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There is a lot of interest among Indian retail investors in India to trade algorithmically

Author: Kumar Shankar Roy/Wednesday, November 6, 2019/Categories: Exclusive

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There is a lot of interest among Indian retail investors in India to trade algorithmically

Is algorithmic trading strategy suitable for retail investors?

In a growing market like India, there is a lot of interest among Indian retail investors to trade algorithmically. There is so much buzz around the markets these days that everybody wants to know more about it and explore it in some form or the other. However, until now, this aspect of trading was the privilege of a selected few. To understand the factors generating a trade algorithmically and to understand the different strategies of trading, the investor needs to be a bit matured (in terms of his experience in the market), have a sound knowledge of trading and investment.

It might not be immediately suitable for all retail investors, but with the new age products that we have designed which use Artificial Intelligence, Factor Research of our methodologies which we have fine-tuned with over our 100 years of research of the US market and our experience of operating and tracking over 80 markets globally, we are looking forward to helping retail investors get the experience of investing algorithmically.

What is the regulatory view on algo trading solutions for retail investors?

The regulation side is evolving pretty fast and Indian regulators are trying to create a framework and guidelines for retail investors to trade algorithmically. We are a registered investment advisor and all the mandates and guidelines issued by Sebi has been taken care of by us in our product AlgoSmith. Sebi mandates that the final order execution of the algos has to be made by the client directly and we ensure and facilitate it for the clients to execute the orders directly by providing seamless broker connectivity.

What are the pros and cons of algorithmic trading strategy?

There are various positives of Algorithmic trading. It eliminates human biases, thus leading to objective trading. It can be tested on historical data before using it, and it minimizes the time used to track a large volume of the price of stocks. Last but not least, it trades automatically, saving time and effort of a human element.

If you look at the flip side, this kind of trading is not suitable for all. You need to have a decent size of capital to be deployed for investment and trading. Investors also need to have a fair amount of knowledge on different trading strategies and a fair deal of knowledge about how to develop algos and test it. Execution and speed is the key for any kind of Algos and clients need to have pretty fast computer hardware to be able to trade fast.
 

You have recently launched AlgoSmith. How is AlgoSmith different from existing trading strategies?

AlgoSmith is an end-to-end solution to retail investors. It provides them our back-tested proprietary algorithms for retail investors which allow them to get the right stock ideas, how much to invest etc. It also provides them with rebalancing strategies along with seamless broker connectivity to execute the orders.

It is designed keeping in mind the retail investors, to help them experience and use different types of algorithms as per their risk appetite and the available investment capital. The different algos in AlgoSmith perform complex operations in the background using O’Neil Research Methodology for stock selection and allocation. The retail investor simply has to evaluate the stocks that the algos are generating and click a couple of buttons to execute the trade through his broker platform.

AlgoSmith currently has four different algos - value, growth and a couple of other algorithms that uses William O Neil’s proprietary factor research and stock selection modules, which the customer can choose among the four based on their risk appetite, capital inducement, and investment horizon.

Unlike other algos or trading strategies, in AlgoSmith, the retail investor does not need to design anything nor go through the complex process of formulating strategies, back-testing it and then developing the algo and follow a compliance process set by regulators. The algos in AlgoSmith are readymade and executable algorithms. The investor simply has to connect his broker account and start investing. He/she definitely needs to follow the rebalancing instructions thrown by the algos whenever the algo feels there is a rebalancing required because of market action.

What safeguards have been built in AlgoSmith so that retail investors do not incur sharp losses due to algo trading?

All algorithms in AlgoSmith has been properly back-tested and all risk mitigation has been factored in. However, the investor has to choose the right algo based on their risk appetite and the capital he wants to invest.

We do a thorough risk-profiling of each and every customer, but in the end, the customer is responsible for selecting the right algo as per his requirement and executing it through his broker account. Like any equity investment, all the algos are subject to market risks and volatility and might not be suitable to each and every investor. However in the long run, the investor will be able to generate better returns.  

Our algo strategies are rebalanced frequently. We track all the stocks in our algos and look for weaknesses if any. Some of our algos are actively managed while few are not. On the actively managed algos, our customers would get a notification asking him/her to sell weak stocks and buy better stocks. For others, they would get a notification at the end of the time period asking them to re-adjust the portfolio, sell weaker stocks and buy stronger ones.

Why have you combined AI forecasting capabilities with human selection of stocks? Doesn't human intervention comes with emotional biases?

Three of our algos do not include human selection of stocks. Having said that, Algo Frog involves human selection of stocks which helps in investing in a well-researched list of stocks, but its in-built rules take care of the human biases arising during buying/selling stocks. Especially with respect to booking profit or loss. CAN SLIM itself is a rule-based approach which helps eliminate human biases by having rules for buying and selling stocks.

Artificial Intelligence eliminates these biases as it can process a lot of information about the stock, its historical performance, its price points, its earnings, its estimates, the news and the performance of the industry, in the flash of a second and come to an objective conclusion. It takes many factors into consideration which a human mind will not be able to process and hence is able to interpret the right action for the stock, which more than often is correct.

Our algos do have some element of human intervention, but that to a maximum action is limited to some element of stock selection, but apart from that maximum of the decision is done using artificial intelligence.

Can you share some examples of algo strategies that will be used?

To start with, we have four different strategies and we are working on identifying more. Our current algos are designed to suit different investors with different types of risk appetite and investment horizon viz, Blue Whale, Turtle Growth, Turtle Value and Frog.

Our Portfolio Managers and Quant & Research Team study various research papers and empirically test multiple algorithms and strategies to identify the best performing portfolio of stocks. In addition, we also consider market conditions, chart patterns, supply, and demand, etc. We follow a systematic, rule-based methodology to avoid any human bias in selecting companies for the portfolio. Our approach is based on over 50 years of research. All Algos are checked for historical out-performance to ensure that only consistently outperforming strategies are selected.

What will be the minimum capital requirement for using a solution like AlgoSmith? How can retail investors come on board?

None of our algos need a high volume of capital. Investors can start with a minimum capital of around 30 to 40 thousand and top it up as and when they feel comfortable. Investors simply need to register with the AlgoSmith platform and subscribe to our algorithms. Once they subscribe, they can link their broker account to execute the algos. 

We currently have around 7 top-rated brokers integrated into our system and is in the process of integrating a few more of them. If the customer does not have an account with any of the broker listed on our platform, he needs to open an account with the registered brokers and then he will be ready to invest using our algos.
 

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