What Is Algorithmic Trading? A Beginner’s Guide

Algorithmic trading is an algorithm-based investment strategy that employs a computer program to automate the buying and selling of assets, such as stocks, commodities, foreign currencies, and the like.

The computer code, or algorithm, is a sophisticated program written by a trader or investor to execute trades when certain conditions arise. The algorithm then executes trades based on a complex set of instructions.

Sometimes called algo-trading, automated trading, or black-box trading, algorithmic trading can, in theory, operate faster than a human trader and potentially generate outsized profits. By being automated, proponents say algorithmic trading eliminates the impact of human emotions. There are inherent risks in algorithmic trading, as well, owing to the level of automation.

What Is Algorithmic Trading?

Algorithmic trading is a form of active investing where an investor utilizes a high-tech program to monitor certain aspects of the market and automatically make certain trades under pre-determined market conditions.

An algorithm might determine when to buy or sell, at what prices, and how large a trade to make, with limited or no human oversight. This is a highly automated strategy, that’s quite different from investing online or through other channels on your own.

Algorithmic trading can offer advantages over manual trading by reducing traders’ salaries and related costs. The programs are capable of analyzing large volumes of data very quickly, which makes them especially appealing for arbitrage strategies, which demand that trades be identified and executed as fast as possible.

More investors have adopted algorithmic trading since the early 2000s, and today it accounts for as much as 70% of total orders in some markets. Technological advances, including vastly expanded computing power and faster internet connections have driven much of the expansion of algorithmic trading. It is also a place where the impact of AI on investing continues to unfold.

How Do Trading Algorithms Work?

In its simplest form, algorithm trading works by tracking a given asset — a stock, an exchange-traded fund or ETF, currency, or commodity — and setting parameters at which the program will buy or sell a given amount of that asset.

For example, the investor could program their algorithm to buy 1,000 shares of a stock if its 50-day moving average rises over its 200-day moving average, and then sell 1,000 shares when its 50-day moving average drops below its 200-day moving average — a task that would normally require technical analysis on the trader’s part.

With those coded instructions, however, a computer program will monitor the stock price for its movement in relation to the two indicators, and place trades accordingly.

For the trader, this saves time and energy while keeping the portfolio operating according to its strategy.

Common Algo Trading Strategies

The algorithms used in algorithmic trading can be relatively simple, as in the example above, or they can be dizzyingly complex. The more complex algorithms analyze a host of factors, including price changes, market conditions, and many other financial and economic and financial data points.

As such, the strategies available to a trading algorithm are limited only by the imagination of the programmer. Nonetheless, there are a few primary strategies that algorithmic trading lends itself to, such as trend-following, arbitrage, and high-frequency trades.

Trend-Following and Arbitrage

One group of investors who use algorithmic trading consists of systematic traders — a form of quant trader who operate according to a strategy of trend following. That strategy requires them to buy or sell according to observed trends in the price of a given security. For them, trading algorithms offer an efficient way to make trades according to a pre-decided, rules-based system.

Arbitrageurs — who aim to see returns by taking advantage of small discrepancies in asset prices — have also adopted algorithmic trading.

Here’s an example: Let’s say there was a stock that traded on two separate exchanges. The trader would set up a program that would track when the difference in the stock price on each exchange became wide enough to make for a profitable trade, then buy the stock on the exchange where it was trading lower, and sell it on the exchange where it was trading higher.

By automating the strategy, the investor can access more opportunities and act on them before other investors do, and the opportunity dries up.

High-Frequency Trading (HFT)

High frequency trading (HFT) is a form of algorithmic trading in which the algorithms place a large number of trades very quickly. It takes advantage of high-speed networks and high-power computing to make trades, often in a fraction of a second.

Because HFT allows investors to quickly trade large volumes of securities, it has the potential to profit from tiny price fluctuations in a given security, and allows institutions to make solid returns on bid-ask spreads. Some see this is an unfair advantage for large institutions, while others argue that HFT increases the liquidity in the market and makes the markets more price-efficient.

Pros and Cons of Automated Trading

Like any strategy, algorithmic trading is not without risks, and some algorithms have failed publicly in recent years.

Pros:

•   Having a fixed steps of parameters and rules built into an algorithm can protect an investor from making emotional decisions.

•   May save time in tracking markets and executing trades, allowing more time for planning and strategy.

•   An algorithm can be programmed to allow you to purchase large amounts of a stock without moving the market higher.

Cons:

•   Algorithmic trading is reliant on technology and vulnerable to failures in computer hardware, software, IT systems, and networks.

•   A trading algorithm, no matter how complex, will have its blind spots, which can cause an investor to miss out on profitable trades that don’t fit the parameters.

•   If the markets change in a way the algorithm doesn’t account for, then losses can pile up fast.

What Kind of Regulation on Algorithm Trading Exists?

Financial authorities, including FINRA in the U.S., monitor and regulate algorithmic trading. For regulated traders, the regulations demand regular testing of their systems and unique identifiers for their algorithms. They also prohibit using algorithms to manipulate prices on the market.

Regulators are largely focused on proper supervision and control of trading algorithms that include comprehensive risk assessment, software testing, and active communication between algorithm developers and compliance staff.

Getting Started With Algo Trading

To start algorithmic trading, you’ll need computer access and network access, as you would with any form of online stock trading. More than that, you’ll need some knowledge of the markets – algorithmic trading isn’t for beginners – as well as some ability to code.

If the last requirement is out of reach, there are other options available. You may also hire a coder, or access one of the many tools that allow you to automate investing.

That may sound daunting, but coding is becoming more accessible with new tools. Some online brokerages offer tools that can help you automate certain trades.

But before you start putting your money to work in an algorithm, consider the risks. It may make sense to back-test your algorithm to see how it would have done in the past, in different market environments, and consult an investment calculator.

The Takeaway

Algorithmic trading is the one way that investors are using technology to make more out of their investments. It offers certain possible advantages, such as saving time, and taking advantage of opportunities you might otherwise miss, but comes with unique risks. As a strategy it’s not for beginners.

If you decide to adopt an algorithmic trading strategy, consider the risks, back-test the strategy you’re programming in and set controls to limit your losses in case it doesn’t work out.

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FAQ

What is a black-box trading system?

A black-box trading system is a form of algorithmic trading program that buys and sells assets using pre-programmed rules. The “black box” name is because the calculations stay hidden from the user, who only sees the final trade inputs and outputs.

Do you have to know how to code to use algorithmic trading?

As new tools evolve, investors can set up reading algorithms without necessarily learning to code. Some tools let you pick indicators and rules on a screen, while others use low-lift codes that allow you to copy-paste basic rules or use AI. And some brokerages allow you to rent or buy pre-tested strategies. It’s also possible to hire a developer to build a custom algorithm.

Can algorithmic trading cause market crashes?

Algorithmic trading may help cause market crashes by accelerating sudden market declines, also known as ‘flash crashes,’ because they can execute large waves of automated trades in seconds. That said, algorithms rarely initiate a crash.

What programming languages are best for trading algorithms?

The programming languages Python and C++ are the industry standards for trading algorithms. But determining the best language depends entirely on your own expertise, as well as your specific trading strategy and speed requirements.

How much money do you need to start algorithmic trading?

You can start algorithmic trading with no money at all, if you’re using simulated trading accounts. But to trade live with real money, the initial capital requirements will range widely from as little as $100 to more than $25,000, depending on the trading platform, the asset class you’re trading, and how it’s regulated.

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