JOURNAL ARTICLE
Capital-Weighted Volume, Volume Price Confirmation, and Famous Investor Portfolios.
Published In: Journal of Investing, 2025, v. 35, n. 1. P. 109 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Lutey, Matt 3 of 3
Abstract
We integrate famous investor strategies into our daily approach, enhanced by a risk overlay tailored to capital-weighted volume. This overlay optimizes risk-adjusted returns, delivering lower standard deviation and improved Sharpe and Sortino ratios compared to unadjusted methods. Our portfolios draw inspiration from iconic investors such as Warren Buffett, Benjamin Graham, and Joel Greenblatt and from William O'Neil's CAN SLIM methodology. We select stocks based on these principles but purchase them only when capital-weighted volume confirms bullish momentum. This disciplined approach minimizes maximum drawdowns and portfolio volatility while maintaining impressive annualized returns that outpace traditional buy-and-hold strategies. In a secondary study, we incorporate the volume price confirmation indicator (VPCI) to exclude low-volume momentum stocks from major indexes, including the Dow Jones, Nasdaq 100, S&P 500, Russell 3000, Russell 2000, and Russell 1000. Adding a momentum-based sell rule—such as exiting positions when prices drop below the 10-day moving average—further enhances overall performance. Since 1990, this refined strategy has generated exponential total returns, achieving gains in the thousands to tens of thousands of percent without increasing risk. These results underscore the power of combining volume-based filters with disciplined buy-and-sell frameworks to maximize investment performance. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Investing. 2025/12, Vol. 35, Issue 1, p109
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2025
- ISSN:1068-0896
- DOI:10.3905/joi.2025.1.371
- Accession Number:190284471
- Copyright Statement:Copyright of Journal of Investing is the property of With Intelligence Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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