Stock market trading has been in existence for several decades now, but only recently has it become open to all. At one point, only professional brokers with MBA qualifications who worked for institutional brokerages could participate in trading activities. But, thanks to the ubiquity of the internet, the common man can also try his hand at trading.
The way trading activities occur has also undergone a sea change since the rise of electronic communication networks (ECNs), and the usage of machine learning and data science in this domain. The process of using machines to carry out trades in place of humans is called algorithmic trading or algo trading. This article gives an overview of some of the stock market basics and how they have changed with algo trading.
Stock Trading 101
A stock exchange or stock market is a generalized term for any platform where people buy and sell financial securities, like stocks, bonds, mutual funds, and other entities. Each of these products is quite different, with varying structures, payoffs, and purposes. For example, a company’s stock is a financial instrument that represents a share of the company’s equity. In contrast, a bond represents a loan made by an investor to a borrower.
Any company whose stocks are available for trading in a stock exchange is said to be a “listed” company. Each company’s share is set a price based on an auction between the millions of sellers and buyers who trade in that particular stock exchange.
Earlier, if a common man wanted access to the stock market, they needed to contact a stock brokerto perform the trading activities for them. However, with the advent of trading platforms on the internet, anyone can trade securities on these online sites.
Based on the market or securities you want to specialize in, you need a minimum initial deposit to start trading. Once you create an account, you can place orders to buy and sell trades with other brokers who are on the same platform.
Features of Online Trading Platforms
Besides the features that enable you to exchange securities, online trading platforms have several other tools you can use. Almost all sites will have the live market data feed to help you monitor the prices of the securities you choose. Others have sophisticated analytical tools that help you predict the future market movement (next hour, next day, and so on).
A stockbroker typically trades on online platforms by making use of these additional features to better understand the market. However, humans cannot monitor multiple markets continuously or execute thousands of trades in split-second intervals. Computers can handle such large amounts of data and perform calculations at high speed, which is why algo trading has become popular in recent times.
What is Algo Trading?
Algorithmic trading is the method where traders can program instructions based on parameters like trading volume, stock price, volatility, and other market conditions so that a computer can execute trades on their behalf. Typically, traders specializing in pensions and mutual funds, those dealing with arbitrages and short-term price fluctuations, and others who trade systematically based on set rules benefit the most from algo trading. Among all the trades executed in the US, around 70% by volume is done through algorithmic trading, and all traders who enter the profession today should be well-versed with the basics of algo trading.
Algorithmic trading works as follows: suppose you want to sell Google (GOOG) shares to make a particular profit. You can ask the machine to monitor the market parameters and ask it to sell 200 shares when the stock price goes above $1,500, and the 20-day moving average is over $1,490. The computer tracks the live market data every instant, and, when such a scenario occurs, it automatically completes the trade on your behalf.
What are some of the other benefits and shortcomings of algorithmic trading when they replace human traders?
Algorithmic Trading: For Better or Worse?
Traders who manually handle deals usually restrict themselves to a couple of markets at most so that they have control over their investments. With the help of a computer, you can trade across multiple markets simultaneously, since the machine can manage that much more data.
The system’s overall accuracy and efficiency are quite high thanks to the computational power, which makes it possible to systematically carry out trade orders to ensure profits. High-frequency trading is best carried out using algo trading tools, making the most of minuscule price fluctuations and realizing gains.
Machines also keep out all emotional play and work solely with the data and parameters you set. You can focus more on the robustness of your strategies than gut instincts, helping you to make consistent earnings.
The Need for Programmers
One machine can potentially replace several traders and intermediaries, which leads to significant cost reductions for the brokerage firm. However, the demand for programmers and software engineers – who also have some finance knowledge – goes up. At the rate at which technology is evolving, programmers need to update themselves frequently to incorporate the latest techniques and algorithms to execute trades more efficiently.
One of the most crucial areas where algo trading wins over humans is its ability to predict the outcomes in specific market scenarios. One way to test the machine’s algorithm is to perform backtesting, which is the process of feeding the computer data from the past and comparing its prediction to the actual results.
Backtesting provides you with an idea of how good the predictive behavior is, which, in turn, gives an estimate of your expected profit or loss. However, some human intervention is needed at this stage because no two market scenarios are exactly alike. Subtle variations could make or break a deal.
Man Versus Machine
Undoubtedly, machines are capable of handling a much larger volume of trades and in the span of milliseconds, but human intervention is still an essential part of algo trading. Traders and programmers need to monitor the computers to check for wrong executions and to step in during power cuts or mechanical failures.
The continuous new developments within machine learning and artificial intelligence, computers can take on more substantial responsibilities, until they become potentially self-reliant in every aspect.