Algorithmic Trading: Definition and Use Cases - SmartAsset (2024)

Algorithmic Trading: Definition and Use Cases - SmartAsset (1)There are many different strategies for managing an investment portfolio But did you know you can automate trades within that portfolio? Algorithmic trading automatically places stock orders based on price and other conditions. Here are the basics of this method, how it works, its pros and cons, and when to use it.

Algorithmic Trading: The Basics

An algorithm is a procedure by which one solves a problem, usually mathematical. It usually requires following a certain number of steps for solving said problem. Also, it typically involves repetition.

Similarly, algorithmic trading, also called algo-trading, is a computer program that trades stocks by following specific steps in a specific order. In short, it trades stocks through computer automation. Above all, it seeks the highest possible returns on a trade in the most efficient manner.

Also referred to as automated trading or black-box trading, algorithmic trading uses several market variables in its algorithm. These variables include price, time, and volume.

History of Algorithmic Trading

Algorithms entered the U.S. financial world with computerized trading systems during the 1970s. The New York Stock Exchange took the biggest step in 1976 when it introduced the Designated Order Turnaround (DOT) system. That system sent orders from traders to right to data specialists on the exchange floor. Within the last decade, automated trades accounted for more than 60% of all trades.

In 2014, author Michael Lewis shed light on algorithmic and high-frequency trading with his book Flash Boys. He explained the infrastructure behind electronic trading and talked to traders and business owners who used it. While he noted that faster computers could make trades more quickly, he added that average investors often lost out as a result.

How It Works

Algorithmic Trading: Definition and Use Cases - SmartAsset (2)In algorithmic trading, traders utilize a computer program to set defined requirements for trade. For example, it can buy 100 shares when a specified number of shares moves below a predetermined price. Similarly, it can sell 100 shares when it moves above a certain price threshold.

The program then monitors the share price. Once it meets those criteria, the computer automatically acts according to pre-programmed buy or sell orders. With algorithmic trading, there’s no need for a trader to manually make the trades.

Pros and Cons of Algorithmic Trading

Algorithmic trading can be a powerful trading tool. As a result, the modern financial world uses it for several reasons. First, it makes it possible to enact trades at a much higher speed and accuracy than trades made manually. Trades occur almost instantly, lowering the change of price fluctuations between a trader’s decision and actual trade.

There’s also a lower chance of human error than when a human trader makes trades. Meanwhile, automated trades often have lower fees with no human traders involved.

But this method of trading isn’t without its downfalls. For one, while the automated systems on which algorithmic trading can streamline trades, making them more accurate and efficient, there’s also the chance that these systems can fail. This could cause an investor to miss out on a potential investment opportunity. Having a human advisor monitor trades is often a wise move. It can ensure trades occur as specified.

This method of trading doesn’t take into account the emotional aspect of trading. While this initially may seem like a good thing. After all, who hasn’t made a trade based solely on emotional or anecdotal experience only to have it tank? But algorithms can only take you so far, and in some cases, what works, in theory, may not translate well into the market for a myriad of reasons. Think market volatility, inherent risk, and the like.

Using Algorithmic Trading

Today’s financial markets use algorithmic trading in broad applications. It often pairs with high-frequency trading, which makes a large number of trades at a high speed across various market sectors.

Artificial intelligence has created deep learning algorithms that seek out more profitable trades. As a result traders and programmers are teaming up on algorithms that become more profitable on their own.

Institutional investors and larger brokerages use algo trading, but so do mutual funds, pensions, and other large-scale investment vehicles. However, hedge funds ask amateur programmers to write algorithms, paying them commissions for highly profitable code. High-speed internet and fast, cheap computers have made algo trading a favorite among day traders.

The Bottom Line

Algorithmic Trading: Definition and Use Cases - SmartAsset (3)Ideally, algorithmic trading can achieve both returns and trading speed that a human trader can’t. For that reason, it is a cornerstone of the modern financial world. However, this method is not without its downsides, from over-automation to failure to take into account real market conditions.

Investing Tips

  • If you’re not sure how algorithmic trading fits into your portfolio, a financial advisor may be able to help. Finding a financial advisor doesn’t have to be hard. SmartAsset’s free tool matches you with up to three vetted financial advisors who serve your area, and you can interview your advisor matches at no cost to decide which one is right for you. If you’re ready to find an advisor who can help you achieve your financial goals, get started now.
  • If you can trade stocks without human help, can you get financial advice that way as well? A robo-advisor can help you with certain decisions, but it isn’t right for everyone. Consider the pros and cons of a robo-advisor before seeking one out.
  • Do you know your investment risk tolerance? How will your investments grow over a certain amount of time? What will taxes and inflation take out of the equation? Before you go automating your investment strategy, consider consulting SmartAsset’s investing guide for answers to your most basic questions..

