This study aims to investigate the influence of the time on the efficiency of Indian capital markets and to propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market.
Authors
Sarveshwar Kumar Inani, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Gaurav Nagpal, Department of Management BITS Pilani, Pilani, India.
Ankita Nagpal, Department of Management BITS Pilani, Pilani, India.
Ritik Gupta, Department of Finance and Economics BITS Pilani, Pilani, India.
Samyak Jain, Department of Finance and Economics BITS Pilani, Pilani, India.
Sanjana Khowal, Department of Finance and Economics BITS Pilani, Pilani, India.
Saurabh Shahdadpuri, Department of Finance and Economics BITS Pilani, Pilani, India.
Summary
This study aims to investigate the influence of the time on the efficiency of Indian capital markets and to propose a recommendation engine that can assist as a feedback system for better investment actions and an efficient capital market. It uses the data comprising fifty stocks listed on the National Stock Exchange over a period from Jan’2015 to Dec’2020 to determine the capital market efficiency and its trends using three techniques: correlation test, residuals test, and runs test.
The proposed recommendation engine can generate the implications of contemporary events on the stock prices which can further bring the pricing errors to the surface faster. It can also assist in enhancing the capital market’s efficiency which leads to a reduction of arbitrage opportunities and faster removal of pricing anomalies in the market.
Published in: 2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)
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