Source: Media Outreach
KUALA LUMPUR, MALAYSIA – Media OutReach Newswire – 7 December 2024 – Artificial intelligence is transforming trading, delivering unprecedented power in data analysis, pattern recognition, and decision-making. However, around 40% of traders hesitate to fully trust AI-driven decisions as they fear losing control over critical trading outcomes. Kar Yong Ang, financial markets analyst at Octa Broker, explores how traders can harness the power of AI while maintaining control and avoiding excessive intervention.
Real Advantages of AI in Trading
AI enables traders to process massive datasets quickly and efficiently. For example, machine learning algorithms analyse historical price data, market sentiment, and global news to predict market trends. Studies confirm that AI-powered algorithms improve trade accuracy by 38% compared to traditional methods.
Alongside this, AI automates time-consuming processes, such as monitoring price fluctuations and stop-loss orders, as well as executing trades based on predefined parameters. A case study on TradeWeb showed that the implementation of AI systems increased trading speed by 23% while the number of errors decreased by 15%.
What is more, AI excels in identifying market patterns that might go unnoticed by human analysis. For instance, JPMorgan’s AI systems predicted potential market movements with an accuracy rate of 75%, as highlighted in a Cointelegraph report.
The Risks of Overusing AI in Trading
Over-reliance on AI could weaken traders’ ability to manually interpret the markets. A recent study showed that traders relying solely on AI experienced a 22% reduction in the ability to perform manual analytics after six months of using AI alone. This ramps up the risks, as traders should always remain on guard and be able to conduct independent objective analysis to avoid misleading assumptions.
Although the algorithms do reduce the number of mistakes, they aren’t error-prone. Data inconsistencies, algorithmic biases, and unpredictable market events can lead to poor trading decisions and losses. For instance, a 2023 market analysis revealed that 12% of trades executed solely by AI systems resulted in unexpected losses due to flawed input data.
Tips for Balancing AI and Manual Trading
Automating decisions may save time but can result in traders losing sight of broader market contexts. Experts stress the importance of using AI as a supportive tool rather than a decision-making replacement. Here are four steps on how traders can integrate AI into their trading routine while balancing the risks and reaping the perks.
- Combine AI insights with manual analysis. AI has to complement traditional trading techniques. For example, combining AI-driven insights with manual analysis can provide a nicely rounded method, improving accuracy and adaptability.
- Start with a demo account. To avoid risking the real budget, it’s advised to test AI’s capabilities and trading decisions using a demo account, which is available on Octa Broker. The demo account allows traders to experiment with AI and recognise its functionality and barriers risk-free.
- Understand AI’s limitations. AI models rely on historical statistics and won’t adapt quickly to surprising market changes. Traders must regularly examine the relevance and accuracy of AI-based tools to ensure solid performance.
- Use AI for post-trade analysis. Post-exchange reviews using AI allow traders to get deeper insights on their trading successes and failures. Tools like Octa Vision analyse beyond trades to help you discover your trading style and propose upgrades. This iterative process allows traders to refine their strategies and avoid repeating mistakes.
Although AI still poses certain risks, people actually trust it more than humans, according to the Ipsos Consumer Tracker. Businesses adopt the tool more willingly, with 50% of financial institutions having already integrated AI into their trading workflow. According to McKinsey, a trend of growing AI adoption on the enterprise level is likely to stay and evolve: AI in business is expected to grow 18% annually through 2030, with advanced predictive models and risk management becoming the standard. This may drive increased adoption rates among retail traders, too.
In 2025, the business ecosystem is expected to rely heavily on AI. Companies that develop a solid understanding of AI applications today will be better prepared to navigate these changes, ensuring they stay at the forefront of the trend. The same works for regular traders. Those who want to make AI a tool for efficient trading should acknowledge its strengths and weaknesses.
Responsible AI deployment is key. Traders who balance AI-driven insights with manual analysis and maintain a focus on continuous learning can leverage the technology. Besides this, they can optimise their trading outcomes while safeguarding against potential risks.
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