Accura Cap PICO Power Fund

Accura Cap PICO Power Fund

Accura cap picopower original objective was to manage their own funds, and it was led by Dr. Nareshchand Gupta and Raman Nagpal, both senior computer scientists, entrepreneurs, and worldwide business executives. Accura Cap picopower Fund's fund managers are both highly qualified and experienced. Dr. Naresh Chand Gupta is a Computer Scientist and Researcher with more than 29 years of expertise. Raman Nagpal has 24 years of experience and holds Master's degrees in Computer Science and International Business, as well as being a CFA and a Certified Corporate Director, all from INSEAD.

Fund Snapshot

Year of Inception2011
Number of Stocks25-35
Investment Horizon3-5 years
Fund ManagersDr Naresh Chand Gupta and Raman Nagpal.

About Fund Managers

Mr. Naresh Gupta is a CEO and Mr. Raman Nagpal is a CIO of AccuraCap. Both the fund managers have high experience and qualification. Mr. Naresh Gupta, is a computer scientist and researcher having total experienced of 29 years. Mr. Raman Nagpal is CFA and a certified corporate director from INSEAD Business School, has received his master’s degree in international business and computer science have a total experienced of 24 years.


Unique Feature

A small to mid-cap fund based on an Artificial Intelligence-driven algorithm-based methodology

Accura cap, however, diversified into managing third-party funds for HNIs, Family offices, and institutional investors as a result of its strategies’ outperformance over time. Accuracap presently manages about $230 million in assets, with a focus on Indian public equity.

Alpha 10 and Pico Power are two methods. From the beginning, both strategies have outperformed the majority of funds in their respective categories in India. Almost every quarter, accura cap portfolio has consistently outperformed the market. Since 2009, accura prime opportunity fund has been used in the market with private funds, and since 2011, it has been used with public funds. Stock selection based on Big Data and Behavioral Analytics produced by prominent Computer Scientists and Business Executives over 15000 hours of in-depth research and supported by deep fundamental research.

A proprietary artificial intelligence-based algorithm that has been developed over ten years is used to choose candidates based on fundamental and technical criteria. According to market capitalization, the investment universe ranges from 101 to 500 enterprises. Return indicators such as long-term earnings trend and other financial health of balance sheet, as well as risk metrics such as promoter level risk, business growth risk, solvency, and liquidity risk, are used to value equities that are eventually added to the accura cap portfolio. The typical holding duration of accura cap portfolio is two years after low turnover. Short-term investments, derivatives, or leverage are prohibited, as is participation in initial public offerings (IPOs) and PSU stocks.

Investment Philosophy

A proprietary Artificial Intelligence-based algorithm developed over ten years drives the selection for Accura Cap PICO Power Fund. The fund focuses on companies ranked from 101 to 500 per market capitalisation.

Comprehensive valuation analysis is performed on return metrics, such as trend, long-term earnings, and risk metrics, such as liquidity risk, solvency, promoter level risk, business growth risk, and balance sheet’s financial strength. 


With the mission of committed to excellence in fund management with the use of world class technology, the focus of the fund is to manage their proprietary fund. With the outperforming strategies, AccuraCap has diversified into managing third party funds for HNIs, institutional investors and Family offices. Accuracap currently manages over $230 million of assets, primarily in the Indian public equity space.

Accuracap have 2 strategies namely- Alpha 10 and Pico power. Both the strategies have outperformed in their respective fields. For PMS and AIF, the stock selection is done on the basis of behavioral analytics and big data by authorized computer scientist and business executives with the time span of over 15000 hours of in-depth research thesis and supported by in-depth fundamental research.