What stocks should I pick this month

Note on your question

No screen can guarantee which stocks you “should pick” or which ones will definitely go up this month. What these filters do is narrow the US market to stronger, more established companies that, based on fundamentals and technicals, have a higher probability of performing well in the near term.

Screening Filters

1. Market Cap ≥ $10,000,000,000 (Large Caps)

   • Purpose: Focus on large, established U.S. companies.
   • Rationale:
     • When you ask “What stocks should I pick this month?”, it usually implies a preference for relatively safer, more liquid names rather than speculative micro-caps.
     • Large caps tend to have better analyst coverage, more stable business models, and tighter spreads, making them more practical for many investors.

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

   • Purpose: Select stocks in a longer-term uptrend or at least not in a prolonged downtrend.
   • Rationale:
     • For a this-month decision, trend direction matters.
     • The 200-day moving average is a widely used technical line: if the price is above it, the stock is generally considered to be in a bullish or healthier technical phase, which aligns with looking for candidates that are not currently “broken” technically.

3. Region: United States

   • Purpose: Limit results to U.S.-based or U.S-listed companies.
   • Rationale:
     • Directly matches your request: “from the US stock market.”
     • Ensures you’re seeing companies more likely to follow U.S. regulatory standards, reporting practices, and macro conditions you are asking about.

4. Exchanges: XNYS, XNAS, XASE (NYSE, NASDAQ, AMEX)

   • Purpose: Restrict to major U.S. exchanges.
   • Rationale:
     • These are the primary U.S. stock exchanges most investors refer to when they say “US stock market.”
     • Helps filter out illiquid over-the-counter (OTC) names and foreign secondary listings, improving liquidity and transparency.

5. Return on Equity (ROE) ≥ 15%

   • Purpose: Find companies that use shareholders’ capital efficiently and profitably.
   • Rationale:
     • Higher ROE typically signals strong profitability and good management, which can support both short-term sentiment and long-term valuation.
     • When choosing stocks “this month,” you generally want companies with solid underlying economics rather than weak, capital-destroying businesses.

6. Revenue 5-Year CAGR ≥ 12%

   • Purpose: Ensure companies have shown solid, sustained revenue growth.
   • Rationale:
     • A 12%+ compound annual growth rate over 5 years is a sign of structural growth, not just a one-off spike.
     • Strong growth stories often attract investor interest and can support the case for continued share price strength, making them more appealing for near-term picks.

7. One_Month_Rise_Prob ≥ 70%

   • Purpose: Focus on stocks that a model estimates have a relatively high probability of rising over the next month.
   • Rationale:
     • Explicitly targets your timeframe (“this month”) by using a short-term probability metric.
     • A 70% threshold narrows the list to names with historically favorable patterns or factor profiles for the coming month—though this is probabilistic, not a guarantee.

Why Results Match Your Request

• Timeframe alignment: The one_month_rise_prob filter and the 200-day moving average both aim to find stocks with positive short-to-medium-term momentum, which fits your “this month” focus.
• Market and venue match: The region and exchange filters ensure you’re strictly looking at mainstream U.S. stocks on NYSE, NASDAQ, and AMEX, as you requested.
• Quality and stability: The market-cap, ROE, and revenue growth filters tilt the screen toward larger, profitable, growing companies—more suitable candidates for many investors deciding what to buy now, rather than speculative gambles.
• Balanced approach: Combining fundamentals (ROE, growth), technicals (PriceAboveMA200), and a probabilistic near-term metric (one_month_rise_prob) gives a more rounded list of potential picks than relying on any single dimension.