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This start-up is helping retail investors make money via algorithm trading

Retail investors are also warming up to the idea with many discount brokerages and start-ups offering them algo trading platforms.

Aprajita Sharma  New Delhi     Last Updated: December 3, 2018  | 17:58 IST
This start-up is helping retail investors make money via algorithm trading
From left: (Mohit Bansal, Ayush Gangwar and Pankaj Chopra)

Algorithm trading is no longer the sole turf of institutional traders, brokers and big fund houses. Retail investors are also warming up to the idea with many discount brokerages and start-ups offering them algo trading platforms.

The challenges, however, still exist for those who cannot code themselves or are not tech-savvy enough to make use of algorithms already available on these platforms.

Kuants, an early stage fintech start-up, is filling this gap. Co-founded by Ayush Gangwar and Mohit Bansal in December 2017, Kuants already has a pool of five Sebi-approved algorithms to trade on their platform.

"For retail investors, we are a ready-made and an aggressive mutual fund... a verified tool, where they can safely place their money. Investors just have to put money and forget about it. We shall trade on their behalf and earn profits for them," says Gangwar.

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Pankaj Chopra, an investor in Kuants and mentors to the co-founders, says, "Our USP is we shall trade for a client, advising them to stay invested with us for at least a year for attractive returns."

There is no minimum investment bar, he says, adding anyone with as low as Rs 10,000 to as high as Rs 10 crore can come to us.

Kuants has tied up with brokerage Motilal Oswal Securities Ltd (MOSL) as a sub-broker. Investors willing to trade on Kuants' platform would need to open a D-mat account with MOSL. "We trade on behalf of clients via MOSL through our own system," explains Chopra.

Currently, we are handling 23 accounts, 50 per cent of which are live, he informs.

Kuants also provides back-testing facility to those who can code themselves. "Users can apply their quantitative skills into developing trading algorithms and back-testing them on our platforms," says Gangwar. Currently, over 800 users are there on its back-testing platform.

Kuants also allows users to submit their strategies on their marketplace.  "The users will be able to select a pre-developed strategy and live trade on it with no manual intervention required."

The marketplace is currently a controlled group, running as a pilot project and the company plans to expand it after validation and availability of trading strategies.

Revenue model

Kuants is at a pre-revenue stage right now, but will have three components to its revenue model:

  1. Brokerage sharing model with MOSL.
  2. Profit sharing with customers: After Kuants meets the minimum return expectation of a client, the return above that will get split between investor and Kuants.
  3. Proprietary trading: Kuants trades with its own captive money to generate profits for itself.

"All the services were launched with a 3-month free trial, which led to extensive growth in numbers and the all-important feedback from our users. We already have seen an increase in user-base by 34 per cent in November itself," says Chopra, adding the monetisation of the services will begin from Jan 2019.

Kuants has a target to achieve monthly recurring revenue of Rs 65 lakh and Rs 3.7 crore in FY19 and FY20, respectively.

So far, the start-up has received a total angel investment of Rs 25.5 lakh and is currently raising its seed round.

For uninitiated, algorithmic trading is a method of executing a large order (too large to fill all at once) using automated and pre-programmed trading instructions that don't require human intervention. Popular algos include Time Weighted Average Price (TWAP), Volume Weighted Average Price (VWAP), Per cent of Value (PoV), Implementation Shortfall, Target Close, etc.

According to a study by National Institute of Financial Management (NIFM), around 50 per cent plus of total orders at both NSE and BSE are algo trades on the client side, while on the proprietary side, algo trades consist 40 per cent plus of total orders placed at both the exchanges.

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