IDFC Neo Equity Portfolio

The portfolio managers believe that investment management is about to witness a fundamental change with the advent of technology applied to data analysis & research, securities selection, and portfolio optimization. Machine learning can play beneficial roles in investment management, especially in applications where there is an abundance of data. IDFC NEO Equity Portfolio seeks to be an all-weather diversified large and mid-capitalized portfolio combining machine learning techniques with portfolio manager expertise. The portfolio will consist of large and mid-capitalized stocks from the S&P BSE 200 index stock universe and can constitute the core long-only equity exposures for clients.

The structure of the Neo investment process seeks to ensure that the Portfolio Manager defines filters and eliminates stocks from the S&P BSE 200 universe. This helps the AI system to identify the right stocks with the best risk-reward balance and algorithmically assign weights.

SCORE

S – Sourcing, Screening and analysing data sets

C – Cleaning and curating data which will be fed into the machine.

O – Optimum portfolio identification by the machine programmed by the portfolio manager.

R – Risk Management to maintain desired risk-reward balance.

E – Evolution of the machine by continuous learning for improving portfolio construction.

Not more than 10% of investment focused on one stock with an aim to minimise risk. Not more than 40% of investment focused on one sector with an aim to maintain optimal risk-reward balance.