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79score
r/algotrading
SaaS subscription
Build

Evidence-Based Factor Screener

Build a SaaS stock screener that ranks indicators by empirical strength, then lets users screen equities using value, quality, and momentum factors with transparent evidence scores. The product should emphasize historical robustness, transaction-cost awareness, and sector-specific behavior rather than hype around any single indicator.

Rising +486%5 channels30-day mention trend: latest 2, peak 4, 30-day series
View on Reddit
Discovered Jun 22, 2026

Why this matters

You want to select stocks with methods that have more than a good story behind them, but every indicator seems to have defenders, critics, and conflicting backtests. You can find academic papers, blog posts, and charting tools, yet none of them make it easy to answer a practical question: which signals still look credible after costs, across sectors, and over changing market conditions? If you are not already running your own research stack, you end up stitching together books, spreadsheets, and partial backtests. That creates uncertainty right where confidence matters most: before you commit capital.

  • · Built for Self-directed investors and serious retail traders who want academically grounded stock screens without building their own quant pipeline..
  • · Most likely monetization: SaaS subscription.

The Pain · Narrative

You want to select stocks with methods that have more than a good story behind them, but every indicator seems to have defenders, critics, and conflicting backtests. You can find academic papers, blog posts, and charting tools, yet none of them make it easy to answer a practical question: which signals still look credible after costs, across sectors, and over changing market conditions? If you are not already running your own research stack, you end up stitching together books, spreadsheets, and partial backtests. That creates uncertainty right where confidence matters most: before you commit capital.

Score Breakdown

Pain Intensity9/10
Willingness to Pay6/10
Ease of Build6/10
Sustainability7/10

Market Signal

30-day mention trendPeak: 4
Sparkline: latest 2, peak 4, 30-day series
Channels covered
algotradingfront_pageproductivitystartupsChatGPT

Go-to-Market

Exact target user

Independent investors who already use stock screeners and want more evidence-driven factor selection without writing code.

Estimated user count

~100K-300K active globally

Primary acquisition channel

SEO long-tail

Price anchor

$29/month

First milestone

25 paying users from search traffic and finance-community outreach within 30 days

MVP Scope · 1–2 weeks

Week 1
  • Define 10 core factors with formulas and plain-English explanations
  • Connect one market data source and one fundamentals data source
  • Build a simple database schema for prices, fundamentals, and factor scores
  • Create a factor evidence page with research summary, caveats, and cost notes
  • Ship a basic stock screener UI with filters for value and cash-flow metrics
Week 2
  • Add sector-relative comparisons for each factor
  • Build historical factor performance charts by decile
  • Add simple transaction-cost assumptions to reported results
  • Implement watchlists and saved screens
  • Launch a landing page with one free evidence report to collect emails
MVP Features: Prebuilt factor library with evidence ratings · Stock screening by value, cash flow, earnings yield, and quality metrics · Sector-relative factor views and historical robustness dashboards

Differentiation

Existing solutions
Generic broker charting toolsCustom quant research stacksBooks and academic papers
Our angle
There is room for a user-friendly research and screening product that converts factor evidence, regime testing, and cost-aware validation into a practical decision tool for self-directed investors.

Why This Might Fail

Self-rebuttal — the most important trust signal

  1. 1The product may be perceived as another generic stock screener unless the evidence layer is clearly differentiated and trusted.
  2. 2Users may not convert if they can replicate core screens using free finance sites and public factor articles.
  3. 3Data licensing costs could compress margins before subscriber volume is high enough.

Evidence Summary

How AI synthesized this insight — no verbatim quotes

The discussion repeatedly favors value and cash-flow-oriented metrics over common chart indicators when the goal is stock selection. Several participants point to long-horizon factor research, while others warn that technical indicators often degrade after costs or regime changes. There is also repeated interest in combining signals rather than trusting one metric alone, which supports a screener that surfaces evidence, caveats, and implementation context.

1 1 post analyzed5 5 channelsAI · AI synthesized · no verbatim

Action Plan

Validate this opportunity before writing code

Recommended Next Step

Build

Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.

Landing Page Copy Kit

Ready-to-paste copy based on real Reddit community language — no editing required

Headline

Evidence-Based Factor Screener

Sub-headline

Build a SaaS stock screener that ranks indicators by empirical strength, then lets users screen equities using value, quality, and momentum factors with transparent evidence scores. The product should emphasize historical robustness, transaction-cost awareness, and sector-specific behavior rather than hype around any single indicator.

Who It's For

For Self-directed investors and serious retail traders who want academically grounded stock screens without building their own quant pipeline.

Feature List

✓ Prebuilt factor library with evidence ratings ✓ Stock screening by value, cash flow, earnings yield, and quality metrics ✓ Sector-relative factor views and historical robustness dashboards

Where to Validate

Share your landing page in r/r/algotrading — that's exactly where these pain points were discovered.

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Report & PRDBUSINESS

Other opportunities in the same theme

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Frequently asked questions

Who feels this pain?
Self-directed investors and serious retail traders who want academically grounded stock screens without building their own quant pipeline.
Is this a real opportunity?
This opportunity scores 79/100 on Pain Spotter's composite metric (pain intensity, willingness to pay, technical feasibility and sustainability). Validate further before committing engineering time.
How should I validate it?
Run 5 customer-discovery conversations with the target audience, post a landing page with a waitlist, and check the linked source post for recent activity before building.