Important Context
It’s not possible to guarantee gains over a 1‑month period. What we can do instead is try to identify stocks that, based on history, trend, and analyst views, have a higher probability of delivering a positive 1‑month return. The filters below are designed exactly for that.
Screening Filters
Market Cap ≥ $10 Billion (market_cap: {'min': '10000000000'})
- Purpose: Focus on larger, more established companies that tend to be more stable and predictable.
- Rationale:
- Large-cap stocks usually have more analyst coverage, deeper liquidity, and more stable business models.
- This reduces idiosyncratic risk (e.g., one bad event wiping out gains) and makes any probability or return estimate more reliable statistically.
Price Above 20-Day Moving Average (PriceAboveMA20)
- Purpose: Capture stocks in a short-term uptrend.
- Rationale:
- The 20-day MA is a common proxy for the last ~1 month of trading.
- Price above this level suggests positive short-term momentum, which historically often persists over subsequent weeks, improving odds of a near-term gain.
Price Above 200-Day Moving Average (PriceAboveMA200)
- Purpose: Ensure the stock is also in a long-term uptrend, not just a short-lived bounce.
- Rationale:
- The 200-day MA reflects the longer-term trend.
- Having price above both 20-day and 200-day MAs filters for names where both short- and long-term momentum are aligned upward, which tends to be more “reliable” than a short-term spike in a downtrend.
1-Month Rise Probability ≥ 75% (one_month_rise_prob: {'min': '75'})
- Purpose: Explicitly target stocks with a historically high estimated probability of being higher in 1 month.
- Rationale:
- This metric (often model-based) estimates the chance the stock’s price will be higher one month from now.
- Setting a threshold of 75% directly addresses your desire for “reliability” by favoring stocks where models suggest gains are more likely than not, with a relatively high confidence level.
Predicted 1-Month Return ≥ 5% (one_month_predict_return: {'min': '5'})
- Purpose: Avoid stocks that might be “safe” but with negligible upside; focus on meaningful expected gain.
- Rationale:
- A minimum expected return of 5% in one month targets situations with both decent upside and high probability, rather than just slightly positive, low-volatility names.
Analyst Consensus: Strong Buy or Moderate Buy (analyst_consensus: ['Strong Buy', 'Moderate Buy'])
- Purpose: Align with professional analyst conviction that fundamentals and valuation support further upside.
- Rationale:
- When analysts rate a stock as Strong/Moderate Buy, it usually reflects positive earnings outlook, catalysts, or attractive valuation.
- Combining quantitative signals (trend, probabilities) with analyst support reduces the chance you’re chasing a purely technical or model-driven anomaly.
Why the Results Match Your Goal
- The probability and predicted return filters directly target stocks with higher modeled odds of delivering a positive 1‑month gain and a meaningful expected magnitude.
- The moving average filters align price trends across short and long horizons, favoring stocks where momentum is on your side rather than fighting a downtrend.
- The large-cap filter improves reliability by focusing on well-covered, more stable companies where estimates and probabilities tend to be more dependable.
- The analyst consensus filter adds a fundamental layer of confirmation, seeking names where professionals also expect gains, not just algorithms or charts.
Together, these filters don’t guarantee profits, but they systematically tilt the search toward stocks that are statistically and fundamentally more likely to produce 1‑month gains with relatively higher reliability.
This list is generated based on data from one or more third party data providers. It is provided for informational purposes only by Intellectia.AI, and is not investment advice or a recommendation. Intellectia does not make any warranty or guarantee relating to the accuracy, timeliness or completeness of any third-party information, and the provision of this information does not constitute a recommendation.