1 December 2023
Algorithmic Trading

Hedge funds and proprietary trading firms have adopted algorithmic trading in the past two decades. Additionally, the APIs are available for programmatic order placement on most crypto exchanges and stockbrokers. They have encouraged individual investors to implement their personalized algorithms.
However, it is important to remember that discretionary trading is still active and significant in the financial industry. This article will explore the key distinctions between algo trading and discretionary trading, examining their pros and cons and the distinct skill sets needed for each approach.

An Overview of Algorithmic Trading

Algorithmic trading, also known as algo trading, executes orders through online terminals based on specific trading logic. It involves using various trading algorithms to generate instructions and convert a trading strategy into computer code.
This method automates the buying and selling of shares quickly and accurately through an algo trading app. This automated approach has become popular in emerging markets due to its efficiency. Algorithmic trading depends on mathematical algorithms to make trading decisions using real-time market data and execute orders in financial markets.


Here are the pros associated with Algo trading:

  • The speed and precision of algo trading are among its main benefits. Algorithms can examine large quantities of information and quick trading with rapidly changing markets.
  • Algo trading can remove the influence of human emotions and preferences, frequently resulting in less-than-optimal investment choices.

Algo Trading makes objective and disciplined investment decisions based on data and predetermined rules in the Algo trading partner program.


Along with profitable advantages, it has certain limitations which impact the trading experience. Here are some of them:

  • One drawback is that algorithms can be inclined to surprising market variation, which is not included in the algo trading software.
  • Moreover, in certain cases, the algorithms might not be accurate with qualitative information such as news which restricts its profitability in specific market conditions.

What Is Exactly Discretionary Trading?

Before algorithmic trading was introduced, discretionary trading was already active in the stock trading market. In earlier times, people would manually engage in trading. It involved placing trades either via phone calls or electronic means using computers.
During this period, traders collect the market data manually, analyze it, and then use that information to make trading decisions. As a result, human traders manually make their choices based on historical databases to buy or sell stocks. However, the need for a faster and more reliable method with accurate research initiated the innovation of algorithmic trading.


Here are some noticeable pros of discretionary trading that make an essential difference between them. Here are the mentions:

  • Discretionary trading provides greater adaptability and the possibility of generating greater profits.
  • With this, human traders can carefully analyze market data, news, and other relevant information to discover opportunities that may be overlooked.
  • With discretionary trading, traders can include their prospects and valuable insights into their investment choices. It results in more improved and advanced investment strategies.


Here are some of the cons:

  • Human traders can make errors and be influenced by emotions, biases, and other psychological factors. It can lead to less-than-optimal investment decisions and potentially lower long-term returns.
  • Discretionary trading needs significant time and effort to monitor the market conditions and adjust its strategies accordingly.

Major Differences Between Algo Trading And Discretionary Trading

Algorithmic trading and discretionary trading are two different strategies in the investment field, having their differences. Algorithmic trading uses pre-programmed rules through algo trading software and quantitative analysis with trading procedures, while discretionary trading depends on human intuition and judgment for making investment decisions. Let us assess some of the differences in brief:

  • Trading Strategy

The trading strategy used by discretionary traders is derived from information obtained through analyzing charts, assessing market conditions, understanding indicative signals, and considering other relevant factors. It allows them to create specific rules to abide by when initiating trades or determining appropriate exit points. 

Conversely, algorithmic traders depend on chart analysis. It uses algorithms to determine when to enter or exit positions in the stock market. Professionals with the necessary programming skills, statistical and probability expertise, risk management proficiency, historical data analysis capabilities, and forecasting abilities develop these algorithms. The algo trading partner program examines the market and makes decisions based on the preset logical rules integrated into the algorithms.

  • Automated approach

Discretionary trading involves manual management by the trader without depending on automated systems for making decisions. Algo trading engine automatically performs trades with an automated approach for profitable trading. 

Discretionary trading needs active market monitoring and analysis charts. In algorithmic trading, the information is processed through the system, providing suggestions for the best results. The trader can then activate the algorithms and monitor progress with necessary adjustments.

  • Market Assessment

A sudden change in market conditions can lead to financial losses if a discretionary trader makes impulsive decisions. It is because of the lack of understanding regarding the volatile market condition. The Algo trading engine can improve its performance in such situations by using techniques like sentiment analysis with programmed algorithms. By considering external factors, these algorithms can accurately interpret market fluctuations.

  • Impact of Human-Based Emotions

Discretionary traders deeply influence human emotions during the decision-making process, sometimes resulting in significant losses. Traders often deal with emotional biases while investing with projected profitable outcomes. The Algo trading has zero percent risk of influencing emotional factors. It is a mathematical model that depends on specific instructions and eliminates any involvement from emotions like greed, fear, or false intuitions.

  • Pre-Defined Regulations 

Discretionary traders do not follow any specific guidelines for trading and investment. Their decision to buy or sell is based on their trading experience and research. It results in unique trading rules for each transaction involving certain risks. 

Algorithmic trading depends on pre-established rules that use historical data and help you make investment decisions. The process of backtesting increases the chances of positive results.


Deciding between algo trading and discretionary trading completely depends on the trader’s personal intentions, level of risk acceptance, and investment principles. Some traders may combine both approaches using algorithms to recognize opportunities and discretionary trading to finalize investment decisions. 

Traders must research, analyze risks widely, and establish a strong risk management strategy to minimize potential losses. Algo and discretionary trading are different investment approaches, each with advantages and disadvantages.

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