FINANCEWeeks to result

Momentum Technical Scoring System

Score and rank stocks on objective momentum signals to find the highest-conviction trend entries

Problem it solves

Investors comparing dozens of stocks within a thematic basket lack a consistent, objective method for ranking them and identifying the best risk/reward entry points.

Best for

Active traders and thematic investors who need a repeatable system to prioritize new positions and monitor existing ones within a large stock universe.

Not ideal for

Long-term buy-and-hold investors or pure fundamentalists who do not incorporate price-based signals into their process.

Overview

Why this framework exists

The Momentum Technical Scoring System awards points to each stock in a thematic basket based on a set of momentum conditions evaluated simultaneously. Stocks earn points for trading above the 50-day moving average, above the 200-day moving average, having a positive 1-month slope on those averages, maintaining an RSI between 50 and 70 (trending but not stretched), showing volume above the 20-day average, and outperforming sector peers on a relative basis. Scores are aggregated and the universe is ranked, giving investors a clear priority list for entries, a watch list of overbought names to avoid, and a flag list of deteriorating names to trim. The system removes emotional bias from position-sizing decisions within a large basket.

Core principles

5 total
  1. Systematic scoring eliminates emotional bias when comparing many stocks simultaneously
  2. The 50-70 RSI zone offers the best risk/reward—trending without being overextended
  3. Volume confirmation separates genuine momentum from low-conviction price moves
  4. Relative performance within a theme matters as much as absolute price action
  5. Positive moving average slope confirms a trend is still accelerating, not just intact

Steps

7 steps
  1. Define the investment universe
    Select the thematic basket or sector index containing the stocks you want to evaluate. Keep the list focused—20 to 100 names within a single theme (e.g., semiconductor supply chain, energy infrastructure) so scoring remains manageable and comparisons are meaningful.
    Pro tipStart with an existing thematic list or ETF holdings rather than building from scratch; the goal is ranking within a coherent group, not screening the entire market.
  2. Score moving average position
    Award separate points for each stock trading above its 50-day moving average and above its 200-day moving average. Stocks above both score highest, signaling an established uptrend across both short and long timeframes.
    Pro tipTreat the 200-day as a binary pass/fail regime filter first—names below it require a higher burden of proof before entry.
  3. Score moving average slope
    Award additional points when the 1-month slope of a stock's moving average is positive, confirming the trend is still accelerating rather than merely intact. Compare slopes across names in the basket to identify the strongest movers.
    WarningA flat or marginally positive slope in a strong sector rally can still signal a weakening name—always view slope relative to peer slopes, not in isolation.
  4. Filter by RSI zone
    Target stocks with RSI readings between 50 and 70. Award full points in this zone, zero points below 50 (downtrend), and negative or zero points above 70 (overbought). This keeps you in confirmed uptrends while avoiding stretched entries.
    Pro tipThe 50-70 RSI range is the sweet spot: the stock is trending with room to run, giving the best risk/reward for new or increased positions.
    WarningDo not override the RSI filter because you like the story—chasing RSI above 70 is the fastest way to enter at the worst point in a momentum cycle.
  5. Check volume confirmation
    Compare each stock's recent volume to its 20-day average. Award points when up-days occur on above-average volume, indicating institutional participation. Penalize names where price is rising on declining volume.
    WarningThinly traded small caps can produce distorted volume averages from a single large order—apply volume scoring only to names with consistent daily liquidity.
  6. Score relative performance
    Measure each stock's price performance versus its closest sector peers over a meaningful lookback (4 to 13 weeks). Award points to relative leaders and penalize persistent laggards, even if their absolute scores are acceptable.
    Pro tipRelative underperformance within a strong theme often signals a company-specific problem the sector tailwind is masking—flag these names for fundamental review before adding exposure.
  7. Aggregate scores and rank the universe
    Sum each stock's points across all criteria, rank the full basket from highest to lowest, and use the ranked list to prioritize new positions at the top and identify names to trim or exit at the bottom. Review the ranking weekly to track changes in positioning.
    Pro tipThe bottom of the ranked list is as valuable as the top—deteriorating scores often precede price breaks and give you time to exit before the tape confirms the move.

Checklist

Saved in your browser

Examples

2 cases
Semiconductor Basket Ranking Post-Correction

After a five-week market selloff, a subscriber applies the scoring system to a 50-stock semiconductor supply chain basket. Most names show RSI near 45-55. Scoring each on all seven criteria, she identifies eight stocks above both moving averages with positive slopes, RSI between 52 and 65, and above-average volume. These become priority buys. Twelve names with RSI below 50 and negative slopes are flagged for trimming, while the rest are held with technical stop levels defined.

OutcomeThe top-scored eight names outperform the broader basket over the following four weeks as momentum re-accelerates, while the flagged twelve names continue to lag.
Oracle Spotlight Identification

Jordi applies his technical scoring framework to software-adjacent names during a sector selloff. Oracle scores well on moving average position and relative performance versus software peers despite being lumped with struggling SaaS companies. The technical score triggers a spotlight update for subscribers, with the compute shortage thesis providing fundamental confirmation for the technical signal.

OutcomeOracle makes a new year-to-date high shortly after the spotlight update, validating the scoring system as a timely and objective entry trigger that emotional or narrative-driven analysis had missed.

Common mistakes

3 traps
Chasing overbought names above RSI 70
The system explicitly excludes stocks with RSI above 70 because entering at that level means buying at peak momentum extension. Overbought names in strong themes almost always consolidate or pull back before continuing, giving patient investors a better entry if the thesis is correct.
Skipping relative performance comparison
A stock can pass every absolute momentum test and still be a persistent laggard within its theme. Ignoring relative performance means holding the weakest names in a basket while stronger peers compound at a faster rate.
Applying the system to a single stock
The scoring framework derives its value from ranking and comparison across many names simultaneously. Scoring one stock in isolation removes the relative context that makes the rankings actionable—there is no way to know if a score of 4 out of 7 is good or bad without seeing the distribution across the full universe.

Origin story

How this framework came to be

Extracted from Jordi Visser's weekly market update video series, where Visser developed and described this scoring methodology to help subscribers systematically evaluate and rank stocks within his AI-infrastructure model portfolio baskets.

Source

Traced to primary
Source · VIDEO
All Time Highs Built On A Compute Shortage — Jordi Visser
Jordi Visser · 2026
Open source →

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