Relative Strength: How to Find Stocks Outperforming the Market

Relative Strength Is Not RSI

Before going any further, a critical clarification. Relative strength (RS) and the Relative Strength Index (RSI) are completely different concepts. The RSI, developed by J. Welles Wilder in 1978, is a momentum oscillator that measures the speed and magnitude of a stock's own price changes on a scale of 0 to 100. It tells you whether a stock is overbought or oversold relative to its own recent history.

Relative strength, by contrast, measures how a stock's price performance compares to a benchmark -- typically the S&P 500 (SPY). A stock with rising relative strength is outperforming the market. A stock with falling relative strength is underperforming, even if its price is going up in absolute terms. This distinction matters enormously: a stock can rise 10% in a year but still have poor relative strength if the S&P 500 rose 20% over the same period.

The confusion between these two concepts is widespread, and it leads to genuine misunderstanding. When William O'Neil discusses "RS Rating" in his CANSLIM methodology, he means relative strength versus the market -- not the RSI oscillator. When Mark Minervini requires stocks to have strong relative strength, he means the same thing. Throughout this article, RS always refers to relative strength versus a benchmark.

How to Calculate Relative Strength

There are several ways to compute relative strength, all capturing the same fundamental idea: how is this stock performing compared to the broader market?

The Ratio Method

This is the simplest approach. Divide the stock's price by the benchmark price (usually SPY or the S&P 500 index) and plot the result over time. When the ratio is rising, the stock is outperforming. When it is falling, the stock is underperforming. The absolute value of the ratio is meaningless -- what matters is its direction and rate of change.

You can apply a moving average to the RS ratio line to smooth out noise and identify the underlying trend. A rising 50-day moving average of the RS ratio confirms sustained outperformance.

The Return Difference Method

Calculate the percentage return of the stock over a lookback period (commonly 6 or 12 months), subtract the percentage return of SPY over the same period. A positive value means the stock outperformed. A negative value means it underperformed. This method is convenient for ranking large numbers of stocks.

The Percentile Ranking Method

Compute the return difference for every stock in your universe. Then rank them from worst to best and convert to a percentile score from 0 to 100. A stock with an RS percentile of 90 has outperformed 90% of all stocks in the universe over the lookback period. This is essentially what O'Neil's RS Rating captures.

Academic Foundations

Unlike many technical analysis concepts, relative strength has robust academic support. It is one of the most well-documented anomalies in finance, and the evidence for its efficacy spans decades, markets, and asset classes.

Levy (1967)

Robert Levy published "Relative Strength as a Criterion for Investment Selection" in the Journal of Finance in 1967. This was the first systematic academic study of relative strength as a stock selection criterion. Levy found that stocks with strong recent relative performance tended to continue outperforming over the following months. This was a controversial finding at the time, as it directly challenged the random walk hypothesis that was gaining acceptance in academic finance.

Jegadeesh & Titman (1993)

The landmark study that cemented relative strength (momentum) as a recognized market anomaly was "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency" by Narasimhan Jegadeesh and Sheridan Titman, published in the Journal of Finance in 1993. Their strategy was straightforward: rank all stocks by their returns over the past 3 to 12 months, buy the top decile (winners), and short the bottom decile (losers). Hold for 3 to 12 months.

The results showed statistically significant abnormal returns of approximately 1% per month for the winner-minus-loser portfolio. This finding has been replicated across virtually every equity market in the world and across asset classes including bonds, commodities, and currencies. The Jegadeesh-Titman momentum strategy is, at its core, a relative strength ranking strategy.

Importantly, momentum returns are not explained by the Fama-French three-factor model (market, size, value). Momentum is a genuinely independent factor, which is why Carhart (1997) added it as a fourth factor in what became the Carhart four-factor model.

