What is Algorithmic Trading: Is it Legal, Profitable or Fails? (2024)

The stock market is one of the highly volatile trading platforms where millions of transactions take place within a fraction of a second.

Share of different companies from different industries is bought and sold by investors or traders manually to generate profits and minimize their losses.

Before the technology was not developed enough, most of the trades were executed manually by humans, which was taking little time to execute and complete the transaction.

Now, automation is taking place everywhere. A stock market is a place that has been used with the help of computer programming that is making the trades automated at faster speed and better accuracy compare to humans.

Algorithmic trading is the invention of such needs that uses a computer program to follow a defined set of instructions to place a trade.

Algo-trading also known as, algorithmic trading, automated trading or black-box trading is simply computer-generated programming used to carry out market orders while following the pre-defined set of rules and instructions based on stock price, timing, quantity, volume and other parameters to execute the buy or sell orders at a faster speed.

Automated stock trading can execute multiple types of transactions at a time at very high frequency and can generate a huge amount of profits compared to humans.

Algorithmic trading takes place with the help of complex formulas, combined with mathematical tools and techniques along with human oversight, to make the final decisions for buying or selling the stocks, cryptocurrencies and other financial instruments traded on the stock exchanges.

Stock market algorithms are developed by human brains using coding to instruct the computer system to make decisions and take actions accordingly.

Algorithmic trading keeps human emotions out of the trade, instead, follows only strategies formulated through a pre-defined set of rules in the algorithms.

The most common trading strategies are trend-following strategies, volume-weighted average price arbitraging and index fund rebalancing.

The most important factor behind using algorithmic trading in the stock market is the use of the right strategy at the right time that is well-tested before successfully and given the returns as per the expectations.

Once the strategy is developed, it is used in the algorithm to develop the automated program and then authenticated by the exchange to use it in the market.

To better know how algorithmic trading works in the stock market let’s take an example. Suppose you want to set the criteria of buying the XYZ Company’s 100 shares when the price reached Rs 500 and selling shares when the price goes above Rs 550.

In another case, if you want to sell 100 shares of XYZ Company if its 20-day moving average goes below the mark of 200 or buy 100 shares of a company when its 100-day moving average moves beyond the 200-day moving average.

Or you are looking to buy 100 shares of XYZ Company if it goes above Rs 150 before the market closes.

While considering all such factors if want to execute this transaction manually, you have to stick on your computer screen throughout the day and track the stock price and other parameters.

While if you have set all these instructions in a stock market algorithm software the orders will be executed automatically when such parameters meet in the system.

While discussing this topic a question arises is algorithmic trading profitable?

The answer is if your algorithmic strategy is effective and fully tested in the market or you are using the right strategy at the right time on the right stock you will generate profits.

Though it is hard to define how much profit can be gained comparatively you will get better returns.

However, the quantity of profits totally depends on the success of strategy, implementation and efficiency in executing the trades.

Therefore algo traders use multiple forms of algorithmic trading strategies to generate small profits even at taking advantage of small pricing discrepancies of stock traded at the different stock exchanges and earn from 2% to 5%.

Using the stock trading algorithm software huge quantity of trades are executed during market hours to generate profits.

This is also called high-frequency trading in which frequent turnover of small traders takes place and generates profits on every trade.

Hence, there is no doubt if deployed precisely, Algo trading gives handsome rewards. And there are few strategies if implemented rightly, that can give consistent returns with zero loss.

Though a high rate of returns is not possible when the volatility index (VIX) is also high it can give you assured returns with making your investment highly profitable in the long term.

And if such trades are done with large volumes and at high-frequency speed, you can generate a significant amount of money invested into the stock market using algorithmic stock trading strategies. This is also called quantitative trading in the stock market.

In India, Alog-based trading is introduced in 2008 with permission from SEBI, especially for institutional investors.

However, with the evolution of more advanced technology, it became more efficient and the door for Algo trading is also opened for retail investors.

Although, legalizing or algorithmic trading in a few countries is totally banned. But now with the time being developed in the field of artificial intelligence, the Algo developers are using machine learning for algorithmic trading software development.

You can say, it is a kind of AI-based robot that is developed with a certain algorithm to take situation-based actions automatically without human intervention.

It is legal but all the algorithm strategies must be authenticated by the exchange before implementation. And if stock market trading is done totally out of human emotions it may cause market instability.

Algorithmic Trading may cause Stock Market Instability

Some people believe the use of robots for stock trading can cause chaos or instability in the market.

Algorithm trading gives a signal or alert that might be considered insider trading, especially if others benefit from their information earlier or the market is inappropriately influenced. However, most of the algorithmic are legal but insider trading is a crime.

Though, computers perform better than humans with zero errors and do not become tired. But every technology-based system has drawbacks and hurdles. Similarly, algorithm trading sometimes also fails in the stock market and not gives the expected returns.

There are many reasons why Algo trading fails like the algorithm strategy is not being tested properly before the implementation. Or accurate data is not used to develop the stock trading algorithm software that fails to give profits to traders, let’s find out more.

Inaccurate or Insufficient Data

While developing such AI-based models a huge amount of historical data is used to train the model through a machine learning algorithm.

If data is not accurate the strategy will not work properly causing unexpected transactions or huge losses in the market.

Lack of Technical Knowledge

While developing such robots for stock trading, knowledge of complex programming languages like C+. C++, Java and Python etc require. And finance analysts or experts may not be familiar with such technical jargon and skills.

Technical Faults

Similarly due to unexpected technical glitches or system faults sometimes Algo trading fails. Computer-related technical faults or errors can come anytime, anywhere without any warning. And they can cause major kinds of system failures.

Lack of Resources

To implement such high-frequency trading strategies, you need well-equipped infrastructure that can support the Algo software speed, data storage, networking and complexities of strategy while performing the buy or sell transactions.

Inefficiency in such resources can lead to the failure of the Algorithm strategy costing you unexpectedly.

Summing-up

Algorithmic trading no doubt is bringing the evolution of huge volume in the stock market. It has reduced human costs due to automated trading systems.

Since the stock exchanges allowed Algo trading, most of the broking houses or institutional financial institutions are now using automated stock trading systems and generating profits for their customers.

If the right AI algorithm for stock trading is used while developing algo trading software it can give the best returns compared to a human-operated manual trading system.

And if the right strategy is applied right time as per the market conditions it can give the best returns in intraday trading. The strategies changed as per the trends in the stock market or stocks.

This article was originally published on moneysukh.com