Analytics in real life: Algo Trading

Written by Maavrus

September 12, 2022

Algo Trading

What is Algo Trading?

Algo trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. It is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to.

Algo Trading

A couple of weeks ago we wrote on the subject of technical analysis. If you had read that blog you would have gotten a glimpse of how some of the key technical indicators are used in the stock market.

So one of the challenges that would come to mind reading about all the technical indicators is how one identifies trends across thousands of stocks across different time frames to make any decision. This challenge is solved by what is called algorithmic trading or Algo Trading more commonly. 

Going to the basics first algorithms are “a procedure for solving a mathematical problem (as of finding the greatest common divisor) in a finite number of steps that frequently involves repetition of an operation” (Mariam-Webster).

How does Algo Trading work?

In our personal experience, Algo Trading is based on 3 key elements- strategy planning, screeners, and backtesting strategy implementation.

Let’s start with strategy planning- strategy planning is based on identifying stocks on indices that show a specific behavior, the most common strategy categories like- trend following, price action, swing trading, mean reversion, pivot points, and many more.

Algorithmic trading

Once you have identified the category of strategies then we will look at some of the strategies under that category. Let us use the trend following strategy as that is the one most commonly used- some of the strategies under trends following are breakout with volume, weak downtrend with OI, uptrend resistance breakout, etc. 

Once the strategies are formed we move to the next level- run a screen on how many stocks are showing this trend-this process is called scanner/screening. Once we identify all the stocks that are following trends we do one of the toughest tests historical efficiency of the strategy- historically backtesting involved a lot of coding and crunching of data. This process has been increasingly solved by some of the platforms that allow visual input for backtesting. The backtest based on the period chosen tells you a lot of things about your strategy like below:

  • Number of possible trades
  • Net profit and loss
  • Win/loss ratio, win ratio, loss ratio
  • Average bar held
  • Max Drawdown

With back-testing, once we have established that the risk-reward ratio is favorable to our risk management preference we can go ahead and execute the strategy. While purely based on data these strategies will do wonders they are susceptible to events like new interest rate announcements, and black swan events like a covid breakout. In such cases, your risk management strategy can protect you against drastic fluctuations.

Algo Trading has seen a rampant rise across the world, especially in European and US markets. In Indian markets, they have been slow to pick up one due to regulatory setup that prohibits retailer traders from using API-based Algo, second due to intense coding requirements to run backtest. However, there have been many significant improvements in this area in India as well. There are really cool Algo Trading platforms that have gotten better with time allowing retail users to take a stab at Algo Trading.

One cannot help but be bullish about where Algo Trading is heading- this is another great example of how analytics is shaping the future in real life. Give it a try and ride the curve as an early adopter.

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