Top Performing Stock Models

Guru Based on Annual
Dashan Huang 21.5%
Partha Mohanram 15.6%
James O'Shaughnessy 18.3%
Motley Fool 13.3%
Wesley Gray 12.0%
Martin Zweig 11.2%
Wayne Thorp 16.5%
Patrick O'Shaughnessy 15.9%
Benjamin Graham 10.8%
Validea 10.8%
* Returns are model returns and do not reflect actual trading. Full performance disclaimer
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Top Performing ETF Models

Portfolio Annual
Factor Rotation - Momentum with Trend 12.7%
Factor Rotation - Composite with Trend 12.3%
Factor Rotation - Momentum 11.3%
Factor Rotation - Macro with Trend 10.7%
Factor Rotation - Composite 10.5%
* Returns are model returns and do not reflect actual trading. Full performance disclaimer
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Our Latest Articles


Knowledge Mining in the Market’s Past Returns

By Justin Carbonneau (@jjcarbonneau)

When you hear stats like the S&P 500 is up 10% for the year or the index has more than tripled off the 2009 low, it’s easy to take those figures at face value and move on. The return of the market in the past is what it is and you can’t change it. However, it can be instructive to look back, under the hood, at the drivers of those returns so that we can think about what might happen going forward. For this article, I wanted to look at the stocks, industries and sectors adding to and detracting from the returns in the market over the past 12 years.


Four Things Buffett Does Most Investors Couldn't or Shouldn't Do

By Justin Carbonneau (@jjcarbonneau)

We admire his track record, investing prowess, long-term thinking, optimism in America, his communication abilities and the sound and consistent investment advice he has shared with millions of investors. But in studying Warren Buffett and looking at his portfolio and actions, it might be more of a story of "do as I say, not as I do".
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Our Podcast - Excess Returns


Episode 57: Why Eliminating Discretion from Quantitative Models is Harder Than You Think

There is a tendency for those of us who support quant models to talk about them as if they are these things that just run on autopilot over the long-term that are free from all the decision-making issues that plague us as human beings. That just isn’t the case, though. There are many decisions that go into the development, optimization, and evolution of quant models that require human intervention and a thoughtful, nuanced approach. In this episode, we discuss the human decisions that go into quant models and how to develop a thoughtful framework to make them.

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Episode 56: Is Value Investing Dead?

Value investing has struggled for over a decade now. Although no one will dispute that fact, there are significant disagreements about whether this is just another of the long periods of underperformance that have been common in the history of value or if something about the strategy has become broken. In the first year of our podcast, we have talked to some of the smartest people we know in the investing world about this topic, including Jim O'Shaughnessy, Tobias Carlisle, Adam Butler, Partha Mohanram, Wes Gray, Vitaliy Katselnelson, and Kai Wu, and have received a diverse set of opinions. In this episode, we bring together all of those insights in an effort to answer one question: Is Value Investing Dead?

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Webinar: An Overview of Validea

A detailed look at the site and how to use it.

Top Quant and ETF Strategies in a Historic Market

A look at some of our strategies and how they worked in the historic 2020 market

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What Our Users Are Saying About Validea

Validea is an incredible valuable tool to have. I depend on it for much of my research to help weed out stocks for my portfolio designs. The filters used for stock selection are easy to use and comes with a detailed analysis as to the why each particular stock either passes or fails the test. The articles & blogs are a great wealth of knowledge too.

Eric J.
Financial Advisor
As a retail investor, I particularly value Validea’s top-notch research capability. With the deluge of investment commentary available via innumerable blogs, articles, FinTwits, white papers, podcasts, etc., the Validea team is one of my go-to sources to maintain some perspective on what's really happening.

Rolf D.
I am always checking my investment/trading ideas with Validea. I feel better knowing that any of the guru models they are following might also be on my side!

Urs K.

Find Your Edge With Validea's Quantitative Investing Tools

Guru Analysis

Analysis of 6000+ stocks using the proven strategies of investment legends like Warren Buffett, Benjamin Graham and Peter Lynch. See the details behind "why" some stocks look good and others don't through the guru methodologies.

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Model Portfolios

22 different model portfolios based on our time tested factor-based strategies.

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ETF Portfolios

Our ETF portfolios use value, momentum and macroeconomic factors to rotate among factors, sectors and asset classes.

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Stock Screener

Screen for stocks that pass the strategies of investment legends such as Joel Greenblatt, John Neff and Martin Zweig. Combine multiple strategies together or add in fundamental filters to refine your result set.

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Trend Following

Our trend following system covers over 45+ asset & investment classes and seeks to help limit losses during major market declines while maintaining a disciplined re-entry method when prices revert. Get alerted when the signals change between Buy and Sell.

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Performance Disclaimer: Returns presented on 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.

Optimal portfolios presented on 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 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.