Alta Cura AI Absolute Return Fund AIF
Alta Cura AIF | Alternatives | | AIFIME's View on Alta Cura AI Absolute Return Fund AIF
Strategy
Strategy focused on market-neutral buckets
Investment Fund
While we are cognizant of the relatively young age of the strategy, we gain comfort from the strong pedigree of the investment team and the demonstrated performance using quant algorithms at Accuracap
Fund's Strategy View
The strategy comprises 4 trading strategy buckets, all primarily focused on market-neutral trades that support absolute return generation. The aim is to earn equity-like returns, with no negative years and returns uncorrelated to the markets. The strong quant credentials of the founder Raman Nagpal, along with a proven algorithm at Accuracap that has been modified for more absolute return strategies, are clear positives for the strategy.
Fund Performance
We refrain from evaluating the fund since it is yet to mature (less than 5 years).
IME's View on Alta Cura AIF
View on AMC
Alta Cura offers a highly differentiated absolute return focussed quant strategy. The strong pedigree of the investment team and the demonstrated performance using quant algorithms at Accuracap gives the AMC credibility despite being a relatively young AMC.
AMC's Pedigree
Alta Cura is a very young AMC, however, the fact that Raman Nagpal has co-built Accuracap has demonstrated the value of Raman's algorithms and provides a level of comfort and credibility to the AMC.
AMC Team
Raman Nagpal has a Masters in Computer Science and has worked in data science at Adobe, prior to setting up Accuracap along with Naresh Gupta. At AccuraCap Raman has developed strong investment credential over the past decade.
Investment Philosophy
While the foundation of Alta Cura's algorithms comes from proven AI algorithms at Accuracap, the adaption of these algos to a more trading-heavy absolute return strategy is still in the early days. The longer-term track record of these algorithms across different market conditions is still to be established.
Investment Strategy
Return Objectives
- Equity-like returns: Target gross returns of 15% or higher.
- Debt-plus risk profile: Aim to avoid negative returns in any given year.
- Market-uncorrelated returns: Seek positive returns across bull, bear, and sideways markets.
Four Investment Buckets
- C1 – Liquid & Liquid-like Investments: Allocation to very low-risk debt instruments such as bank fixed deposits, debt mutual funds, and government securities. Provides stable fixed-income returns and serves as margin capital for market-neutral strategies.
- C2 – Market-Neutral Arbitrage Strategies: Deployment of arbitrage-style option strategies including calendar spreads, time-decay trades, and volatility dispersion to exploit pricing inefficiencies across options with the same underlying.
- C3 – Long–Short Equity Portfolio: Construction of long–short positions by buying stocks expected to outperform and selling stocks expected to underperform, based on AI-driven signals, with the objective of maintaining low net market exposure.
- C4 – AI & ML–Based Bi-Directional Strategies: Use of AI models to determine market outlook (positive, stable, or negative) and execute hedged F&O strategies designed to generate alpha across different market regimes.
Investment Bucket Allocation
C1 is typically fully invested to provide stability and margin support. Allocations to C2, C3, and C4 are dynamically adjusted based on AI-driven market outlook, with exposure to any single bucket capped at 40% of the overall portfolio.
Investment Philosophy
The strategy is driven by Artificial Intelligence and machine learning–based algorithms designed to identify profitable absolute return opportunities. These algorithms are built using a large number of indicators and advanced data science techniques, with continuous learning embedded to improve predictive accuracy over time. The models are developed by a credible and technically strong team led by Raman Nagpal, who holds a Master’s degree in Computer Science and previously worked in data science roles at Adobe, alongside co-founder Naresh Gupta. The underlying AI framework has demonstrated consistent outperformance in Accuracap’s long-only strategies over more than a decade and has been adapted for absolute return objectives.
While the algorithmic foundation is derived from proven systems, the application of these models to a more trading-intensive absolute return strategy is still in the early stages. As a result, the longer-term performance of the strategy across multiple market cycles remains to be fully established.
Trailing Performance
| 1yr | 3yr | 5yr | Since Inception | |
|---|---|---|---|---|
| Alta Cura AI Absolute Return Fund AIF | 11 | 13.8 | 14.1 |
Performance as of: 30-Nov-25 | Inception Date: 01-Nov-21 | Performance are post-fees, pre-taxes. Global funds denominated in USD or fund currency.
Investment team
Sanjiv Syal | 3-star rated FM
Fund Manager | 39 yrs Experience | 4 yrs at current firm
Past Experience: ABL Financial Services (Founder)
A derivatives trader and serial Entrepreneur, Sanjiv has a diverse experience spanning 35 years. Besides managing his proprietary trading book, his other core competencies include Strategic planning, Fund Raising, Relationship building, Operational excellence, and Project management. He has vast operational and fund-raising experience in vario us sectors including in Financial services, Information Technology and Real Estate. He holds a Bachelor of Commerce Honours from Shri Ram College of Commerce and is a qualified Chartered Accountant (1985).
Raman Nagpal | 5-star rated FM
Founder & CIO | 32 yrs Experience | 10 yrs at current firm
Past Experience: Morpria Alliance (Board of Directors), Adobe (Executive Director), AVP Technology (Founder)
Raman is a computer scientist, with a deep background in technology & finance. He has been responsible for developing several new technologies in the areas of adaptive learning engines, spurious drug detection systems and application of data analytics in stock markets. Prior to founding AccuraCap in 2015 along with Naresh Gupta, Raman worked along with him at Adobe as an Executive Director.
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