Finviz screener

FinViz Screener

Overview

Translate natural-language stock screening requests into FinViz screener filter codes, build the URL, and open it in Chrome. No API key required for public screener; FINVIZ Elite is auto-detected from $FINVIZ_API_KEY for enhanced functionality.

Key Features:

• Natural language → filter code mapping (English)
• URL construction with view type and sort order selection
• Elite/Public auto-detection (environment variable or explicit flag)
• Chrome-first browser opening with OS-appropriate fallbacks
• Strict filter validation to prevent URL injection

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When to Use This Skill

Explicit Triggers:

• "Find oversold large caps near 52-week lows"
• "Screen for tech sector value stocks"
• "Show me high-growth small caps on FinViz"
• "Screen for stocks with insider buying"
• "Show me FinViz breakout candidates"
• "Find stocks with dividend yield > 5% and ROE > 15%"

Implicit Triggers:

• User describes stock screening criteria using fundamental or technical terms
• User mentions FinViz screener or stock filtering
• User asks to find stocks matching specific financial characteristics

When NOT to Use:

• Deep fundamental analysis of a specific stock (use us-stock-analysis)
• Portfolio review with holdings (use portfolio-manager)
• Chart pattern analysis on images (use technical-analyst)
• Earnings-based screening (use earnings-trade-analyzer or pead-screener)

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Workflow

Step 1: Load Filter Reference

Read the filter knowledge base:

cat references/finviz_screener_filters.md

Step 2: Interpret User Request

Map the user's natural-language request to FinViz filter codes. Use the Common Concept Mapping table below for quick translation, and reference the full filter list for precise code selection.

Note: For range criteria (e.g., "dividend 3-8%", "P/E between 10 and 20"), use the {from}to{to} range syntax as a single filter token (e.g., fa_div_3to8, fa_pe_10to20) instead of combining separate _o and _u filters.

Common Concept Mapping:

User Concept	Filter Codes
High dividend	fa_div_o3 or fa_div_o5
Small cap	cap_small
Mid cap	cap_mid
Large cap	cap_large
Mega cap	cap_mega
Value / cheap	fa_pe_u20,fa_pb_u2
Growth stock	fa_epsqoq_o25,fa_salesqoq_o15
Oversold	ta_rsi_os30
Overbought	ta_rsi_ob70
Near 52W high	ta_highlow52w_b0to5h
Near 52W low	ta_highlow52w_a0to5l
Breakout	ta_highlow52w_b0to5h,sh_relvol_o1.5
Technology	sec_technology
Healthcare	sec_healthcare
Energy	sec_energy
Financial	sec_financial
Semiconductors	ind_semiconductors
Biotechnology	ind_biotechnology
US stocks	geo_usa
Profitable	fa_pe_profitable
High ROE	fa_roe_o15 or fa_roe_o20
Low debt	fa_debteq_u0.5
Insider buying	sh_insidertrans_verypos
Short squeeze	sh_short_o20,sh_relvol_o2
Dividend growth	fa_divgrowth_3yo10
Deep value	fa_pb_u1,fa_pe_u10
Momentum	ta_perf_13wup,ta_sma50_pa,ta_sma200_pa
Defensive	ta_beta_u0.5 or sec_utilities,sec_consumerdefensive
Liquid / high volume	sh_avgvol_o500 or sh_avgvol_o1000
Pullback from high	ta_highlow52w_10to30-bhx
Near 52W low reversal	ta_highlow52w_10to30-alx
Fallen angel	ta_highlow52w_b20to30h,ta_rsi_os40
AI theme	--themes "artificialintelligence"
Cybersecurity theme	--themes "cybersecurity"
AI + Cybersecurity	--themes "artificialintelligence,cybersecurity"
AI Cloud sub-theme	--subthemes "aicloud"
AI Compute sub-theme	--subthemes "aicompute"
Yield 3-8% (trap excluded)	fa_div_3to8
Mid-range P/E	fa_pe_10to20
EV undervalued	fa_evebitda_u10
Earnings next week	earningsdate_nextweek
IPO recent	ipodate_thismonth
Target price above	targetprice_a20
Recent news	news_date_today
High institutional	sh_instown_o60
Low float	sh_float_u20
Near all-time high	ta_alltime_b0to5h
High ATR	ta_averagetruerange_o1.5

