Top Performing Stock Models

Guru Based on Annual
Partha Mohanram 15.1%
Dashan Huang 20.6%
Motley Fool 12.5%
Wayne Thorp 16.3%
Martin Zweig 10.7%
Validea 10.4%
James O'Shaughnessy 15.2%
Patrick O'Shaughnessy 15.1%
Wesley Gray 9.8%
Peter Lynch 9.9%
* 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 12.1%
Factor Rotation - Momentum with Trend 11.9%
Factor Rotation - Composite with Trend 11.6%
Factor Rotation - Composite with Trend 11.6%
Factor Rotation - Macro with Trend 10.7%
* Returns are model returns and do not reflect actual trading. Full performance disclaimer
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Our Latest Articles


What Peter Lynch, the Granddaddy of Stock Picking, Might Say To 3 Million New Robinhood Investors

By Justin Carbonneau (@jjcarbonneau)

Over 3 million new accounts were opened at Robinhood in the first quarter of this year – a resurgence in individual stock picking in the heart of the COVID-19 shutdown few could have anticipated. The renewed interest in individual stocks is in opposition to a trend of just a year or so ago, where the rise of passive investing, robo advisors and the challenges of trying to beat the market put a damper on investors buying individual stocks. But not everyone had given up hope on the fading stock picker.


When Fundamentals Don't Matter

By Jack Forehand (@practicalquant)

Valuing a company typically involves looking at its price and judging that price relative to its current and projected future fundamentals. But what happens when something breaks this process? What happens when companies are no longer valued based on their fundamentals? What happens when factors outside of those specific to each company become dominant over the facts regarding their businesses?
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Our Podcast - Excess Returns


Episode 36: Have the Fed, Narratives and Passive Flows Broken Fundamental Investing?

Valuing a company (or the market in general) typically involves looking at its price and judging that price relative to its current and projected future fundamentals. But some have argued that this process has become broken in the most recent decade and other factors have become more important than actual results. In this episode, we talk about some of these factors, how they have impacted the market, and what they might mean for the future.

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Episode 35: Finding Diamonds in the Rough Among Growth Stocks

Buying expensive stocks has historically been a terrible investing strategy. On average, expensive stocks significantly underperform the market as a whole over time. But despite the poor performance of the group, the absolute best performing individual stocks typically come from within this universe. The difficult part is trying to identify them in advance. In this episode, we look at a quantitative growth strategy developed by Partha Mohanram, a professor at the University of Toronto, and how it seeks to find diamonds in the rough among growth stocks.

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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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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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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.