From Desktop Spreadsheet to FinViz Screener — Best PracticesMoving your desktop spreadsheet of stocks, ETFs, or other financial instruments into the FinViz screener can save time, improve analysis, and make it easier to spot opportunities. This article covers a practical, end-to-end workflow: preparing your spreadsheet, formatting and exporting it, importing or using FinViz features effectively, automating the process, and maintaining clean, actionable data. Whether you’re a DIY retail trader, a portfolio manager, or a quant hobbyist, these best practices will help you get the most out of combining your local data with FinViz’s powerful screening tools.
Why move from a desktop spreadsheet to FinViz?
A spreadsheet offers flexibility for manual tracking, custom calculations, and private notes. FinViz provides fast visual screening, ready-made filters, charts, and news aggregation. Combining both allows you to:
- Keep sensitive/custom metrics locally while leveraging FinViz’s market data and visual tools.
- Rapidly screen public market data against your curated lists.
- Reduce manual lookup time and the risk of transcription errors.
1) Plan what you need to transfer
Start by deciding which data from your spreadsheet should be mirrored or used with FinViz:
- Symbol tickers (required).
- Exchange (if you track OTC, foreign, or specific exchanges).
- Position size, cost basis, and notes — keep these local if you prefer privacy.
- Custom metrics (e.g., proprietary score) — export if you’ll use them for reference, but FinViz won’t import custom columns into its screener; you’ll use them locally.
- Watchlist tags or groups to recreate in FinViz manually.
Keep in mind: FinViz primarily screens by ticker and public attributes; it does not import arbitrary custom fields into its screening filters.
2) Clean and standardize your spreadsheet
A clean dataset avoids errors during export/import and ensures accurate screening:
- Use a single column for tickers, all uppercase, with no extra spaces.
- Remove duplicates and delisted symbols.
- Verify ticker correctness (e.g., BRK.B vs BRK-B — use the format FinViz recognizes).
- Format dates consistently (ISO: YYYY-MM-DD) if you track timestamps.
- Ensure numeric fields use plain numbers (no currency symbols or commas) if you intend to export them.
Example: a minimal sheet for FinViz should have a column labeled “Ticker” with values like:
AAPL MSFT TSLA BRK-B 3) Exporting from desktop apps
How you export depends on the app you use.
- Microsoft Excel: File → Save As → CSV (Comma delimited) (*.csv).
- Google Sheets: File → Download → Comma-separated values (.csv).
- LibreOffice Calc: File → Save As → CSV.
Export tips:
- Save a copy before trimming columns.
- Use UTF-8 encoding to avoid character issues.
- If your tickers have hyphens or dots, check how your app exports them (Excel may change formats); export and open the CSV in a plain text editor to verify.
4) Getting your watchlist into FinViz
FinViz does not support direct bulk import of CSVs into its public free screener. However, there are several practical approaches:
- Manual entry: For small lists, paste tickers directly into FinViz’s Watchlist field (on the screener page) separated by commas.
- URL-based list: FinViz accepts a list of tickers in the URL query parameter for its screener. You can construct a URL like: https://finviz.com/screener.ashx?v=111&s=ta_basic&f=sh_avgvol_o1000,sh_price_o5,ta_perf_1w_u,ta_perf_1m_u&ft=4&c=0,1,2
(Replace the query with your tickers in the appropriate parameter.) - FinViz Elite features: The paid Elite plan supports saved watchlists and additional export options — consider upgrading if you need regular, native sync.
- Browser automation / scripts: Use a script (e.g., Python + Selenium) to log in (if Elite) and populate the watchlist or to navigate FinViz pages built around your tickers.
Practical tip: For quick screening without Elite, open the Screener page and paste your tickers into the search field as a comma-separated list, then apply filters.
5) Use FinViz filters effectively with your list
FinViz shines when you combine your list with its filters.
- Start broad, then refine: apply basic filters like market cap, average volume, and price to remove illiquid or micro-cap names.
- Use technical filters (moving averages, RSI, performance) to find momentum or mean-reversion setups.
- Use fundamental filters (PE, EPS growth, dividend yield) for value or income strategies.
- Sort results by performance, volume, or custom columns to prioritize candidates.
Example workflow:
- Paste your tickers into the ticker search.
- Filter: Market Cap > Large (if you want blue-chips), Avg Volume > 500k.
- Add technical: Price above 50-day SMA.
- Sort by 5-day performance to see recent movers.
6) Automating the workflow
For frequent syncs, automation reduces manual steps.
Options:
- Python script + requests/scraping: Fetch FinViz pages and parse the results for your tickers. Respect FinViz terms of service and rate limits.
- Selenium/WebDriver automation: Simulate browser actions to paste lists and capture results/screenshots. Useful if you need Elite-only features accessed via the UI.
- Spreadsheet add-ins / APIs: Use third-party connectors (some Excel add-ins fetch market data) and then programmatically compare against FinViz outputs.
Sample Python pseudocode for scraping (conceptual):
import requests from bs4 import BeautifulSoup def get_finviz_quote(ticker): r = requests.get(f"https://finviz.com/quote.ashx?t={ticker}") soup = BeautifulSoup(r.text, "html.parser") # parse price, change, pe, etc. return data Always throttle requests and cache results to avoid overloading the site.
7) Handling data privacy and proprietary metrics
Keep sensitive data local. Use FinViz for public attributes and visual screening; store position sizes, cost bases, and proprietary ratings in your spreadsheet. If you automate, ensure exported logs do not contain private notes.
8) Reconcile and validate results
After importing or screening, reconcile findings:
- Cross-check prices and key metrics against another source (broker or exchange) before trading.
- Spot-check random tickers to ensure formatting didn’t alter symbols.
- Keep a changelog when you update your local spreadsheet so you can revert if needed.
9) Maintainability — folder and naming conventions
- Use a clear folder structure: /watchlists/YYYY-MM-DD/ or /watchlists/strategy-name/
- Name CSVs with date and strategy: my_watchlist_momentum_2025-09-02.csv
- Add a README or metadata row describing fields.
10) Common pitfalls and troubleshooting
- FinViz ticker format mismatch (e.g., BRK-B vs BRK.B). Verify accepted formats.
- Excel auto-formatting (dates, large numbers): set column formats to Text for tickers.
- Rate limiting and scraping blocks: add delays, use caching, or use Elite features.
- Expect partial results when using complex filter combinations; test filters on a single known ticker first.
Quick checklist before importing
- Tick column uppercase, no spaces.
- Remove duplicates/delisted entries.
- Export as UTF-8 CSV.
- Test with 5–10 tickers before full list.
- Respect FinViz terms and limits when automating.
Example end-to-end mini workflow (practical)
- Clean tickers in Excel (Ticker column, Text format).
- Save as UTF-8 CSV.
- Open FinViz Screener → paste tickers into the search field.
- Apply basic filters (price, volume).
- Sort and export (if Elite) or copy results into your local file for tracking.
- Use a Python script weekly to snapshot FinViz data for your tickers.
Combining your desktop spreadsheet with FinViz gives you the best of both worlds: private, customizable tracking locally and fast, powerful market screening online. With good data hygiene, clear naming conventions, and cautious automation, you can build a reliable, repeatable workflow that scales with your trading or investing needs.
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