The ABCs of Algorithmic Trading
Algorithmic trading, also known as algo trading, occurs when computer algorithms—not humans—execute trades based on pre-determined rules. Think of it as a team of automated trading systems that never sleep, endlessly analyzing market trends and making trades in the blink of an eye.

The algorithms can be trained to manage all sorts of trading. Quick trading and highly liquid markets can make this tool more effective, so it is more commonly seen in fast-moving markets such as stocks, foreign exchange, cryptocurrencies, and derivatives. Low or nonexistent transaction fees make it easier to turn a profit with rapid, automatically executed trades, so the algorithms are typically aimed at low-cost opportunities. However, a tweak here and there can adapt the same trading algorithms to slower-moving markets such as bonds or real estate contracts, too (Those quick-thinking computers get around).

Over time, these systems have grown increasingly sophisticated, utilizing artificial intelligence (AI) techniques like machine learning and deep learning. Some even use large language models (LLMs) similar to OpenAI’s ChatGPT, analyzing financial news and social media chatter to make trading decisions. Taking advantage of a more detailed set of real-world variables can make the algorithm more effective, at least in theory.

Most algorithms employ some sort of quantitative analysis, executing trades when the asset’s trading follows a certain pattern. It’s useful to give the computer access to some very deep pockets, to the point where its automatically executed trades can control the real-time price action to some degree. Even without that price-moving advantage, the millisecond reaction time of a computerized trader can turn a profit even from a relatively quiet market with little price movement.

The Relevance for Buy-and-Hold Investors in India
As buy-and-hold investors, we might wonder why we need to understand the lightning-fast world of algorithmic trading. Successful long-term investing is better served by patience, foresight, and staying the course, right?

Well, even from a view on the sidelines, you should know how algorithmic trading influences the Indian markets. These algorithms can affect stock prices and market volatility, creating ripples that eventually touch our portfolios.

However, it’s important to remember that these trading algorithms are designed for the financial equivalent of bullet chess, with one hand on the clock and where fractions of a second mark the difference between winners and losers. That’s not the slow and steady investing game we humans are used to, and not necessarily one we should attempt to emulate.

Proceed with Caution, Dear Investor
Should you be tempted to dip your toes into the world of algo trading? As a seasoned long-term investor, I would advise caution. Algo trading, especially the kind driven by advanced AI, is a complex field that requires a unique set of skills in programming, data analysis, and finance.

The fast pace of algo trading could lead to quick gains—but remember that rapid losses can pile up just as swiftly, especially in volatile market conditions. For us, it might be like trying to sprint in a marathon. You’re looking at exhaustion and potential injury (financially speaking) more quickly than sticking with a slow and steady pace.

You and I are not computerized hares, moving more like the inexorable tortoise of Aesop’s classic fable. And there is nothing wrong with that since a more methodical approach suits human investors better. Warren Buffett made his billions without leaning on digital high-speed trades. Algorithmic trading funds like Citadel and Renaissance Technologies may have made multibillionaires out of Jim Simons and Ken Griffin, but even they can’t hold a candle to Buffett’s more methodical wealth-building acumen.

An Inside Look at Algorithmic Trading in India
To understand how a quantitative stock fund uses algorithmic trading, let’s imagine a situation with a fictional stock called the Indian Electronics Corporation, which has the ticker “INDIAE.”

Our quant fund has developed a complex model trained on vast amounts of historical market data. This model predicts, with a certain degree of probability, that when the trading volume of INDIAE shares crosses a certain threshold with positive price momentum, the price is likely to rise significantly in the next few minutes before it corrects back down. That’s how the stock has behaved many times in the past, and it looks likely to do it again, and again, and again—maybe many times in a single day or even in a five-minute span. INDIAE is a volatile little ticker!

One fine Monday morning, as the opening bell rings on the Bombay Stock Exchange (BSE), the fund’s trading algorithm, affectionately called “QuantBot,” springs into action. It monitors the trading volume of INDIAE, never taking its digital eye off the proverbial ball. At 10:03 AM, QuantBot notices that the trading volume of INDIAE starts to spike.

QuantBot quickly cross-checks the other criteria outlined in its model. The share price is moving upward, and a quick AI-powered sentiment analysis of social media posts about INDIAE shows increasing investor enthusiasm. All the stars align, and the algorithm decides to make its move. In fact, it doesn’t have a choice—this is exactly what the program was looking for!

Conclusion
Algorithmic trading has revolutionized the way trading is conducted, making it more efficient, systematic, and less prone to human errors. By leveraging predefined algorithms and real-time data, traders can achieve faster and more accurate execution of trades, ultimately enhancing their profitability and reducing risks.

As buy-and-hold investors in the Indian stock market, while we may not need to participate in algorithmic trading directly, understanding its impact on the markets can help us make more informed decisions and navigate the complexities of the modern financial landscape. Remember, while the fast-paced world of algo trading might be tempting, sticking to a methodical, long-term investment strategy is often the key to sustainable success.