How can we improve quant trading for retail traders?
Indian Capital Markets is a huge ecosystem. Till November 2020, the total trading volume was Rs. 3300 Lac Crore. A lion’s share of this volume is intraday trading (buy/sell the same day)
The split between institution traders(Mutual Funds, Insurance, Banks etc) and retail traders (common people like us) is not always clearly defined. Common wisdom says that retail traders’ contribution is between 20–30%. This means common folks like us trade about Rs. 825 Lac Crore volume every year.
As per our research, close to 95% of intraday-retail traders lose money. There are a couple of reasons for this —
Retail traders are unable to access high-quality research which is generally reserved for large institutions and UHNIs
Majority retail traders punch in orders manually which leads to human errors
Most retail traders doing their own research are using tools and techniques that no longer work in today’s information explosion age
This is a widespread issue in a 145 years old industry (BSE launched in 1875). Many genuine players have tried to solve these problems. Let’s classify them into 2 categories
Do it yourself (DIY)
These tools allow traders to create their own trading rules using little to no coding. It’s an excellent approach with a lot of potential. However, in our market testing people’s reaction to such a tool was :
Although the interface (UI / UX) is simple to use but making the right rules is difficult. Only a tiny fraction of people would actually know what they are doing and the others hope they stumble upon rules that can make money.
Algo Trading Platform
To overcome the previous problem of creating trading strategies, these platforms have community-generated strategies. This is an amazing idea to crowd-source intelligence. But, from our market research, the reaction of customers was:
In theory, this idea has many merits but suffers from drastic quality issues. Additionally, most traders find it incredibly difficult to select the right strategy out of the hundreds of strategies on sale. This is a decision overload situation.
A common problem across both types of players is complex order execution. There’s some manual work required which makes it prone to human errors. Some companies also request for the password of customer’s broking account to automate orders — which is illegal as per SEBI regulations.
Some pioneering companies integrate with brokers to automate trades. This solves the problem of manual order entry and is the future of broking in India.
However, the major issue remains unsolved — providing high-quality research to retail traders.
Decades ago, mutual funds were created to solve a similar problem. Retail investors were unable to pick the right stocks and fund managers would make these decisions for them. You can think mutual funds as a Portfolio Management Service (PMS) service for common investors.
Then there are AIF Cat III funds created by SEBI. This is a quant or hedge fund that use sophisticated trading strategies. However, the minimum investment ticket size in an AIF Cat III fund is Rs. 1 Crore, far beyond the reach of retail traders. There are no alternatives to AIF Cat III for retail traders. This is partly due to SEBI’s efforts to protect them. The trading market is stigmatised because of dishonest players defrauding their customers with false promises.
We need to get creative and create solutions whose quality & convenience can match hedge funds and at the same time respect the guidelines set by SEBI. Only by collaborating with various stakeholders in this ecosystem can this be achieved.