Tiny Titans Stock Screener: History, Performance, and Refinements

Tiny Titans: A Brief History

After he published his book in 2006, James O’Shaughnessy became a household name in financial circles. In particular, he is known for creating the “Tiny Titans” stock screener, an algorithm which has become celebrated for delivering extremely high returns, albeit somewhat volatile ones.

O’Shaughnessy’s screen is designed to identify undervalued stocks with small market capitalizations, often referred to as microcap stocks. The strategy is based on the premise that these smaller companies are frequently overlooked by analysts and institutional investors, creating potential opportunities for individual investors.

The rationale behind this approach is multifaceted. First, due to their size, these companies often receive minimal attention from professional analysts, leading to a potential information gap in the market. This lack of coverage can result in mispricing, where a company’s true value may not be accurately reflected in its stock price.

Secondly, large mutual funds and institutional investors typically avoid significant positions in these microcap stocks. Their size constraints mean that any substantial investment would likely move the stock price, making it difficult for them to build or exit positions without affecting returns. This institutional avoidance further contributes to the potential for mispricing and undervaluation.

O’Shaughnessy argues that this combination of factors creates a fertile ground for finding “diamonds in the rough” – companies with strong potential that have not yet been recognized by the broader market. These undiscovered gems, he believes, have the capacity to generate exceptional returns as they grow and attract more attention from investors and analysts.

Another key aspect of O’Shaughnessy’s strategy is the observation that microcap stocks often exhibit low correlation with the broader market indices. This characteristic makes them potentially valuable as a diversification tool within a larger investment portfolio. By including these stocks, investors may be able to reduce overall portfolio volatility and potentially improve risk-adjusted returns.

In essence, O’Shaughnessy’s approach seeks to capitalize on market inefficiencies in the microcap space, aiming to uncover undervalued companies with significant growth potential while simultaneously providing a hedge against broader market movements.

Specifically, Tiny Titans filters for these criteria:

While this strategy sounds compelling in theory, its practical effectiveness has unfortunately not lived up to the hype. Let’s examine the evidence that reveals its practical limitations.

Results since 2000

If we only backtest microcap stocks and megacap stocks (no P/S or sort applied), we can see that O’Shaughnessy’s methodology is essentially correct. Stocks with a market cap between 25 and 250 million consistently outperform stocks with a cap greater than 100 billion (but not the S&P).

However, these micro stocks are also far more volatile. This backtest has a range of over 1100% (100% loss to a 1000% gain) over its run period. The filtered Tiny Titans is slightly more stable, but still returns a chart with mountains and valleys sharp enough to make even the most unorthodox of investors go shopping for a pacemaker.

Propping Up the Giant

Examining this graph, we can see that Tiny Titans ceases to be a whirlwind of success from 2010 to 2020.This decline has sparked a wave of analysis and reinterpretation across financial media and investment circles. They tweak one criterion or another in an effort to “fix” the strategy, and continue bringing back those high returns. We will examine a couple of the most popular “tweaks” and see if they help.

Changing the rebalance period

One of the simplest modifications done on Tiny Titans is simply to rebalance more often. Instead of the leisurely quarterly rebalance in the canonical screener, others set their screener to re-evaluate monthly, or even weekly.

The pink in this graph represents the screen rebalanced monthly, and the charcoal rebalanced weekly. The results for each are rather consistent: rebalancing monthly nets you higher, but more volatile gains than the standard quarterly, while weekly provides a smaller, milder return.

Limiting Raw Close

Another common refinement (for this and other screeners) is to remove stocks with a low closing price. At first glance, this seems understandably counter-intuitive: why add a filter that so consistently underperforms the original screener?

There are a number of reasons that require us to invoke this strategy. The first lies in relative gains contrasting with absolute gains. A penny stock purchased at 10 cents, even with a gratuitous return of 1000%, only yields a single dollar–a value not material to most investors. Additionally, their low prices and trade volumes make penny stocks more vulnerable to manipulation. It’s comparatively easy for an aspiring swindler to generate false interest in the stock, only to sell the shares he holds at the inflated prices before they come crashing back down to reality. Neither of these qualities are desirable to investors, so it’s only sensible to avoid penny stocks. To that end, all of our subsequent refinements will be on those stocks with RawClose>3.

Refining with Piotroski’s F-Score

We can also refine O’Shaughnessy’s screen by using it in tandem with another financial indicator.. In this example, we use the Piotroski F-Score to refine Tiny Titans further, filtering out those tickers that scored less than 6.

At first glance, we seem to have struck gold–a return of over 10,000%. However, if something looks too good to be true, it’s best to assume that it is. 2013 is when the Piotroski screener began to rise in earnest; let’s take a closer look at the holdings in that time period.

While there are a few clear outperformers, these tickers aren’t so far ahead of the pack as to be called outliers. It doesn’t appear then that we owe our success to one or two fluke investments. What if we ignore the entire years of 2013 and 2014 entirely? These were by far the best-performing years, perhaps the algorithm just got lucky in that brief period.

The gain isn’t quite as dramatic as before, the screen still brings a return of over 4,000%. Even with the best years removed, our screener leaves both the S&P and the vanilla O’Shaughnessy in the dust. It would seem that we’ve exhausted our repository of ‘sanity checks’ on this screener. Even after correcting for the raw close price and removing any possible outliers, we still see very good performance from this screener. Finding the reason for this, and whether this performance can be expected in the future, is left as an exercise for the reader.