Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The classical view of experts associates greater risks with greater rewards. The present study explores whether increased volatility in portfolios can create more returns for investors by using technical indicators or the buy-and-hold (BH) strategy. The study used closing prices of National Stock Exchange (NSE) 500 index firms for a period of 16 years (2007–2022). Five portfolios ranging from low to high volatility were created using standard deviation as a key measure. Findings indicate that as the volatility of the portfolios increases, the moving average (MA) returns seem to be higher. Across the various MA time frames, the 20-day MA seems to have generated the highest return annually (36.53% before transaction costs and 31.05% after transaction costs) due to reasonable trading opportunities with adjustable transaction costs. The CAPM also generated positive alpha (after bearing transaction costs) in the case of 20, 50, and 100 days MA, with the values being 16.66%, 13.29%, and 12.09%, respectively, in the case of highly volatile portfolios. On the other hand, while the BH strategy created substantial returns in all scenarios, the risk factor was extremely high due to the high standard deviation. Hence, it is suggested that investors/traders consider the BH strategy more cautiously while choosing between technical analysis returns and BH returns. Investors with high-risk preferences may have BH as their choice, while day traders with managed risk appetites may prefer technical tools over BH returns. AcknowledgmentThe infrastructural support provided by the FORE School of Management, New Delhi in completing this paper is gratefully acknowledged.
The classical view of experts associates greater risks with greater rewards. The present study explores whether increased volatility in portfolios can create more returns for investors by using technical indicators or the buy-and-hold (BH) strategy. The study used closing prices of National Stock Exchange (NSE) 500 index firms for a period of 16 years (2007–2022). Five portfolios ranging from low to high volatility were created using standard deviation as a key measure. Findings indicate that as the volatility of the portfolios increases, the moving average (MA) returns seem to be higher. Across the various MA time frames, the 20-day MA seems to have generated the highest return annually (36.53% before transaction costs and 31.05% after transaction costs) due to reasonable trading opportunities with adjustable transaction costs. The CAPM also generated positive alpha (after bearing transaction costs) in the case of 20, 50, and 100 days MA, with the values being 16.66%, 13.29%, and 12.09%, respectively, in the case of highly volatile portfolios. On the other hand, while the BH strategy created substantial returns in all scenarios, the risk factor was extremely high due to the high standard deviation. Hence, it is suggested that investors/traders consider the BH strategy more cautiously while choosing between technical analysis returns and BH returns. Investors with high-risk preferences may have BH as their choice, while day traders with managed risk appetites may prefer technical tools over BH returns. AcknowledgmentThe infrastructural support provided by the FORE School of Management, New Delhi in completing this paper is gratefully acknowledged.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.