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Algorithmic Trading: Definition and Use Cases - SmartAsset (2024)

FAQs

What is the best way to define algorithmic trading? ›

Algorithmic trading (also called automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions (an algorithm) to place a trade. The trade, in theory, can generate profits at a speed and frequency that is impossible for a human trader.

Is algorithmic trading illegal? ›

Yes, algo trading is legal. No rules are in place by any federal or financial regulatory body that prevent an individual from algo trading.

How accurate is algo trading? ›

High Accuracy

Since algo-trading does not require human intervention to make buying or selling decisions, algo-trades have a much higher accuracy. They are free of all human-made errors. For example, the algorithm will not misenter the quantity of units meant to be traded.

Is algo trading really profitable? ›

Algo trading is not only profitable, but it also increases your odds of becoming a profitable trader., Algo trading is ideal for someone who wants to trade with their full-time job. While they can develop trading strategies in their extra time and which are executed by the system when they are at their job.

How to learn algorithmic trading from scratch? ›

To start, you need to understand the concept of the stock market. Beginning with the basics, you will need to backtest the various strategies and select one that meets your needs. Discover algo-trading and its pros and cons to know how it can help you trade smarter and more profitably.

What is the math behind algorithmic trading? ›

Linear algebra is required to understand the ins and outs of linear regressions, time series in general, multivariable calculus, and a vast majority of machine learning algorithms.

What is the success rate of algorithmic trading? ›

The success rate of algorithmic trading varies depending on several factors, such as the quality of the algorithm, market conditions, and the trader's expertise. While it is difficult to pinpoint an exact success rate, some studies estimate that around 50% to 60% of algorithmic trading strategies are profitable.

Can I do algorithmic trading on my own? ›

To create algo-trading strategies, you need to have programming skills that help you control the technical aspects of the strategy. So, being a programmer or having experience in languages such as C++, Python, Java, and R will assist you in managing data and backtest engines on your own.

Why is algorithmic trading bad? ›

While it provides advantages, such as faster execution time and reduced costs, algorithmic trading can also exacerbate the market's negative tendencies by causing flash crashes and immediate loss of liquidity.

Who is the most successful algo trader? ›

He built mathematical models to beat the market. He is none other than Jim Simons. Even back in the 1980's when computers were not much popular, he was able to develop his own algorithms that can make tremendous returns. From 1988 to till date, not even a single year Renaissance Tech generated negative returns.

Is algo trading fake or real? ›

Yes, algo trading is real. It refers to the use of computer algorithms to execute trading strategies automatically.

What are the disadvantages of algo trading? ›

Disadvantages of Algorithmic Trading

These situations are called black swan events and can lead algorithmic traders to suffer losses. The system relies entirely on the use of technology. Hence, if there is even a slight glitch in the system, the entire program of automation trade can crash.

How much money is required for algo trading? ›

Algo Trading FAQ

The minimum capital required for algo trading varies from platform to platform. However, most platforms require a minimum capital of Rs. 10,000 to Rs. 20,000 to get started.

How much do Algo traders make? ›

Algorithmic Trader salary in India ranges between ₹ 2.5 Lakhs to ₹ 100.0 Lakhs with an average annual salary of ₹ 20.0 Lakhs. Salary estimates are based on 31 latest salaries received from Algorithmic Traders. 1 - 9 years exp.

How hard is algo trading? ›

(But that would involve paying interest, so it's a bit more complicated) So, algo trading is at the same time difficult and easy, it is difficult because you have to learn programming, mathematics, and finance, but it is easy because it is about going into a position and then getting out of a position.

What are the methods for algorithmic trading? ›

Strategies for Algorithmic Trading

Any good strategy for algorithm trading must aim to improve trading revenues and cut costs of trading. The most popular strategies are arbitrage, index fund rebalancing, mean reversion, and market timing. Other strategies are scalping, transaction cost reduction, and pairs trading.

What is an example of algorithmic trading? ›

Example of Algorithmic Trading

Suppose you've programmed an algorithm to buy 100 shares of a particular stock of Company XYZ whenever the 75-day moving average goes above the 200-day moving average. This is known as a bullish crossover in technical analysis and often indicates an upward price trend.

What is algorithmic trading also known as? ›

Algorithmic Trading is also known as Black Box Trading. 2. It is a trading system that utilizes advanced and complex mathematical models and formulas to make high-speed decisions and transactions in the financial markets.

What is the difference between algorithmic trading and trading? ›

The basic difference

This method completely relies on human judgement, intuition, and emotional intelligence while making a trading decision. On the other hand, algorithmic trading involves the use of complex algorithms and computer programmes to automate the trading process.

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