Top Performing Stock Models

Guru Based on Annual
Return
James O'Shaughnessy 20.7%
Meb Faber 21.1%
Dashan Huang 20.0%
Partha Mohanram 14.1%
Motley Fool 13.5%
Validea 17.3%
Martin Zweig 11.9%
Benjamin Graham 11.7%
Validea 11.6%
Peter Lynch 11.3%
* Returns are model returns and do not reflect actual trading. Full performance disclaimer
All Stock Portfolios

Top Performing ETF Models

Portfolio Annual
Return
Factor Rotation - Momentum with Trend 13.8%
Factor Rotation - Composite with Trend 13.2%
Factor Rotation - Momentum 12.1%
Factor Rotation - Composite 11.3%
Factor Rotation - Value with Trend 10.9%
* Returns are model returns and do not reflect actual trading. Full performance disclaimer
All ETF Portfolios

Our Latest Articles

7/27/2022

What Seeing Galaxies From "Far, Far Away" With The Webb Telescope Can Teach Us About Investing

By Justin Carbonneau® (@jjcarbonneau)

NASA recently released images from the James Webb Telescope, the most powerful telescope ever. With gold plated mirrors and at about half the size of a 757 aircraft, the telescope is now providing researchers with some of the deepest, most detailed images of the universe ever observed.

7/13/2022

Beware the Back Test

By Jack Forehand, CFA, CFP® (@practicalquant)

Active investment managers have a pretty dismal long-term record. Depending on which study you look at somewhere between 80% and 90% of managers underperform their benchmarks over the long-term net of fees. But what if I told you there was a way to turn those results upside down? What if there was a world where managers beat their benchmark 90% of the time? What if there was a world where managers knew how to position their portfolio in advance for any market environment and were able to adjust to anything the market throws at them?
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Excess Returns Podcast

8/11/2022

Episode 165: Show Us Your Portfolio: Phil Huber

In our latest episode of Show Us Your Portfolio we speak to Savant Wealth CIO Phil Huber. We discuss Phil's approach to building his personal portfolio and the core principles that guide it. We also discuss Phil's view on the expected returns of stocks and bonds, his approach to selecting alternative investments and a lot more.

Watch on YouTube    Listen on Apple Podcasts    Listen on Spotify    Listen on Google Podcasts

8/4/2022

Episode 164: Constructing an Intangible Asset Based Value Strategy with Kai Wu

Research has shown that value investing needs to change. Our economy has transitioned from one dominated by tangible assets like buildings and equipment to one dominated by intangible assets such as brands and intellectual property. Although many researchers have looked at the issue of how to value intangible assets, far fewer are looking at how to translate that into an actual investment strategy. Our guest this week has done exactly that. We speak to Sparkline Capital founder Kai Wu about how he looks at intangible assets and the machine learning based methods he uses to value them. We also get into the nuts and bolts of constructing an intangible focused value strategy and discuss issues such as selecting an investment universe, determining the number of stocks to hold, position sizing, industry concentration and a lot more.

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Performance Disclaimer: Returns presented on Validea.com are model returns and do not represent actual trading. As a result, they do not incorporate any commissions or other trading costs or fees. Model portfolios with inception dates on or after 12/30/2005 include a combination of back tested and live model returns. The back-tested performance results shown are hypothetical and are not the result of real-time management of actual accounts. The back-testing of performance differs from actual account performance because the investment strategy may be adjusted at any time, for any reason and can continue to be changed until desired or better performance results are achieved. Back-tested returns are presented to provide general information regarding how the underlying strategy behind the portfolio performed in our historical testing. A back-tested strategy has the benefit of hindsight and the results do not reflect the impact that material economic or market factors may have had on advisor's decision-making if actual client assets were being managed using this approach. The model portfolios offered on Validea are concentrated and as a result they will exhibit high levels of volatility and their performance can be substantially impacted by the performance of individual positions.

Optimal portfolios presented on Validea.com represent the rebalancing period that has led to the best historical performance for each of our equity models. Each optimal portfolio was determined after the fact with performance information that was not available at portfolio inception. As a result, an investor could not have invested in the optimal portfolio since its inception. Optimal portfolios are presented to allow investors to quickly determine the portfolio size and rebalancing period that has performed best for each of our models in our historical testing.

Both the model portfolio and benchmark returns presented for all equity portfolios on Validea.com are not inclusive of dividends. Returns for our ETF portfolios and trend following system, and the benchmarks they are compared to, are inclusive of dividends. The S&P 500 is presented as a benchmark because it is the most widely followed benchmark of the overall US market and is most often used by investors for return comparison purposes. As with any investment strategy, there is potential for profit as well as the possibility of loss and investors may incur a loss despite a past history of gains. Past performance does not guarantee future results. Results will vary with economic and market conditions.