IDFC Neo Equity

Scheme Rating

IME Scheme Rating

The Scheme does not meet our selection criteria at this time

Not a recommended fund: This is not a recommended fund, primarily because the AMC does not meet our selection criteria. We believe that there are better fund houses to invest in, within the Indian mutual fund universe.

IME Strategy Rating

Quant-based Investment Strategy: Have taken the approach of running an AI quant-based investment approach. Strategy is too young to be proven. Pedigree to be established based on the longer-term track of the algorithm.

PMS Scheme Ratings are driven by IME’s Proprietary Scheme Rating Methodology, which takes into account our ratings of the Scheme’s investment strategy, its maturity, the investment team, and our separate rating on the AMC that runs this particular scheme. Our views on each of these individual criteria are available via the IME RMS – which you can view by reaching out to one of our relationship managers (using either the live chat or book appointment feature on this site).

IME View on IDFC Neo Equity

Type: Large Cap | Quant | AUM (38.2 cr) | Inc Date (11 Jul 2017)

IDFC Neo Equity Portfolio- Investment Strategy

IDFC Neo Equity is a multi-cap strategy. The strategy uses artificial intelligence and a machine learning-based investment process. The portfolio is agnostic to any one specific theme or investment style. It attempts to combine macro themes and bottom-up alpha generation with a focus on the low correlation between portfolio holdings, downside volatility control, and portfolio liquidity.

Investment ‘Score’ Framework 

  • Sourcing: Sourcing, screening and analysing multiple datasets to identify factors that influence returns of a stock. 
  • Cleaning: Clean and curate data for analysis to meet investment requirements of generating potential sources of alpha. 
  • Optimum Portfolio: Optimum Portfolio identified to be included in the portfolio. 
  • Risk Management: ongoing risk management of portfolio to maintain desired risk-reward balance. 
  • Evolution: Machine learning process continuously learns and keeps evolving to improve its portfolio management ability.  

Investment Process

  • Step 1: The portfolio manager may introduce filters and eliminate stocks from the S&P BSE 200 universe based on prevailing market conditions. 
  • Step 2: The machine identifies the right mix of attributes in stocks. Then selects the optimal one with the best risk-reward balance. 
  • Step 3: Best stocks (as per the machine output) are algorithmically assigned weights. 

Trailing Performance

1yr 3yr 5yr Since Inception
IDFC Neo Equity 35.6 15.8 15.5 10.2
S&P BSE 500 TRI 39.5 19.5 19 14.4
Alpha over Broad Mkt BM -3.9 -3.7 -3.5 -4.2
Nifty 50 TRI 28.5 16.2 16.7
Alpha over Category BM 7.1 -0.4 -1.2

Performance as of: 28-Feb-23 | Inception Date: 11-Jul-17

Fund Managers

Chetan Mehra | 4-star rated FM

Fund Manager

Chetan Mehra is a data scientist with 2 decades of experience in quantitative analysis and in building trading models. He holds a Ph. D. in Computer Science, Multi-agent Systems in Computational Finance from the University of Southampton and an MBA in Finance from the University of Leeds. His Ph.D. focussed on a data science approach to capturing structure in data to build smart portfolios. Mehra has managed global futures, equity, and multi-asset portfolios as well as had trading experience across asset classes.

Vijay K | 4-star rated FM

Director & Head, Liquid Alternatives & PMS | 24 yrs Experience | 7 yrs at current firm

Mr. Vijay Krishna Kumar is an early pioneer and a specialist with a 12-year track record in India Long/Short investing and has a total global investment experience of almost two decades.Before joining IDFC AMC, Mr. Kumar was the Director of Mumbai-based Gulmohar Alpha Capital Advisors and Senior Portfolio Manager of Swiss based multi-manager SteppenWolf Capital LLC. During his time there, he won awards for ‚ÄòBest Emerging Markets Investor ‚ India’ and ‚ÄòBest India Long/Short’ by AI Hedge in 2016. Prior to this, he was the CIO and Portfolio Manager for The Chatterjee Group’s public equities division (TCG, a Soros spinoff). During his tenure, TCG IndiaStar was ranked number two by Eurekahedge in its peer group. Before that, he was the Co-CIO of the AGRA India Fund (PCE Investors, London), seeded by New Alpha Advisers, a consortium of blue-chip European insurance companies. Mr. Kumar holds a Masters in Corporate and International Finance from Durham University, UK.

Fee Structure

Fee StructureFee
Fixed Fee Structure2.5
Variable Fee Structures0% fixed + 20% above 12% hurdle
Exit Fees1yr(3%), 2yr(2%), 3yr(1%)


AMC: IDFC PMS (click link for detailed AMC review)

Not a Recommended AMC: IDFC PMS has taken a unique approach to follow an AI-driven investment style. We like the fact that an AMC with established credentials in traditional fundamental research, has not gone the standard route of other AMC-promoted PMS's of launching PMS portfolios on the back of their in-house mutual fund strengths. While this is clearly an interesting & innovative approach, whether the AI-driven PMS of IDFC does manage to deliver outperformance in real-life markets is still unproven. It is yet too early to recommend investments in IDFC PMS.

IDFC PMS does not meet our criteria for PMS AMC Selection at this time. Understand our AMC rating criteria at AMC Rating Criteria or contact us via the LiveChat to learn more.

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