Funds managed
| Fund name | Asset Class | License |
| Alpha 10 | Public Equities (Large Cap) | PMS |
| Pico Power | Public Equities (Mid Cap) | PMS |
| Dynamo |
Alpha 10
- Inception Date: 19 September 2011
- Product Profile: The Investments under the strategy predominantly comprise of stocks having Larger Market Caps. The objective is to outperform the BSE 100 Index through constructing a relatively stable portfolio with high level of liquidity and lower impact cost.
- Universe of Investments: Stocks comprising the top 100 by market capitalization on BSE.
- No. of companies in the portfolio: Generally, 10 to 20
- Liquidity: High
- Return will be benchmarked against: BSE 100 Index
Pico Power
- Inception Date: 10 October 2011
- Product Profile: The strategy seeks to provide Long term capital appreciation by investing primarily in stocks having Small Market Caps with high growth potential. The objective of the strategy is to outperform the returns generated by BSE Small Cap Index.
- Universe of Investment Small Cap: All stocks below top 200 by market capitalization on BSE.
- No. of companies in the portfolio: Generally, 25 to 30.
- Return benchmarked against: BSE Small cap Index.
Recent performance can also be observed – http://www.accuracap.com/AccuraCap-performance.html#dynamo
Other licenses could be:
- Offshore fund based in Mauritius/Singapore
- AIF Category 1/2/3
About the AMC
- Founded in 2009. Led by Dr. Naresh Gupta and Raman Nagpal, both veteran computer scientists, entrepreneurs and global business executives, the original focus of the fund was to manage their proprietary funds.
- However, given the outperformance of its strategies over the years, Accuracap diversified into managing third party funds for HNIs, Family offices and institutional investors. Accuracap currently manages over $230 million of assets, primarily in the Indian public equity space
Key staff
- Dr. Naresh (Total experience – 29 years): Computer Scientist, and a prolific Researcher, Gold medalist from IIT-Kanpur and a Ph.D. from the University of Maryland.
- Raman Nagpal (Total Experience – 24 years): Bachelor’s in Computer Science from Delhi Institute of Technology, Master’s in Computer Science from BITS Pilani. Master’s in International Business and CFA, Certified Corporate Director from INSEAD Business School.
Investment Philosophy (for firm)
At the heart of the Investment System at Accuracap is the basic philosophy that a portfolio comprising of a bunch of high quality businesses with a “moat around their business model”, bought at a historically reasonable valuation and held for medium to long term will invariably beat the market and most other funds by a fair margin.
The key is to identify such high quality stocks very objectively and scientifically, invest into them but then not fall in love with any of these businesses, howsoever attractive they might have seemed at some point. Most great business stay great but some will deteriorate.
Every quarter, review the held portfolio for any possible deterioration in their business model, and exit any businesses that show clear signs of such deterioration. And keep doing this every quarter without giving credence to market sentiments or emotions.
Accuracap has evolved a unique ranking algorithm that conducts extensive “Spatio-temporal” analysis of every business in their investment universe, by comparing it against every other business over space and time. This helps to narrow down the list to some very high quality businesses. Next, using the very unique “Pendulum Hypothesis”, they buy these businesses at reasonable “reasonable valuation”. And then formulate equi-weight portfolios of such businesses.
The key strategy is to hold on to winning ideas and weed out losers at regular intervals based on the concept of spatial – temporal analysis (i.e. assessment of business relative to its rank within the sector, across sectors both the current point in time and over historical periods as well) with very limited scope envisaged for manual intervention. They have fully automated quant models.
Media
Title: Will AI eat the fund manager’s job in India? AccuraCap shows it will, Source: Factor Daily, Date: 27 March 2017
https://factordaily.com/ai-big-data-machine-learning-funds-fintech/
The Partners talk about their model, their history and firm’s history.The model runs on a mathematical model straddling big data analytics and artificial intelligence AccuraCap allocates and reviews portfolios once a year with quarterly rebalancing. Some of the data sheets in the AccuraCap model have gigabytes of data, not surprisingly.Then they talk about not going into details of the model which means sharing the data, which is also the reason they don’t want patents for the model, because it will make the data public. They also discuss about the philosophy from they got inspired, it’s a value investor’s philosophy Joel Greenblatt. They wanted to try this in India. They cited – ‘The conclusion was: if you look at the past performance of companies very closely and create a good portfolio based on that, you are going to be better off than trying to look into the future on what or how companies will do’.
Title: Anshu Kapoor: Head, Global Wealth Mgmt – Edelweiss, Source: Bloomberg, Date: 15 October 2015
https://www.youtube.com/watch?v=O4Qsf0izC6g
For edelweiss to enter the HNI segment, they tied up with AccuraCap, fund will be based on data and behavioural analytics. Edelweiss chose accuracap because they have automated strategy, made by the two very well experienced data scientists, very less human touch and very accurate and disciplined approach, their 4 year’s track record, which is audited by Morningstar. They followed equity long only strategy. Where their equity, debt ratio recommended was 70:30. Fees was 0.5% of the assets and the performance fees in addition. Then they talked about accuracap vs mutual funds, wherein sharpe ratio is higher than in the case of mutual funds. Fund has been outperforming MF’s on absolute returns.
Analyst questions
- What are the shortcomings of lacking human intervention in managing funds? Have you ever considered making a strategy wherein the handling would be hybrid as in partially done by humans and partially by an automated system?
- How do you make your investors believe in your strategy, how do they measure your track record? How do you pitch them about the strategy being fully automated?
- What kind of checks and balances do you have in place to gauge the working of the model?
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