How can artificial intelligence be used in investing?

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Investing is one of the most quantitatively intensive fields there is. Still, it is cluttered with old-school models that are simple and heuristic-based. The new-age millennial investors recognize the power of artificial intelligence. They are increasingly looking to utilize the power of AI to democratize the world of investing and get access to tools to invest, like professional Wall Street investors.

Artificial Intelligence has had an enormous impact and has surpassed humans in many fields, from gaming to computer vision to self-driving cars. Artificial Intelligence can create a competitive edge to extract actionable insights in the complex framework of the financial markets with their ever-changing dynamic nature, hundreds of noisy factors affecting performance, and non-linear interactions. There are no areas in investing, from modeling returns to reducing risk to even reducing costs, where AI does not have a better solution than a human.

The first users of AI in investing were the famous global hedge funds, with mathematicians like Jim Simons using proprietary AI models to make a killing in the market in the last half-century. But now, the use of AI is becoming more and more mainstream. Robo-advisors use automated, algorithm-driven models to analyze the markets and optimize our investments. So AI is slowly but surely coming everywhere.

In today’s day and age, AI-driven investing provides a transparent and flexible way to invest for the new-age investor who wants to be in the driver’s seat. AI-driven advisors solve critical problems that the investor faces with these tools, from asset allocation to stock selection to reducing trading costs. Globally asset managers, brokerages, hedge funds, and Robo-advisors are increasingly adapting to AI, and the research work on the subject is growing in leaps and bounds.

AI is used in investing some a diverse set of areas. An AI-driven model can better any quantitative process marred by linear thinking, heuristics, and over-fitting. Some key areas where AI is used are:

  • Alpha Generation – The first job of every investment manager in the field is generating excess returns, and an AI-driven manager has the same role. Machine Learning algorithms can better model the non-linear nature of diverse financial datasets and extract more accurate and actionable insights on alpha generation.
  • Managing Risk – Risk is more predictable than returns in the financial markets, and AI can be a gamechanger in risk management. Artificial intelligence models can predict the changing volatility patterns and market regimes to inform the asset allocation model better to safeguard capital.
  • Extracting Alternative Information – An exciting new area of investing where AI plays a significant role in extracting information from unstructured data. For example, pulling sentiment out of Twitter or consensus estimates from analyst notes, drawing information about a company based on internet searches or geographic activity data. The avenues for exploration here are endless.
  • Operational Efficiency – Last but not least, Artificial Intelligence techniques can enhance the user experience by empowering asset managers to understand user requirements better and get better insights using big-data analytics.

Artificial Intelligence is nascent in India and is blooming in investment management. Artificial intelligence has the edge over traditional models and managers. It can process large datasets and extract actionable insights, accounting for the complex non-linear interactions between the hundreds of economic and financial variables. As the new set of investors and the new asset managers are more data-driven and influenced by AI, we see the investing field evolve to be more efficient and rewarding.

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Views expressed above are the author’s own.

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