Why Relative Strength Works

Several behavioral and structural explanations have been proposed for why relative strength persists as an anomaly:

• Behavioral underreaction: Investors are slow to update their beliefs in response to new positive information. When a company reports strong earnings or receives a positive catalyst, the stock price adjusts gradually rather than immediately, creating a period of persistent outperformance.
• Institutional trend-following: Many institutional investors follow momentum and trend-following strategies, either explicitly or implicitly. As a stock begins to outperform, it attracts buying from these institutions, which further reinforces the outperformance.
• Winner-take-all dynamics: In competitive industries, the leading company often captures a disproportionate share of profits and market share. This creates a fundamental basis for sustained outperformance that is reflected in relative strength.
• Confirmation cascade: Analyst upgrades, media coverage, and fund inflows tend to follow strong price performance, creating a self-reinforcing cycle that extends the period of outperformance.

O'Neil's CANSLIM and RS Rating

William O'Neil, founder of Investor's Business Daily and author of How to Make Money in Stocks, made relative strength a central component of his CANSLIM stock selection method. The "R" and "S" in CANSLIM stand for "Relative Strength" and "Supply and Demand" -- both of which relate to a stock's price behavior relative to the market.

O'Neil's proprietary RS Rating ranks all stocks on a scale of 1 to 99 based on their price performance over the prior 12 months, with heavier weighting on the most recent quarter. An RS Rating of 80 means the stock has outperformed 80% of all stocks in the database. O'Neil's research found that the vast majority of the biggest stock market winners -- stocks that went on to gain 100%, 200%, or more -- had an RS Rating of 80 or higher before their major advance began.

O'Neil's recommendation is straightforward: focus on stocks with an RS Rating of 80 or higher. Avoid stocks with ratings below 70, even if they look "cheap" on a fundamental basis. A low RS Rating means the market is telling you something negative about the stock, and the market is usually right.

Minervini's Relative Strength Criteria

Mark Minervini, a US Investing Championship winner and author of Trade Like a Stock Market Wizard, uses relative strength as a core filter in his Volatility Contraction Pattern (VCP) methodology. Minervini's approach requires that a stock's relative strength be in the top 30% of all stocks before it qualifies as a VCP breakout candidate.

Minervini's rationale is that strong relative strength confirms institutional accumulation. When a stock is outperforming the majority of the market, it means that sophisticated, well-capitalized buyers are actively building positions. The VCP pattern then identifies the specific consolidation and contraction that precedes the next leg higher.

The combination of relative strength filtering with a specific technical setup (the VCP) is a practical example of how relative strength works best: not as a standalone signal, but as a qualifying filter that ensures you are fishing in the right pond. By requiring top-30% relative strength, Minervini eliminates the vast majority of stocks from consideration and focuses only on those with confirmed institutional demand.

Sector-Relative Strength

An important extension of relative strength analysis is measuring a stock's performance not against the broad market, but against its own sector. This is sector-relative strength, and it isolates a stock's idiosyncratic outperformance from sector-level trends.

For example, during a broad technology sector rally, nearly all tech stocks will have strong relative strength versus SPY. But which tech stocks are outperforming the technology sector ETF (XLK)? Those are the stocks with genuine company-specific strength, not just sector tailwinds.

A stock with strong relative strength versus both SPY and its sector ETF is exhibiting the most compelling kind of outperformance. It is benefiting from sector tailwinds AND company-specific catalysts. Conversely, a stock that is strong versus SPY but weak versus its sector is likely just riding the sector wave -- a less reliable signal.

Sector-relative strength is particularly useful for avoiding the trap of buying a mediocre stock in a hot sector. If the entire biotech sector is rallying but your stock is underperforming biotech peers, that relative weakness is a warning sign even though the stock's absolute returns look good.

RS Divergence: The Early Warning Signal

One of the most valuable applications of relative strength is detecting RS divergence -- when a stock's relative strength begins to deteriorate while its absolute price is still rising or holding steady. This divergence is an early warning that the stock's trend may be exhausting.

The logic is straightforward: if a stock is making new highs in absolute price but its RS ratio is making lower highs, it means the stock is rising more slowly than the market. The trend is intact in absolute terms but weakening in relative terms. Historically, RS divergence often precedes absolute price breakdowns by weeks or months.

The mirror image is equally useful: when a stock's RS begins to improve while its price is still basing or consolidating, it suggests that the stock is beginning to attract buying interest relative to the market. This positive RS divergence can be an early signal that a new uptrend is forming before the breakout becomes obvious on the absolute price chart.

Practical Implementation

Here is a step-by-step approach to incorporating relative strength into your stock analysis and selection process.

