Let’s jump right in and answer the following questions—What is program trading? In simple words, program trading refers to a trading approach that uses computer-generated algorithms and a set of predefined instructions to trade large volumes of stocks. Often, the significant turnover volumes are coupled with high-frequency trades. The computer-generated algorithms for program trading are derived using mathematical models and quantitative analysis. Mathematical models and statistical analysis methods can also help code trading strategies into trading algorithms. These algorithms can identify patterns and trends in the markets. Algo trading, short for algorithmic trading, is a subset of program trading that takes automation to the next level by executing trades based on predefined algorithms without the need for manual intervention, allowing for rapid decision-making and precise market timing.
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Purpose of Program Trading
Thanks to computer-generated algorithms, program trading trades are automated; the trades are executed without human intervention. For example, as a program trader, you could code an algorithm to buy the 50 Nifty 50 stocks in a specified quantity in the first and last hours of the trading day. Because orders are placed simultaneously, programmed trades can help reduce risk. At the same time, these types of trades can also capitalise on market inefficiencies.
Program trading makes it possible for you to place trades and benefit from opportunities that are inaccessible to traders placing their trades manually. Hence, This trading approach is primarily adopted by hedge fund or mutual fund managers. They can use programme trading strategies to buy and sell multiple stocks at the same time. Likewise, these firms may also employ program trading strategies to execute trades every few months. The absence of intervening human emotion and erraticism results in a higher percentage of profitable trades.
Types of Program Trading
Moving on, let’s look at some prominent types of trading visible in today's financial markets.
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Principle trading: In this type of trading, the firm, like a brokerage house or an institutional investor, uses program trading strategies to buy a stock portfolio. The stock portfolio they buy likely replicates popular indexes like the Nifty 50 or Sensex; or may contain stocks from these popular indexes. They purchase the portfolio on their own account, as they believe that that will increase the portfolio's value. As the stocks do well, they attract the attention of retail investors. Then as retail investors start purchasing those stocks, the institutions sell their stock to fulfill retail orders. Apart from that, they may also earn a commission through brokerage on each trade.
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Agency Trading: Investment management firms that invest and trade for clients exclusively may adopt program trading strategies to buy stocks that fulfill the firm’s trading criteria. Once purchased, the shares are credited to the client's demat accounts. These investment management firms also use program trading strategies to rebalance investment portfolios. This is often observed in the case of passive funds that replicate popular indexes. For instance, a Nifty 50 index fund may use index rebalancing strategies to replicate the stock proportions of the index.
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Basis Trading: This program trading strategy revolves around capitalizing on price inefficiencies in the financial markets. Here, the investment firm may use program trading strategies to buy stocks they find undervalued and short stocks that are overvalued.
For example, after a swift rally in the banking sector due to substantial credit growth in the banking industry. However, these positive numbers cause all banking stocks to appreciate. That said, some banking stocks may still be undervalued, as the best is yet to come. On the other hand, in some banking stocks, the market is overestimating positive numbers. In the former case, the select stocks may still be overvalued; in the latter, the stocks are likely overvalued. So the traders may develop algorithms to find such opportunities.
Factors Facilitating Program Trading
Several factors have helped program trading grow over a period of time; let’s take a look at the major ones below.
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Technology: Advancements in technology have helped automate trading to a great extent. At the same time, technological advancements have also drastically reduced trading costs. Automation and lower trading costs have helped pave the way for program trading.
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Portfolio diversification: Investors view portfolio diversification as an effective measure to mitigate risk. Program trading has made it easier to diversify larger portfolios.
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Institutional investors: The increase in the number of institutional investors has led to the discovery of more efficient ways to trade securities. They strive to automate large trades, and therefore, most institutional investors rely on program trading.
Pros and Cons of Program Trading
So far, you may have got the impression that all is well with program trading. However, every trading method has its pros and cons, and program trading is no exception to the aforementioned statement. That said, let us first look at the pros of program trading in a structured manner before looking at the cons.
Pros
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Program trading relies on predefined instructions coded into computer algorithms to execute trades, which makes it possible to execute trades within microseconds.
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The instantaneous placement of orders allows the traders to capitalise on arbitrage opportunities and other trade opportunities that would not have been possible otherwise.
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Program trading allows the trader to trade multiple stocks or securities simultaneously; this feature proves to be very handy for institutional investors.
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Lastly, as a computer performs the trade, no human emotions are involved that could lead to fear or greed, resulting in trading indiscipline. The absence of these factors makes this trading more profitable, as the predetermined strategy is the core focus.
Cons
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Although it is much faster and has a higher success rate than manual trading, using computer-generated algorithms doesn’t ensure a 100% success rate.
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Some market participants and organisations have criticised this approach of trading for increasing the level of volatility in the market.
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However, the biggest disadvantage of program trading could be attributed to the fact that it entails high expenditures. The data requirements and technology infrastructure is inaccessible to most retail investors.
Conclusion
However, all said and done, the program trading will continue to grow in relevance and become more accessible to investors as technology advances. In 2018, the program traded for 50-60% of all trades placed on a given trading day. Furthermore, in developed economies like the US, as per 2021 data, 70-80% of the trades were executed using program trading strategies. This trend is expected to emerge in India as well.
