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AskGalore
AskGalore
IT Services - FinTech, ESG, Supply Chain, Blockchain, DeFi, dApps & NFT Development | Gen-AI | AI/ML | Growth Marketing
Published Feb 15, 2024
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Successfully trading in stocks involves not only a thorough analysis of the company's financials, management, price patterns, indicators, etc. but also speculation, which means relying on market sentiments and momentum. Both propositions are very fruitful yet carry high risk, keeping investors and investments always aware of their financial goals and investment strategies while investing. It is now that in our human-ai-augmented universe, with the high capital investments in AI development and deployment in our banking industry and its successful run, artificial intelligence (AI) algorithms are also being applied in stock trading through data analysis and pattern recognition. These algorithms are capable of speedy analysis of large volumes of data while identifying trading opportunities, computing them, and executing trades.These coded algorithms are quite accurate in their predictions of stocks. Asset management companies deploying AI have been recording accuracy of more than 80% while predicting stock price movements. Comparatively, algorithms have also been found to deliver high efficiency at lower costs. Since market sentiments play a pivotal role for traders engaged in day trading, the deployed AI can effectively analyze social media trends, news articles, and other sources of information to assess the day-to-day market sentiment. Also, by making an investment pattern analysis of where traders and investors are investing in specific assets, AI can help traders anticipate upcoming price movements and make their investment decisions accordingly. It is significant to note that AI-based trading systems currently require human oversight to manage risks and adapt to changing market conditions. Regulatory bodies also closely monitor AI-powered trading to ensure fairness and prevent market manipulation.
Stock trading with AI typically involves the following processes
This complete iterative process of data analysis, i.e., model development, its validation, deployment, and monitoring, is crucial for successful stock trading with AI, and it does require human expertise in data science, machine learning, finance, and risk management to effectively and efficiently leverage AI technologies in the financial markets.
While AI-powered stock trading offers good advantages for successful trades, such as
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It also raises concerns about the bias in algorithms, system reliability, and regulatory oversight.
We human traders, on the other hand, bring qualities like
In May 2023, JP Morgan revealed on Investor Day that their asset management division uses AI to develop trading strategies and hedge equity portfolios and that it has more than 300 AI use cases in production. By now, even smaller banks are using this technology too. AI trading stocks is completely legal in India too, irrespective of whether you are an investment firm or a private investor.
The algorithm AI platforms utilized and the AI strategy providers have to be registered with SEBI, and an exam is mandated for the strategy providers. The profitability and return claims made by the AI stock trading providers may have to be substantiated through a Performance Validation Agency (PVA).
Just a reminder: while stock trading can be a fruitful investment, it remains a high-risk strategy subject to market risks in both cases.
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