Step 3: Present Filter Selection

Before executing, present the selected filters in a table for user confirmation:

| Type | Value | Meaning |
|---|---|---|
| Theme | artificialintelligence | Artificial Intelligence |
| Sub-theme | aicloud | AI - Cloud & Infrastructure |
| Filter | cap_small | Small Cap ($300M–$2B) |
| Filter | fa_div_o3 | Dividend Yield > 3% |
| Filter | fa_pe_u20 | P/E < 20 |
| Filter | geo_usa | USA |

View: Overview (v=111)
Mode: Public / Elite (auto-detected)

Ask the user to confirm or adjust before proceeding.

Step 4: Execute Script

Run the screener script to build the URL and open Chrome:

python3 scripts/open_finviz_screener.py \
  --filters "cap_small,fa_div_o3,fa_pe_u20,geo_usa" \
  --view overview

# Theme-only screening (no --filters required)
python3 scripts/open_finviz_screener.py \
  --themes "artificialintelligence,cybersecurity" \
  --url-only

# Theme + sub-theme + filters combined
python3 scripts/open_finviz_screener.py \
  --themes "artificialintelligence" \
  --subthemes "aicloud,aicompute" \
  --filters "cap_midover" \
  --url-only

Script arguments:

• --filters (optional): Comma-separated filter codes. Note: theme_* and subtheme_* tokens are not allowed here — use --themes / --subthemes instead.
• --themes (optional): Comma-separated theme slugs (e.g., artificialintelligence,cybersecurity). Accepts bare slugs or theme_-prefixed values.
• --subthemes (optional): Comma-separated sub-theme slugs (e.g., aicloud,aicompute). Accepts bare slugs or subtheme_-prefixed values.
• --elite: Force Elite mode (auto-detected from $FINVIZ_API_KEY if not set)
• --view: View type — overview, valuation, financial, technical, ownership, performance, custom
• --order: Sort order (e.g., -marketcap, dividendyield, -change)
• --url-only: Print URL without opening browser

At least one of --filters, --themes, or --subthemes must be provided.

Step 5: Report Results

After opening the screener, report:

1. The constructed URL
2. Elite or Public mode used
3. Summary of applied filters
4. Suggested next steps (e.g., "Sort by dividend yield", "Switch to Financial view for detailed ratios")

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Usage Recipes

Real-world screening patterns distilled from repeated use. Each recipe includes a starter filter set, recommended view, and tips for iterative refinement.

Recipe 1: High-Dividend Growth Stocks (Kanchi-Style)

Goal: High yield + dividend growth + earnings growth, excluding yield traps.

--filters "fa_div_3to8,fa_sales5years_pos,fa_eps5years_pos,fa_divgrowth_5ypos,fa_payoutratio_u60,geo_usa"
--view financial

Filter Code	Purpose
fa_div_3to8	Yield 3-8% (caps high-yield traps)
fa_sales5years_pos	Positive 5Y revenue growth
fa_eps5years_pos	Positive 5Y EPS growth
fa_divgrowth_5ypos	Positive 5Y dividend growth
fa_payoutratio_u60	Payout ratio < 60% (sustainability)
geo_usa	US-listed stocks

Iterative refinement: Start broad with fa_div_o3 → review results → add fa_div_3to8 to cap yield → add fa_payoutratio_u60 to exclude traps → switch to financial view for payout and growth columns.

Recipe 2: Minervini Trend Template + VCP

Goal: Stocks in a Stage 2 uptrend with volatility contraction (VCP setup).

--filters "ta_sma50_pa,ta_sma200_pa,ta_sma200_sb50,ta_highlow52w_0to25-bhx,ta_perf_26wup,sh_avgvol_o300,cap_midover"
--view technical

Filter Code	Purpose
ta_sma50_pa	Price above 50-day SMA
ta_sma200_pa	Price above 200-day SMA
ta_sma200_sb50	200 SMA below 50 SMA (uptrend)
ta_highlow52w_0to25-bhx	Within 25% of 52W high
ta_perf_26wup	Positive 26-week performance
sh_avgvol_o300	Avg volume > 300K
cap_midover	Mid cap and above

VCP tightening filters (add to narrow): ta_volatility_wo3,ta_highlow20d_b0to5h,sh_relvol_u1 — low weekly volatility, near 20-day high, below-average relative volume (contraction signal).

