Algorithmic Traders in India Earn $7 Billion While Most Retail Traders Struggle

Fact checked by
Mike Christensen, CFOA
September 25, 2024
Algorithmic traders earned $7 billion in India in 2024, while 93% of non-algorithmic retail traders struggled with losses. Automating strategies with tools like TradersPost can help retail traders bridge the gap in trading success.

In the fiscal year 2024, algorithmic traders in India made a staggering $7 billion, according to a report shared on Bloomberg. Meanwhile, 93% of non-algorithmic retail traders faced losses, especially in derivatives, futures, and options markets. The data highlights a growing divide between institutional players who leverage algorithmic trading and retail traders who primarily engage in manual trading.

Why Are Algorithmic Traders More Successful?

The success of algorithmic trading, particularly for institutions, can be attributed to several factors:

Advanced Risk Management: Algorithms are programmed with precise risk management rules, ensuring that trades are executed according to predefined criteria. This consistency helps avoid emotional trading mistakes.

Execution Efficiency: Algorithms can place large orders using strategies like VWAP (Volume Weighted Average Price), allowing institutions to obtain fair pricing without significantly impacting the market.

Automation and Scalability: Automated trading enables strategies to scale efficiently without human limitations, allowing for consistent execution even under various market conditions.

The Struggles of Retail Traders

For retail traders, the manual trading process often involves inconsistent risk management and emotional decision-making. Many traders lack a structured approach, leading to poor outcomes when dealing with complex instruments like futures and options. The statistic showing that 93% of non-algorithmic retail traders lose money underscores the need for retail investors to adopt algorithmic methods to level the playing field.

The Case for Automation with TradersPost

To bridge the gap between institutional and retail trading success, platforms like TradersPost offer tools for automating trading strategies. By converting trading ideas into algorithmic steps, retail traders can improve consistency and reduce the element of chance. Automating risk management within strategies further enhances the potential for long-term profitability.

Conclusion

The significant earnings of algorithmic traders in India highlight the advantages of automation and risk management in trading. With the majority of retail traders experiencing losses, adopting algorithmic processes and automation platforms like TradersPost could be key to improving trading outcomes.

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