Fri. Apr 12th, 2024
Algorithmic trading

Algorithmic trading has been around for decades, but it has grown rapidly in recent years. The future of algorithmic trading is expected to be growing even stronger.

Algorithmic trading strategies are changing the way the financial market operates. Financial markets have benefited greatly from the technological advancements and algorithmic trading strategies of the past two decades. With the increased trading volumes and client expectations, trading desks are under pressure to improve execution performance. To handle a wide range of flows, traders are using algorithms and automation. 

According to a report by Market Research Future (MRFR), “Algorithmic Trading Market Size Is Anticipated To Grow At CAGR of 13.1% by 2030”.

How did it all begin? Let’s rewind a little!

History of Algorithmic trading

The computerization in the financial markets for placing and executing orders started in the early 1970s when the New York Stock Exchange introduced the first electronic order system – Designated order turnaround (DOT). The exchange floor specialists were able to fulfill orders sent by investors from faraway places.

Later in 1984, the NASDAQ exchange also released its own electronic trading system called “Small Order Execution System (SOES).” This system allowed up to 1000 shares to be automatically executed.

Another encouragement to the financial market came in 2001 when IBM research published an article “International Joint Conference on Artificial Intelligence”, which states that – “Experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM’s own MGD, and Hewlett-Packard’s ZIP) could consistently outperform human traders.”

Over time, technological advancements with the adoption of modern approaches by investment banks, mutual funds, pension funds, and hedge funds brought huge success.

Fast forward to a few facts – In 2018, algorithmic trading contributed to nearly 60-73% of all U.S. equity trading and 50% in the Indian financial market. Leading 12 investment banks earned about $2 billion from the portfolio and algorithmic trading in 2020, according to Coalition Greenwich.

Future of Algorithmic trading

Algorithmic trading is a way of executing trades automatically on a stock exchange based on predefined criteria and without any human intervention.

According to Nasdaq, “This is a big advantage of algorithmic trading. Human traders may make irrational decisions influenced by their emotions, especially fear and greed. Algo trading forces trades to take place within a predetermined set of criteria.”

There are many different types of algorithmic trading strategies. These are often classified as either high-frequency trading or low-frequency trading. High-frequency strategies rely on speed and scalability in order to make profits from small price movements in the market. Low-frequency strategies use a longer time frame to make trades based on fundamental data and company performance.

In today’s market, the challenge is how to make better use of the available trading strategies, execution processes, and algorithms that may be unfamiliar to traders. Algorithmic trading because it requires constant tuning and periodic changes in trading infrastructure.

As algorithms become more focused on specific instruments, market conditions, and available credit, traders and clients will be more trusting of algo providers, opening a world of opportunities for performance improvement. By incorporating automation and machine learning, it may become possible to manage orders and execute them seamlessly.

Artificial Intelligence (AI) and Machine Learning (ML) in algorithmic trading is a new wave of technology that will change the way we trade. In the future, algorithms will be able to provide more intelligent decisions than simple benchmark-based algorithms, helping traders achieve the best outcomes by suggesting specific settings and parameters based on historical data.

According to a 2019-study by Institutional Investor “4 of 5 participants expected AI/machine learning to be fully integrated into the trading process by 2024. Only 44% were using it at the time of the study, while 17% said they planned to use it within two years.”

Artificial intelligence is estimated to contribute $15.7 trillion to the global economy by 2030 – Research by PwC showed that consumer demand stimulated by product enhancements through AI will contribute 45% of total economic gains. This will mean a boost of 26% and 14.5% to the Chinese and North American GDPs respectively. 

The bottom line is that you must stay on top of the latest technologies and strategies if you want to stay competitive and earn profits. But what skill do you need in algorithmic trading? Let’s understand.

Start your Algorithmic Trading Journey

The future of algorithmic trading is bright, with new opportunities emerging every day. The key to success with algorithmic trading is to find the right strategy and then automate it so it can be applied at scale. 

Listed below are a few tips that will help you become a successful algorithmic trader:

  • Have sound knowledge of the Financial market
  • Code your own strategy
  • Backtest your strategy using historical/current data
  • Optimize parameters
  • Choose the right broker
  • Manage your risks
  • Keep optimizing and tweaking your strategy for performing well
  • Keep learning and developing new skills


Algorithmic trading is not just a tool for traders, but also a way for companies to manage their cash flow and optimize their capital allocation strategy by investing in better opportunities at the right time.

The future of algorithmic trading is set to be shaped by key themes and trends set to emerge in 2022. This is pushing the boundaries of trading across the globe. There is a race to gain a competitive edge in trading, and algorithmic trading can help you achieve that.

Algorithms are the future. This is the next phase of trading’s evolution. The most comprehensive Algorithmic Trading course is the Executive Programme in Algorithmic Trading (EPAT) by QuantInsti if you wish to learn about various aspects of algorithmic trading. This course equips you with the required skill sets to be a successful trader.

By Manish