Recipe 3: Unfairly Sold-Off Growth Stocks

Goal: Fundamentally strong companies with recent sharp declines — potential mean reversion candidates.

--filters "fa_sales5years_o5,fa_eps5years_o10,fa_roe_o15,fa_salesqoq_pos,fa_epsqoq_pos,ta_perf_13wdown,ta_highlow52w_10to30-bhx,cap_large,sh_avgvol_o200"
--view overview

Filter Code	Purpose
fa_sales5years_o5	5Y sales growth > 5%
fa_eps5years_o10	5Y EPS growth > 10%
fa_roe_o15	ROE > 15%
fa_salesqoq_pos	Positive QoQ sales growth
fa_epsqoq_pos	Positive QoQ EPS growth
ta_perf_13wdown	Negative 13-week performance
ta_highlow52w_10to30-bhx	10-30% below 52W high
cap_large	Large cap
sh_avgvol_o200	Avg volume > 200K

After review: Switch to valuation view to check P/E and P/S for entry attractiveness.

Recipe 4: Turnaround Stocks

Goal: Companies with previously declining earnings now showing recovery — bottom-fishing with fundamental confirmation.

--filters "fa_eps5years_neg,fa_epsqoq_pos,fa_salesqoq_pos,ta_highlow52w_b30h,ta_perf_13wup,cap_smallover,sh_avgvol_o200"
--view performance

Filter Code	Purpose
fa_eps5years_neg	Negative 5Y EPS growth (prior decline)
fa_epsqoq_pos	Positive QoQ EPS growth (recovery)
fa_salesqoq_pos	Positive QoQ sales growth (recovery)
ta_highlow52w_b30h	Within 30% of 52W high (not at bottom)
ta_perf_13wup	Positive 13-week performance
cap_smallover	Small cap and above
sh_avgvol_o200	Avg volume > 200K

Recipe 5: Momentum Trade Candidates

Goal: Short-term momentum leaders near 52W highs with increasing volume.

--filters "ta_sma50_pa,ta_sma200_pa,ta_highlow52w_b0to3h,ta_perf_4wup,sh_relvol_o1.5,sh_avgvol_o1000,cap_midover"
--view technical

Filter Code	Purpose
ta_sma50_pa	Price above 50-day SMA
ta_sma200_pa	Price above 200-day SMA
ta_highlow52w_b0to3h	Within 3% of 52W high
ta_perf_4wup	Positive 4-week performance
sh_relvol_o1.5	Relative volume > 1.5x
sh_avgvol_o1000	Avg volume > 1M
cap_midover	Mid cap and above

Recipe 6: Theme Screening (AI + Sub-theme Drill-Down)

Goal: Find mid-cap+ AI stocks focused on cloud infrastructure and compute acceleration.

--themes "artificialintelligence"
--subthemes "aicloud,aicompute"
--filters "cap_midover"
--view overview

Type	Value	Purpose
Theme	artificialintelligence	AI theme universe
Sub-theme	aicloud	Cloud & Infrastructure vertical
Sub-theme	aicompute	Compute & Acceleration vertical
Filter	cap_midover	Mid cap and above

Multi-theme example: --themes "artificialintelligence,cybersecurity" selects stocks tagged with either theme (OR logic via | grouping).

Tips: Iterative Refinement Pattern

Screening works best as a dialogue, not a one-shot query:

1. Start broad — use 3-4 core filters to get an initial result set
2. Review count — if too many results (>100), add tightening filters; if too few (<5), relax constraints
3. Switch views — start with overview for a quick scan, then switch to financial or valuation for deeper inspection
4. Layer in technicals — after confirming fundamental quality, add ta_ filters to time entries
5. Save and iterate — bookmark the URL, then adjust one filter at a time to understand its impact

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Resources

• references/finviz_screener_filters.md — Complete filter code reference with natural language keywords (includes industry code examples; full 142-code list is in the Industry Codes section)
• scripts/open_finviz_screener.py — URL builder and Chrome opener