What Is Algo Trading?

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Algo Trading

Algo trading has grown at a blistering pace since the mid-1990s when it accounted for only 3% of trades. Currently, it accounts for almost 85% of dollar trade volumes and is one of the hottest applications of technological innovation in recent years. 

In today’s interconnected financial markets, algo trading has played a pivotal role in empowering traders and firms to eliminate human error and emotion while also solving latency problems, changing the way many trade.

What is algo trading?

Algo trading, also known as algorithmic, automated, or BlackBox trading, encapsulates trading systems that are heavily reliant on sophisticated programming models, mathematical formulas, and/or high-speed computer software to determine trading strategies to employ.

Algo trading employs computer code and chart analysis to determine when to enter and exit trades in accordance to set parameters like price movements or volatility levels. 

Traders utilise electronic platforms to enter trading orders, leveraging on these sophisticated algorithms that execute pre-programmed trading instructions, which account for various variables such as timing, price, and volume. 

When market conditions match pre-determined criteria, the trading algorithm can execute a purchase or sell order on the trader’s behalf, saving the trader valuable time as trades are executed almost instantly.

With a defined set of instructions written within these algorithms, traders are able to generate profits at high speed and frequency in a manner that is impossible for a human trader. 

Algorithmic trading
Photo by Markus Spiske on Unsplash

How does algo trading work?

As alluded to earlier, trading algorithms are a specific set of clearly defined instructions that carry out trading-related tasks or processes. In essence, trading algorithms can involve a level of manual intervention or can be entirely electronic, also referred to as zero-touch algos. 

These defined instructions can be initiated based on pre-set quantitative factors, arbitrage opportunities, or the client’s preference. They sometimes work around an Application Program Interface (API) that lets traders choose their strategy and enter their specific requirements before the trades are executed by the brokers on their behalf.

For example, algo trading can be employed by a trader who might desire to implement trades when the asset price reaches a specific level. Based on existing market conditions, the trading algorithm can recommend the position to take. 

Another example is when a trader follows trade criteria, such as: buy 100 contracts of a currency pair, when its 100-day moving average goes above the 200-day moving average, and sell the same amount when its 100-day moving average goes below the 200-day moving average.

Following this set of two basic instructions, computer software can be programmed to automatically monitor prices (and the moving average indicators), then place the buy and sell orders when the defined conditions are met. 

As such, there is no manual intervention needed here, and the trader is no longer required to manually monitor the live prices and graphs, or place orders himself. Instead, the algorithm does his work for him very effectively and efficiently.

Characteristics of Algo Trading

Generally speaking, a bulk of the algo-trading today revolves around quantitative trading, technical trading, and/or High-Frequency Trading (HFT). 

As such, algo trading is primarily based on systematic approaches rather than methods or techniques based on trader intuition or instinct, automating trade executions without human intervention. 

Benefits of algo trading

Besides creating significant profit opportunities for traders, algo trading makes trading more systematic by ruling out human emotional impacts on trading activities.

With numerous advantages over manual trading, algo trading has become part and parcel of the finance industry, and this trend will most likely continue. Some of its benefits include:

  • Significantly reduced risk of manual errors when placing trades. 
  • Trade order placement is mostly instant and accurate, which means there is an increased chance of executing trades at the desired price levels.
  • Trades are timed correctly and instantly to avert significant price changes. 
  • Algo trading allows for simultaneous automated checks on multiple market conditions.
  • An algo-trading strategy can be easily backtested, utilising available historical and real-time data to see if it is a viable trading strategy.
  • Traders spend less time actively monitoring the markets as algorithms are intended to account for various factors and scenarios.

How different is algo trading from human trading?

Computer platforms used in algo trading can deliver a much shorter reaction time and offer a higher level of reliability than manual execution. This is because most decisions reached by a computer rely on the underlying strategy with specified rules. 

As most algo trading decisions are made based on an underlying strategy with specified set of rules, a high level of competence and objectivity in trading decisions can be achieved, while eliminating any human emotions and errors.  Trades executed via the algo can also be reproduced with backtesting of trading data, which would help to improve subsequent strategies and decisions.

Getting started with algo trading

The first step in algo trading would be to formulate a trading strategy based on an individual’s trading and risk management objectives..

The next step is creating the algorithm to automate these trading strategies using programming languages like Python, R, or any other trading software. The strategy can also be backtested against historical data to provide further analysis.

Traders who are interested in algo trading will need to have an understanding of financial markets, data analysis, statistical tools and techniques, and some statistical competence to conduct test hypotheses, market microstructures, trading portfolio optimization, and backtesting, as well as some programming skills.

The financial  market landscape has changed dramatically over time with many new electronic trading platforms introduced that compete with already established exchanges. Traders should compare various platforms to find one that works best with their requirements.

statiscal tool
Photo by Olya Kobruseva from Pexels

Conclusion

Algo trading systems play an increasingly vital role in financial markets as they can handle large order volumes in a manner that humans cannot match.

The industry will also continue to see algo trading playing an important role in institutional trading with its increased efficiency, accuracy, and capacity.

Read more on algo trading platforms at Ortega Capital.

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