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Algorithmic Trading Vs Discretionary Trading What’s the Difference?

March 25, 2024
Reading Time: 3 minutes

In financial markets, two primary trading approaches dominate: algorithmic trading and discretionary trading. While both aim to capitalise on market opportunities, they differ significantly in methodology, execution, and decision-making processes.

Algorithmic Trading

Algorithmic trading, also known as algo trading or automated trading, on platforms like uTrade Algos, employs computer algorithms to execute trades automatically based on predefined rules and criteria. These algorithms analyse vast amounts of market data, identify patterns, and execute trades with minimal human intervention. 

Advantages of Algorithmic Trading 

Speed and Efficiency

Algo trading operates at lightning-fast speeds, executing trades in milliseconds, which is impossible for human traders. This speed advantage allows algorithmic systems to capitalise on fleeting market opportunities. 

Emotion-Free Trading

Algorithmic trading software operates based on predefined rules, devoid of emotional biases that often influence human decision-making. This eliminates the impact of fear, greed, or other emotions on trading outcomes. 

Backtesting and Optimisation

Algo trading strategies, on platforms like uTrade Algos, can be backtested using historical data to assess their performance under various market conditions. This enables traders to refine and optimise their strategies before deploying them in live markets. 

Disadvantages of Algorithmic Trading

  • Tech Dependency: Algorithmic trading software is vulnerable to glitches, bugs, and outages, which can result in significant financial losses.
  • Lack of Judgement: They lack the human intuition and judgement necessary to adapt to unforeseen market events, leading to potential losses during periods of market volatility or unusual conditions.
  • Overfitting Risk: While algorithms may perform well in backtesting environments, they can fail to perform optimally in live markets due to overfitting, where strategies are too finely tuned to historical data and do not generalise well to new data.
  • Market Volatility: High-frequency trading algorithms, in particular, have been criticised for exacerbating market volatility and contributing to flash crashes by executing large volumes of trades in milliseconds.
  • Regulatory Scrutiny: Algorithmic trading programs face increasing regulatory scrutiny due to concerns about market manipulation, systemic risk, and the potential for algorithms to amplify market movements unpredictably. 

Discretionary Trading

Discretionary trading involves human decision-making based on trader intuition, analysis, and judgement. Traders rely on their experience, market knowledge, and instincts to make buy or sell decisions in real time. 

Advantages of Discretionary Trading 

Flexibility and Adaptability

Discretionary traders can quickly adapt to changing market conditions, news events, or unforeseen circumstances. Their ability to interpret market sentiment and adjust strategies on the fly can be advantageous in volatile markets.

Subjectivity and Creativity

Discretionary trading allows for the subjective interpretation of market data and the application of creative trading strategies. Traders can capitalise on unique insights or niche opportunities that may not be captured by algorithmic models. 

Fundamental Analysis

Discretionary traders often rely on fundamental analysis, assessing the intrinsic value of assets based on factors such as earnings, revenue, and economic indicators. This approach can uncover long-term investment opportunities overlooked by algorithmic models focused on short-term price movements. 

Disadvantages of Discretionary Trading

  • Emotional Bias: Discretionary traders are susceptible to emotional biases such as fear, greed, and overconfidence, which can lead to impulsive or irrational trading decisions.
  • Limited Scalability: Discretionary trading strategies may struggle to scale effectively, as managing large portfolios and executing trades across multiple markets can be challenging for individual traders.
  • Subjectivity: Discretionary traders rely on their interpretation of market data, which can lead to inconsistent decisions among traders and a lack of a systematic approach to trading.
  • Time Intensive: Discretionary trading requires constant monitoring of market conditions and decision-making, consuming significant time and effort that may not be sustainable for all traders.
  • Manual Processes: Discretionary traders often rely on manual processes for trade execution and analysis, which can lead to inefficiencies and errors, especially when compared to the automation and speed of algorithmic trading programs. 

