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According to Nitish Maini, Director of Strategy at WorldQuant, India's deep pool of technical specialists and developed technological infrastructure create favorable conditions for continuous growth in the field of quantitative investing.

In an email exchange with Business Standard, he stated that India possesses the necessary elements for sustainable development in quantitative investing, including an extensive base of technical personnel and a strong technological foundation. He noted the sharp increase in the number of participants from India in the International Quantitative Championship WorldQuant (IQC), which exceeded 54,000 people in the last edition, compared to approximately 15,600 participants in 2024.

Quantitative investing uses mathematical models, statistical methods, and algorithms to identify market patterns and generate investment signals. WorldQuant, founded in 2007, is an international asset management firm specializing in quantitative methods, developing and applying systematic investment strategies across various markets.

The continuation of quantitative methods development

According to Maini, the next stage of quantitative investing development will be determined not so much by access to large volumes of data or automation, but by improved research methodologies. He emphasized that Indian researchers can focus on developing investment concepts that are robust, economically significant, and distinct from existing ones.

In India, although asset managers still primarily rely on fundamental research, quantitative models are increasingly being integrated into investment strategies. There is a specific scheme in the mutual fund category focused on quantitative methods, which collectively manages approximately 10,000 crore rupees. Furthermore, several other actively managed funds also utilize quantitative tools to varying degrees.

Maini added that artificial intelligence (AI) accelerates and simplifies quantitative research, helping specialists analyze information, formulate hypotheses, test different scenarios, and automate parts of the research process. However, he warned that broader access to technology does not guarantee a sustainable investment advantage.

He concluded that 'speed does not equal understanding,' noting that as access to AI tools expands, the importance of the quality of questions asked, the discipline of the research process, and the ability to make decisions when evaluating results will increase.