Abstract
The study empirically investigates two theories that claim to explain the low-risk effect in Indian equity markets using a universe of stocks listed on the National Stock Exchange of India (NSE) from January 2000 to September 2018. Leverage constraints and preference for lottery are two major competing theories that explain the presence and persistence of the low-risk effect. While the leverage constraints theory argues that systematic risk drives low-risk anomaly and therefore risk should be measured using beta, lottery demand theory claims that irrational investor’s preference towards stocks with lottery-like payoffs is responsible for the persistence of the low-risk effect, and risk should be measured by idiosyncratic volatility. However, given that most of the risk measures are highly correlated, it is not easy to precisely measure a specific theory’s contribution to explaining the low-risk effect. The study constructs the Betting against correlation (BAC) factor to measure the contribution of leverage constraints to the low-risk effect. It further constructs the SMAX factor to untangle the contribution of lottery preference theory. The results show that leverage constraints theory predominantly explains the low-risk effect in Indian markets. This study contributes significantly to the body of literature, as this is the first such study on the Indian market, one of the major emerging markets, especially when the debate on theories explaining the low-risk effect is yet to settle.
Highlights
The Capital Asset Pricing Model (CAPM) predicts a positive relationship between an investment’s risk and its estimated return
While the leverage constraints theory argues that systematic risk drives low-risk anomaly and risk should be measured using beta, lottery demand theory claims that irrational investor’s preference towards stocks with lottery-like payoffs is responsible for the persistence of the low-risk effect, and risk should be measured by idiosyncratic volatility
This observation this study examines the performance of is consistent with Joshipura and Peswani’s (2017) the MAX factor in the Indian equity market
Summary
The Capital Asset Pricing Model (CAPM) predicts a positive relationship between an investment’s risk and its estimated return. The low-risk effect persists over several years despite investors wanting to earn higher returns at a lower risk It is prevalent across developed and emerging markets and within various asset classes. Understanding whether and how the low-risk effect or any other known factor manifests in Indian markets compared to its developed and other large emerging markets is vital for global and Indian investors’ community With this objective, the study investigates the following questions: 1) Is the low-risk effect measured by BAB and MAX factor present in the Indian equity markets?. 4) Which theory explains the low-risk effect in India – leverage constraints or lottery preference?. The effect is unique, and none of the established factors can explain it entirely It delivers positive risk-adjusted returns irrespective of the risk measure used to create the low-risk factor (BAB or MAX). The rest of the paper is organized as follows: Section 1 consists of the literature review, section 2 presents the data and the empirical model, section 3 presents the results and discussions, and the last section provides the conclusion
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