Key Differences

Decision-Making Process

Algorithmic trading in India, and across the world, relies on pre-programmed rules and algorithms to execute trades automatically, while discretionary trading involves human decision-making based on intuition, analysis, and judgement. 

Speed and Automation

Algorithmic trading, on platforms like uTrade Algos, operates at high speeds, while discretionary trading may involve slower decision-making processes and manual execution. 

Emotional Influence 

Algorithmic trading eliminates emotional biases, while discretionary trading may be susceptible to emotional decision-making. 


Algorithmic trading strategies are rigid and may struggle to adapt to unexpected market conditions, whereas discretionary traders can adjust their strategies in real time.

In conclusion, both algorithmic and discretionary trading offer distinct advantages and cater to different trading styles and preferences. While algorithmic trading, in India and across the world, excels in speed, efficiency, and systematic execution, discretionary trading provides flexibility, adaptability, and human judgement. Understanding the differences between these approaches is crucial for traders to choose the strategy that best suits their goals, risk tolerance, and market conditions.

Frequently Asked Questions

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uTrade Algo’s proprietary features—advanced strategy form, one of the fastest algorithmic trading backtesting engines, and pre-made strategies—help you level up your derivatives trading experience

The dashboard is a summarised view of how well your portfolios are doing, with fields such as Total P&L, Margin Available, Actively Traded Underlyings, Portfolio Name, and Respective Underlyings, etc. Use it to quickly gauge your algo trading strategy performance.

You can sign up with uTrade Algos and start using our algo trading software instantly. Please make sure to connect your Share India trading account with us as it’s essential for you to be able to trade in the live markets. Watch our explainer series to get started with your account.

While algo trading has been in use for decades now for a variety of purposes, its presence has been mainly limited to big institutions. With uTrade Algos you get institutional grade features at a marginal cost so that everyone can experience the power of algos and trade like a pro.

On uTrade Algos, beginners can start by subscribing to pre-built algos by industry experts, called uTrade Originals. The more advanced traders can create their own algo-enabled portfolios, with our no-code and easy-to-use order form, equipped with tons of features such as robust risk management, pre-made algorithmic trading strategy templates, payoff graphs, options chain, and a lot more.

From single-leg strategies to complex portfolios, with upto five strategies, each strategy having up to six legs, uTrade Algos gives one enough freedom to create almost any auto trading strategy one likes. What’s more, is that there are pre-built algos by industry experts for complete beginners and pre-made strategy templates for those who want to try their hand at strategy creation.

An interesting feature that uTrade Algos is bringing to the table is a set of pre-built algorithms curated by top-ranking industry experts who have seen the financial markets inside out. These algorithms, called uTrade Originals, will be available for subscribers on the platform.

Algos have the capability to fire orders to the exchange in milliseconds, a speed which is impossible in manual trading. That is why traders leverage the power of algo trading to make their efforts more streamlined and efficient. You can try uTrade Algos for free for 7 days!

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Knowledge Centre & Stories of Success

In the world of algorithmic trading, measuring performance goes beyond simply looking at profits. Here strategies are executed at lightning-fast speeds and hence, metrics beyond profits are needed to assess the robustness of it all. Among the various metrics, the PnL aka Profit and Loss is a critical metric that sheds light on the effectiveness of your algo trading strategy. 

Algorithmic trading has become increasingly popular among traders looking to automate their strategies and capitalise on market opportunities. With the rise of algorithmic trading platforms like the uTrade Algos algo trading app, traders have access to powerful tools and technologies to execute trades with precision and efficiency. However, to make the most of these tools, it's essential to optimise your algorithmic trades effectively. Let us explore seven essential tips for optimising your algorithmic trades using the app.

In algorithmic trading, where seconds can make a difference, having effective exit parameters is crucial for managing risk and improving the chances of returns. Global exit parameters serve as predefined rules or conditions that trigger the exit of a trade, ensuring disciplined and systematic trading. In this guide, we'll find out about the concept of global exit parameters, explore their significance in algo trading, and understand how they function in real-world trading scenarios.

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