AI sees slow adoption in stock market trading

Industry experts said there is some market interest in using AI in analytics and end-user features, but much of it is still in its infancy.

These include fundamental issues that plague many brokerages, said Tejas Khode, co-founder and CEO of BrokerageFires.

“Brokerages are still focused on using technology to reduce latency, and make their platforms safe from the dangers of downtimes and crashing – events that can cause massive losses. For brokerages It is not impossible to invest in building AI recommendation and analysis models on our own platform similar to the available charts and data, but this will be a factor when the market creates demand for tech-driven advice,” he added.

Sonam Srivastava, founder of equity research and advisory firm Right Research, agreed, “While we clearly rely on using AI to analyze data and create trends, we feed our machine learning systems “Our market is still stagnant. It’s not ready for AI to become a standalone factor for which investors will flock to a platform,” he said.

Both executives highlighted key factors in how the stock market operates, due to which the AI ​​upstart hasn’t seen its growth spurt. For most funds, technical expenses are centered around fundamental infrastructure, or distributed to clients through human brokers and advisors after data is used to perform statistical analysis. As Srivastava said, about 90% of his clients approach him to benefit from his nearly two decades of experience as a market researcher and consultant – and not for the AI ​​or technology component of his offering.

As a result, companies are shying away from investing in AI to promote customer offerings, as customers are wary of trusting AI to invest on their own.

It also stems from the way the market functions, according to market traders. Abhay Bhatia, a Mumbai-based trader and investor, said that one of the major reasons why AI is not an immediate hit in the stock market is how market trends work.

“In a market environment where there are clear trends, it is easy to use AI to project how a stock might perform, and invest accordingly. However, in an edge market, where large out-of-turn crashes occur, or irregularities are caused by external factors, AI may not be a factor that can be fully relied upon, and human intervention is always required. ” They said.

Bhatia said that there has been an increase in the use of AI in the stock market, with algorithmic trading currently accounting for about 10% of the total market volume. However, both Srivastava and Bhatia confirm that the market size for investors interested in using AI is temporarily small, which automatically makes it difficult for brokerages and advisory firms to obtain a return on investment (ROI) in AI technologies. Translates to a smaller opportunity to do.

Despite this, startups have continued to play in this space, currently addressing a small market size in India. Sumit Chanda, chief executive of Mumbai-based AI-based investment advisory firm Jarvis Invest, said the company’s machine learning tool seeks to make value predictions based on 12 million parameters, a factor that has seen the company grow over the past year. Jarvis grew from 1,820 users in March last year to 4,900 users, representing a 2.7x increase. The company currently has 110 crore of the total investment portfolio under its management.

However, Bengaluru-based AnaStrat, which uses AI to offer post-trading analysis of investment decisions made by users, has not seen such rapid growth, and is looking to diversify. Mohit Golecha, co-founder, Anastrat, said the overall growth has been slow, “but it has been largely fueled by the stock market consolidation over the last one year.” As a result, the firm has harnessed its AI. Platform to create a virtual investment learning environment – ​​a simulation where users can access AI analytics, learn to use them and make virtual investment decisions before actually trading in the market.