About ScamDunk
Helping retail investors identify potential stock manipulation and pump-and-dump schemes through data-driven analysis.
Our Mission
ScamDunk was created to help everyday investors protect themselves from stock manipulation schemes. We believe that access to analytical tools shouldn't be limited to Wall Street professionals. Our platform analyzes publicly available market data and identifies patterns commonly associated with pump-and-dump schemes, helping you make more informed decisions.
How Our Scans Work
1. Market Data Analysis
We fetch real-time price, volume, and company data from regulated financial data providers.
2. Pattern Detection
Our algorithms identify price spikes, volume anomalies, and classic pump-and-dump signatures.
3. Structural Assessment
We evaluate stock characteristics like market cap and liquidity that affect manipulation risk.
4. Behavioral Analysis
If you provide pitch text, we analyze it for manipulation red-flag language patterns.
Coverage
What We Cover
- ✓US Stocks - NYSE, NASDAQ, OTC Markets
- ✓Real-time data - Current prices and volumes
- ✓Historical patterns - 100 days of price history
- ✓SEC alerts - Trading suspension lists
Not Currently Supported
- ✗International stocks - Non-US markets
- ✗Cryptocurrencies - Digital assets
- ✗Options & Futures - Derivatives
- ✗Bonds & ETFs - Other instruments
Understanding Results
HIGH Risk
Multiple significant red flags detected. Extreme caution warranted. Does not confirm a scam, but risk profile is elevated.
MEDIUM Risk
Some concerning signals detected. Additional research recommended before any decisions.
LOW Risk
Few or no manipulation indicators. Does NOT mean the stock is a good investment—only that obvious manipulation signals were not detected.
Our Data Sources
- Market Data: Real-time and historical data from licensed financial data providers
- Company Info: Exchange listings, market cap, updated daily
- Regulatory Data: SEC EDGAR feeds for trading suspensions
Important Documents
Questions?
Reach out at support@scamdunk.com