Step 1: Compute RS for Your Universe

For each stock in your universe, calculate the 6-month return and subtract SPY's 6-month return. This gives you the raw RS value. Rank all stocks by this value and convert to a percentile (0-100). Store this as each stock's RS percentile score.

Step 2: Apply a Minimum RS Filter

Eliminate all stocks with RS percentile below your threshold. O'Neil uses 80. Minervini uses approximately 70 (top 30%). A reasonable middle ground is to require RS percentile of 70 or higher for long candidates. This single filter eliminates the majority of stocks and focuses your analysis on those with confirmed outperformance.

Step 3: Evaluate RS Trend Direction

A high RS percentile tells you the stock has outperformed recently. But is the outperformance accelerating or decelerating? Compute the RS ratio (stock price / SPY price) and apply a 50-day moving average. If the RS ratio is above its 50-day MA, the outperformance is in an uptrend. If below, it may be deteriorating.

Step 4: Check Sector-Relative Strength

Repeat the RS calculation using the relevant sector ETF instead of SPY. Stocks that are strong versus both SPY and their sector represent the highest-quality relative strength. Stocks that are only strong versus SPY but weak versus their sector may be riding sector momentum rather than exhibiting company-specific strength.

Step 5: Combine with Other Factors

Relative strength is a powerful filter, but it is most effective when combined with other independent signals. Insider buying (SEC Form 4 filings), earnings acceleration, and volume patterns provide complementary information. A stock with top-quartile relative strength, recent insider purchases, and a constructive base pattern has a much higher probability of future outperformance than any single factor alone.

When Relative Strength Fails

No factor works all the time, and relative strength has well-documented failure modes.

Momentum crashes: The most significant risk is momentum reversal, sometimes called momentum crash. During sharp market corrections and regime changes, former winners can reverse violently and underperform former losers. The most notable examples include the 2009 market bottom (momentum crashed as beaten-down stocks rallied aggressively) and certain sector rotation events where the leadership changes abruptly.

Late-cycle exhaustion: Stocks with extreme relative strength (top 5%) are sometimes in the final stages of a parabolic advance. Buying the strongest relative strength stocks without regard for valuation or chart structure can lead to buying blow-off tops. This is why Minervini combines relative strength with the VCP -- the VCP identifies constructive consolidation, filtering out parabolic excess.

Low-liquidity distortions: Micro-cap and low-float stocks can show extreme relative strength due to a single large buyer or a short squeeze. This relative strength is not sustainable and does not reflect genuine institutional accumulation. Apply a minimum liquidity filter (average daily volume, market capitalization) before ranking by RS.

Relative Strength in Alpha Suite

Alpha Suite incorporates relative strength as a component of its signal scoring pipeline. Specifically, the system computes each security's return relative to SPY over the trailing period and uses this as a factor in the technical overlay score. Stocks showing positive relative strength versus SPY receive a scoring boost, while those with deteriorating relative strength receive a penalty.

This relative strength measure is combined with insider conviction scoring (derived from SEC Form 4 filings), volume-confirmed breakout detection, RSI-14, and a volatility-anchored barrier model. The result is a composite signal that weights multiple independent factors rather than relying on any single metric.

The system requires relative strength in the top 40% for inclusion in the signal output. This is a less aggressive filter than O'Neil's 80 threshold, reflecting the fact that the system already applies multiple other filters (insider conviction, volume, technical structure) that narrow the candidate set. The relative strength filter serves as a confirmation that the broader market is not actively rejecting the stock.

The Bottom Line

Relative strength is one of the most well-supported concepts in empirical finance. The academic evidence, spanning from Levy (1967) through Jegadeesh & Titman (1993) and beyond, consistently shows that stocks with strong recent relative performance tend to continue outperforming. This is not a marginal or debatable finding -- it is one of the most robust anomalies in the financial literature.

The practical implication is straightforward: use relative strength as a qualifying filter. Focus your analysis and capital on stocks that are already demonstrating market leadership. Avoid stocks with poor relative strength, regardless of how attractive they appear on other metrics. The market's verdict, as expressed through relative strength, is a powerful and persistent signal that should not be ignored.