September 7, 2021

Rule-Based Active Investing: Bringing Method to the Market

Rajiv Shastri

Director & Chief Executive Officer, NJ Asset Management Private Limited

Traditional investment portfolios are constructed using a combination of indexing and discretionary investing. Indexing refers to the replication of popular indexes through Index Funds or Exchange Traded Funds. The composition of these indexes is typically based on market capitalization and indexing allows investors to acquire a “market” portfolio and benefit from “market” returns in a disciplined and transparent manner. By contrast, discretionary investing relies on experts to select the right stocks. This offer potentially higher returns, but at the cost of lower discipline and higher fees.

Over recent years across developed markets, asset managers are employing a new approach to portfolio construction: rule-based active investing (also known as smart beta or factor investing). This investment approach takes the best of indexing and discretionary investing. The result is an approach that offers the best of both worlds; transparency, discipline, and potential outperformance.

Rule-based active investing relies on creating rules and following them. Unlike discretionary investing which focuses itself on stock selection, rule-based active investing focuses on the creation of rules. In this process, stock selection is just a system-driven outcome. Research into rules starts with the identification of common attributes observed in outperforming stocks. Criteria to measure these attributes are developed and rules are defined based on these criteria. These rules are tested and validated based on past data to determine effectiveness and efficiency. Finally, complementary rules for various desirable attributes are combined into a protocol. Stocks are selected and weighted based on this protocol to become the portfolio without any human discretion or bias.

An ongoing effort is focused on optimizing existing rules & developing new ones. As data accumulates and technology evolves, new insights emerge which allow more efficient and effective rules. Pursuing these is a constant, unending endeavor.

A significant advantage of rule-based active investing is the ability to simulate the performance of these rules on past data to determine its performance characteristics. Another important benefit is that since stocks are selected on the basis of established rules, the portfolio always remains true to its label. This builds awareness of possible performance variations in managers and investors in advance.

Globally, the presence of rule-based active investing is growing. According to Morningstar, $710 billion was invested in strategic beta ETFs (a proxy for rule-based investment) as of December 31, 2017. With over 700 strategic beta ETFs on offer today, they now account for 21% of all ETF assets, up from 14% in 2010. More advisors and investors are coming to appreciate the value of incorporating rule-based active into investment portfolios.

In India, data availability has grown steadily across the last couple of decades. Combined with the latest advances in technology for analyzing big data sets, rule-based active investing is now not only possible here but can prove to be an attractive diversification opportunity to investors who currently allocate almost all their investments to discretionary funds.

Disclaimer: Mr. Rajiv Shastri is Director and Chief Executive Officer of NJ Asset Management Private Limited and the views expressed above are his own. The views provided above should not be construed as investment advice. Investors must make their own investment decision based on their specific investment objectives and financial position. The opinion expressed are not necessarily those of NJ Asset Management Private Limited (NJAMPL) and consequently, NJAMPL or any of its Directors, Officers, Employees, and personnel do not accept any responsibility for the editorial content or its accuracy, completeness, or reliability and hereby disclaim any liability with regards to the same.