Introduction
Interest in factor investment solutions have significantly risen in the past decade. In general, factor investing refers to an approach that targets stock characteristics that drive the difference in expected returns over the long term. Sometimes, factor investing is referred to as smart beta, or strategic beta, because the factor approach will deviate the underlying portfolio from the market portfolio (the market beta) in a systematic method. Some of the common factors that have been well documented in academic literature and adopted by the investment industry include low volatility, momentum, quality and value. Most of the evidence has been strong and promising that those factors can generate excess returns over the historical sample periods. As of March 31, 2022, factor ETFs managed about USD 1.6 trillion assets globally, a 24.6% CAGR compared with the USD 178 billion 10 years ago.
How did these factors perform in the Indian market? Can investors access factor performance through an indexing approach? What are some applications of factor indices in the Indian market? In this paper, we introduce the S&P BSE Factor Index Series, which implements the factor investing framework through an indexing approach to reflect the performance of the low volatility, momentum, quality and value factors.
In the following four sections, we provide brief descriptions of the S&P Dow Jones Indices (S&P DJI) approach to each of the common factors. We will then provide an extensive discussion on the performance of the four factor indices, and a potential approach to combining the four factor indices to form an alternative for core equity allocation.
In each of the introductory sections, we follow the same framework to present the factors. The underlying index universe to construct the S&P BSE Factor Index Series is the S&P BSE LargeMidCap, which is designed to represent the top 85% of the total market cap of the S&P BSE AllCap. The S&P BSE LargeMidCap was launched in 2015, with the first value available in September 2005, so we use back-tested historical data starting on Sept. 30, 2005, to study the full sample period performance of each factor. Every six months, at month-end in March and September, we sort the constituents of the S&P BSE LargeMidCap in order by each factor. We then form equal-weighted quintiles and market-cap-weighted quintiles from those sorted values, denoting Quintile 1 as the stocks with the highest exposure to the factor and Quintile 5 as the stocks with the lowest exposure. We are interested in whether Quintile 1 generates better performance than Quintile 5. The performance of Quintile 1 tends to be more important, especially for long-only investors. We analyze the performance from both the annualized compound return and the risk-adjusted return perspectives.
