platform. One  such auto algo trading platform is Bhaav. This platform with the help of set and defined algorithms and AI integration helps you to place the trade without having to worry about all the market factors and obtaining every inch of knowledge. 

Concluding Points

With an auto algo trading platform like Bhaav it has become quite convenient and easy to place the trading and generate profit. As this platform allows you to set a fixed risk level, based on which all the trade orders are being placed for maximum benefit. 

If you are someone who is interested in algo trading but don’t have enough time, experience or expertise, Bhaav is the right platform for you. Here we do all the work for you, and you get to relax in the meantime. For more information get in touch with our experts today or download our app and get started with trading. 


1. How does algorithmic trading work?

Algo trading works by leveraging mathematical data or strategies based on computer algorithms to place the trade orders in the market with required information and date of the market trends. 

2. What are some common algorithmic trading strategies?

Some of the common algorithmic trading strategies are: Index Fund Rebalancing, Percentage of Volume, Trading Range, and Implementation Shortfall. 

3. How can I get started with algorithmic trading?

Download our app today and get started with your algo trading today.