IMPORTANT DISCLAIMER: Blank Capital Research ("BCR") is a technology platform, not a registered investment advisor or broker-dealer. The algorithmically generated signals, scores, and rankings provided on this site ("God Mode" Signals) are for informational and research purposes only and do not constitute financial advice, investment recommendations, or an offer to sell or solicit an offer to buy any securities.
HYPOTHETICAL PERFORMANCE RESULTS: The "timing scores" and "regime signals" displayed are based on quantitative models. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under-or-over compensated for the impact, if any, of certain market factors, such as lack of liquidity.
RISK OF LOSS: Trading in financial markets involves a high degree of risk and may result in the loss of your entire investment. Data provided by third-party sources (Intrinio, Snowflake) is believed to be reliable but is not guaranteed for accuracy or completeness. Past performance is not indicative of future results.
© 2026 Blank Capital Research. All rights reserved. System Version: Aegis V8 (God Mode).
Common questions about our stock ranking system, methodology, and how to use our research.
Our ranking system uses quantitative methods to score and rank approximately 3,000 U.S. stocks based on characteristics that academic research has shown to predict future returns. Each stock receives a score from 0-100 and a star rating (1-5 stars).
Rankings are updated monthly. This frequency balances keeping signals fresh with minimizing unnecessary trading costs.
We rank all U.S. common stocks meeting these criteria: stock price at least $1.00, average daily trading volume at least $100,000, market cap at least $50 million, and sufficient data coverage (at least 80% of required fields). This typically results in about 3,000 stocks.
No. Our rankings are for informational and educational purposes only. They do not constitute investment advice or recommendations. Always consult a qualified financial advisor before making investment decisions.
Factor investing targets specific characteristics (factors) that explain differences in stock returns. Academic research going back 50+ years has identified factors like value, momentum, and quality that persistently predict returns across markets and time periods.
We selected factors that: (1) have strong academic evidence published in top journals, (2) work across different markets and time periods, (3) have economic rationale explaining why they work, and (4) can be measured reliably with available data.
Profitability measures how efficiently a company generates profits from its operations. We use "Cash-Based Operating Profitability" from Ball et al. (2016), which adjusts for accounting tricks by focusing on actual cash generation. Companies that generate strong cash profits have real earnings power and tend to outperform.
Momentum measures recent price performance. Stocks that have gone up tend to keep going up (at least for a while). We use 12-month returns, excluding the most recent month. This works because investors tend to underreact to news, causing prices to adjust gradually.
Value measures how cheap a stock is relative to its fundamentals. We use a composite of earnings yield, cash flow yield, sales yield, and book value. Cheap stocks tend to outperform because investors get overly pessimistic about struggling companies and overly optimistic about glamorous growth stocks.
Low volatility measures price stability. Surprisingly, less volatile stocks have historically delivered better returns than more volatile stocks—the opposite of what traditional finance theory predicts. This happens because investors prefer exciting, volatile stocks and bid them up too high.
Investment measures how aggressively a company is expanding. Companies that grow assets slowly ("conservative" investors) tend to outperform those expanding rapidly. Aggressive companies often destroy value through empire-building, overpaying for acquisitions, or expanding at the wrong time.
Short interest measures how many investors are betting against a stock. When sophisticated short sellers avoid a stock, it's often a positive signal. Short sellers do extensive research and are often right—low short interest suggests informed investors don't see major problems.
5 stars (score 75+): Strong Buy. 4 stars (score 65-74): Buy. 3 stars (score 50-64): Hold. 2 stars (score 40-49): Reduce. 1 star (score below 40): Avoid. These use AQR-style fixed score thresholds applied to our full universe of 7,333+ stocks.
No. Five stars means a stock scores well on our factors, but factor models are probabilistic, not certain. Individual stocks can underperform despite good factor scores. Your personal situation, risk tolerance, and existing holdings all matter. Diversification is essential.
Not necessarily. One star means a stock scores poorly on our factors, but some low-scoring stocks will still do well. Selling has tax implications, transaction costs reduce returns, and the stock might be appropriate for your specific situation.
Our Information Coefficient (IC) is about 0.044, meaning there's a positive but modest correlation between our rankings and future returns. This is actually quite good for a stock ranking system—perfect prediction is impossible. Over time, higher-ranked stocks tend to outperform lower-ranked stocks.
Our rankings are purely quantitative and don't consider brand recognition, management quality (beyond financials), future growth potential (beyond current momentum), or news and analyst opinions. A well-known company might rank poorly if it's expensive, has weak profitability, poor momentum, or high volatility.
Research shows that timing factor exposures is extremely difficult and often counterproductive. As Cliff Asness of AQR wrote: "Timing factor exposures is every bit as hard as timing the market." We provide market regime information for context, but our factor weights remain constant.
A z-score measures how many standard deviations a value is from the average. We calculate z-scores so that all factors are on the same scale, we can combine them meaningfully, and extreme values don't dominate. A z-score of +2 means the stock is 2 standard deviations above average on that factor.
Winsorization clips extreme values to reduce the impact of outliers. We set values below the 1st percentile to the 1st percentile value, and values above the 99th percentile to the 99th percentile value. This prevents data errors or truly extreme observations from distorting our rankings.
Stocks must have at least 80% of required data fields to be ranked. For remaining missing values, we use the cross-sectional average (effectively neutral). Stocks with insufficient data are excluded entirely.
We use several metrics: Information Coefficient (IC) measuring correlation between rankings and future returns, IC t-statistic measuring statistical significance, and Tier Spread measuring the return of score 75+ stocks minus score-below-40 stocks.
Based on backtesting: IC of 0.044 (good), IC t-stat of 9.84 (highly significant), and annual spread of 18% (strong). Important: Past performance does not guarantee future results. Backtests may overstate performance due to survivorship bias and hindsight.
Limitations include survivorship bias (we only rank currently active stocks), look-ahead bias (backtests use data that wasn't available in real-time), transaction costs (not included in metrics), capacity constraints (some stocks may be too small), and factor crowding (returns may diminish as factor investing grows).
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