AI

Screening Filters

1. Market Cap ≥ $5B (market_cap: {'min': '5000000000'})

   • Purpose: Focus on larger, more established AI-related companies.
   • Rationale:
     • In AI, many tiny startups and speculative names exist; a $5B+ market cap threshold filters out the riskiest micro/small caps.
     • Larger companies are more likely to have meaningful AI R&D budgets, existing customer bases, and durable business models, making them more representative of the “AI sector” rather than short‑lived hype.

2. Price Above 200-Day Moving Average (moving_average_relationship: ['PriceAboveMA200'])

   • Purpose: Ensure the stocks are in a generally positive or stable long-term price trend.
   • Rationale:
     • The 200-day moving average is a common technical indicator for long-term trend.
     • Requiring price above this level tends to exclude AI names that are in strong downtrends or under severe distribution, and instead focuses on those where the market is currently rewarding their AI story and fundamentals.

3. AI / Tech-Related Themes (themes)
   ['AI Beneficiary', 'Software as a Service', 'Cloud Computing', 'Semiconductor Equipment & Materials', 'Technology', 'Robotics', 'Big Data', 'Cybersecurity']

   • Purpose: Directly target companies that are either core AI players or strongly exposed to AI demand.
   • Rationale:
     • AI Beneficiary: Explicitly flags companies expected to benefit from AI adoption—this is the most direct link to the query “AI.”
     • Software as a Service (SaaS): Many AI applications are delivered as cloud-based software products; leading AI platforms are often SaaS.
     • Cloud Computing: Training and deploying AI models is computationally intensive and heavily relies on cloud infrastructure providers and platforms.
     • Semiconductor Equipment & Materials: AI workloads need advanced chips (GPUs, specialized accelerators); upstream equipment and materials suppliers are critical enablers of AI.
     • Technology: A broad tech tag to capture diversified tech firms embedding AI across their product suites (search, office software, devices, etc.).
     • Robotics: Applied AI (computer vision, autonomy, automation) is central to modern robotics and industrial automation.
     • Big Data: AI models feed on data; firms specializing in data platforms, analytics, and data infrastructure are AI beneficiaries.
     • Cybersecurity: AI both drives new security products (AI-driven threat detection) and increases demand for advanced cybersecurity as systems get more complex.
       Together, these themes map out the AI ecosystem: core AI software, enabling infrastructure, and key application areas.

4. Quarterly Revenue YoY Growth ≥ 10% (quarter_revenue_yoy_growth: {'min': '10'})

   • Purpose: Select companies showing solid recent growth, potentially reflecting strong demand for AI-related products and services.
   • Rationale:
     • AI is a growth area; companies truly benefiting from AI are likely to show above-average revenue growth.
     • A 10%+ year-over-year quarterly growth threshold screens out stagnating or shrinking businesses that may talk about AI but aren’t seeing it translate into actual sales.

5. 5-Year Revenue CAGR ≥ 10% (revenue_5yr_cagr: {'min': '10'})

   • Purpose: Ensure growth is not just a one-quarter spike but part of a sustained multi-year trend.
   • Rationale:
     • AI-related leaders often have multi-year growth trajectories, as AI adoption builds over time.
     • Requiring a 10%+ compound annual growth rate over five years helps identify companies with durable growth engines, not just short-term AI hype.

Why Results Match the “AI” Query

• The theme filters directly target the AI value chain: core AI beneficiaries, cloud, chips, data, robotics, and cybersecurity, all of which are central to AI development and deployment.
• The growth filters (quarterly and 5-year revenue) help ensure the companies are actually capitalizing on AI trends in a measurable way, not just marketing themselves as “AI” without growth.
• The market cap and technical trend (price > 200-day MA) filters prioritize established, more liquid companies that the market currently views favorably—more consistent with investors seeking meaningful exposure to AI rather than speculative penny stocks.