ArthAlpha Machine Learning (Equity) Quant
Portfolio Management ServiceStrategy AUM
Trailing 1Y return
Trailing Returns
APMI · annualised beyond 1Y · as of 01 May 2026
- 1M
- +1.46%
- 3M
- +2.33%
- 6M
- +4.20%
- 9M
- —
- 1Y
- +5.38%
- 2Y
- —
- 3Y
- —
- 4Y
- —
- 5Y
- —
- Since Inception
- +5.93%
- Strategy AUM
- ₹60 Cr
- Benchmark
- BSE 500 TRI
Performance vs Benchmark
Strategy vs BSE 500 TRI · trailing returns, % · alpha = excess
| Period | Strategy | Benchmark | Alpha |
|---|---|---|---|
| 1 Month | +1.46% | −0.17% | +1.63% |
| 3 Months | +2.33% | −2.34% | +4.67% |
| 6 Months | +4.20% | −5.39% | +9.59% |
| 1 Year | +5.38% | −0.07% | +5.45% |
| 2 Years | +0.00% | +0.00% | +0.00% |
| 3 Years | +0.00% | +0.00% | +0.00% |
| 4 Years | +0.00% | +0.00% | +0.00% |
| 5 Years | +0.00% | +0.00% | +0.00% |
| Since Inception | +5.93% | +0.48% | +5.45% |
Monthly Performance
Growth of ₹100 invested · month-on-month · 13 months
| Month | Strategy | Benchmark | Alpha |
|---|---|---|---|
| May-2026 | +1.46% | −0.17% | +1.63% |
| Apr-2026 | +11.72% | +10.38% | +1.34% |
| Mar-2026 | −9.72% | −11.37% | +1.65% |
| Feb-2026 | +4.49% | +0.45% | +4.04% |
| Jan-2026 | −1.75% | −3.34% | +1.59% |
| Dec-2025 | −0.81% | −0.24% | −0.57% |
| Nov-2025 | −2.07% | +0.96% | −3.03% |
| Oct-2025 | +3.54% | +4.27% | −0.73% |
| Sep-2025 | +1.30% | +1.24% | +0.06% |
| Aug-2025 | −2.93% | −1.75% | −1.18% |
| Jul-2025 | −3.51% | −2.71% | −0.80% |
| Jun-2025 | +5.13% | +3.68% | +1.45% |
| May-2025 | +5.41% | +3.54% | +1.87% |
Strategy Details
APMI fact sheet
- Inception
- 29 Oct 2024
- Age
- 1.7 Years
- Min. investment
- ₹50,00,000
- Turnover (1Y)
- 8.46×
- Turnover (1M)
- 0.77×
- Product
- Equity
as of 31 May 2026
Asset classes
Investment objective
Long Term Wealth Creation.ArthAlpha MEQ is an advanced machine learning-driven quantitative investment strategy designed to identify market inefficiencies and generate superior risk-adjusted returns. By integrating expertise from multiple disciplines including fundamental analysis, quantitative finance, data science, and behavioral psychology. MEQ effectively uncovers mispricings in stock prices. This innovative approach enables the strategy to capitalize on market anomalies, ensuring optimized investment decisions with a focus on long-term performance and risk management.
Fund Managers
1 manager
Name
Rohit Beri
Experience
22.00 years
Fees & Investment
As disclosed to APMI
- Min. investment
- ₹50,00,000
- Fixed fees
- Not disclosed
- Variable fees
- Not disclosed
- Exit load
- Not disclosed
APMI does not publish a fee schedule for this strategy — confirm fees with the portfolio manager.
PMS Industry — SEBI
Latest monthly aggregate
- Total PMS AUM
- ₹44.11 Lakh Cr
- Total clients
- 2,23,279
- Discretionary
- ₹37.37 Lakh Cr
- Period
- july-2026
Industry AUM by asset class (top 5)
- Plain Debt Listed₹28.98 Lakh Cr
- Listed Equity₹7.60 Lakh Cr
- Plain Debt Unlisted₹5.00 Lakh Cr
- Mutual Funds₹1.93 Lakh Cr
- Others₹40,423 Cr
About
- Provider
- ArthAlpha LLP
- Strategy
- ArthAlpha Machine Learning (Equity) Quant
- Benchmark
- BSE 500 TRI
- Source
- APMI
Strategy performance, AUM, fees and fund-manager details are sourced from APMI (Association of Portfolio Managers in India); industry aggregates are from SEBI’s monthly PMS disclosures. Returns beyond one year are annualised; past performance is not indicative of future results, and a PMS strategy carries no capital guarantee. For information only, not investment advice.