QuantAI Alpha Pick

Screening Filters

1. PriceAboveMA200 (Price above 200-day moving average)

   • Purpose: Ensure the stock is in a longer-term uptrend or at least not in a clear downtrend.
   • Rationale: For a QuantAI “Alpha Pick,” you generally want names where price action already confirms underlying strength. Trading above the 200-day moving average is a classic technical signal of positive long-term momentum and helps avoid structurally weak or down-trending stocks that may look cheap but are fundamentally out of favor.

2. Quarterly Revenue YoY Growth ≥ 10%

   • Purpose: Focus on companies with solid and growing business fundamentals.
   • Rationale: A true “alpha” candidate should have underlying business momentum, not just technical or speculative strength. Requiring at least 10% year-over-year quarterly revenue growth filters out stagnating or shrinking businesses and biases the list toward companies that are expanding their top line, which often supports future earnings and stock performance.

3. P/E (TTM) between 5 and 40

   • Purpose: Avoid both extremely overvalued and extremely distressed (or questionable) names.
   • Rationale:
     • A minimum P/E of 5 helps exclude many ultra-low P/E stocks that may be “value traps,” facing structural issues or one-off earnings distortions.
     • A maximum P/E of 40 avoids the most richly valued, speculative names where expectations are already very high and downside risk from multiple compression is significant.
       This range focuses QuantAI picks on companies that are reasonably valued relative to earnings, balancing growth with valuation discipline.

4. One-Month Rise Probability ≥ 65%

   • Purpose: Emphasize stocks with a statistically higher chance of positive performance over the next month, based on QuantAI’s model.
   • Rationale: The idea of an “Alpha Pick” implies a higher-probability edge, not just any stock. By setting a relatively high threshold for the model’s one-month rise probability (≥ 65%), the screener targets situations where the model’s historical patterns suggest a favorable risk/reward over the near term, rather than random or coin-flip outcomes.

5. One-Month Predicted Return ≥ 8%

   • Purpose: Ensure not only a high probability of rising, but also a meaningful expected upside.
   • Rationale: A stock could have a decent chance of rising but only by a small amount. Requiring an expected one-month return of at least 8% aims to focus on names where the model projects a return substantial enough to justify the risk and transaction costs. This aligns closely with the concept of an “Alpha Pick”: a combination of high probability and attractive expected magnitude of return.

Why Results Match “QuantAI Alpha Pick”

• Quant-driven edge: The two predictive filters (one-month rise probability and one-month predicted return) are directly aligned with a quantitative “alpha” concept—seeking statistically favorable, model-identified opportunities rather than random picks.
• Balanced by fundamentals and valuation: Revenue growth and P/E constraints ensure that the candidates are not purely momentum or speculative plays; they have reasonable fundamentals and valuations that can support continued performance.
• Risk control via trend filter: The 200-day moving average condition helps avoid fighting major downtrends, which adds a layer of risk management common to professional-quality quant and discretionary processes.

Together, these filters define “QuantAI Alpha Picks” as stocks that:

1. Are in a favorable technical trend,
2. Show solid fundamental growth,
3. Trade at reasonable valuations, and
4. Have a quantitatively modeled edge for upside in the next month, both in probability and expected return.