Explore the Advanced Research Tools on Our Main Site to Improve Your Daily Market Analysis
Real-Time Data Scanners and Custom Filters
Standard market feeds often lag or miss subtle shifts. Our main site hosts a proprietary scanner that ingests tick-level data across 12 exchanges simultaneously. You can build custom filters based on volume surges, relative strength divergence, or unusual options flow. Unlike generic platforms, this tool lets you save complex multi-condition alerts (e.g., “stocks with RSI under 30 AND institutional buying >2% of float”). The scan runs server-side, updating every 2 seconds, so you never miss a breakout.
For day traders, the “Heat Map” module visualizes sector rotation in real time. Combine it with the “Gap Scanner” to pre-market identify stocks trading outside their normal volatility bands. These filters reduce noise by 40% compared to standard watchlists, according to internal tests.
Backtesting Engine with Machine Learning
Most backtesters assume static market conditions. Our engine uses a random forest model to simulate slippage, liquidity constraints, and regime changes. You can test a strategy against 15 years of historical data, then run a Monte Carlo simulation to assess robustness. The tool outputs a risk-adjusted return table and a drawdown calendar.
To refine entries, use the “Pattern Recognizer” – it scans for 47 chart patterns (e.g., bull flags, inverse head-and-shoulders) and calculates historical win rates for your specific timeframe. This bridges the gap between discretionary and systematic trading.
Sentiment Analytics and News Aggregation
Price action alone is half the picture. The research suite includes a natural language processing engine that monitors 3,500 news sources, earnings call transcripts, and social media chatter. It assigns a sentiment score per ticker (from -1 to +1) and highlights sudden shifts. For example, if a stock’s sentiment drops from +0.7 to -0.2 within an hour, the system sends an alert with the triggering headlines.
A separate “Insider Activity” tracker logs SEC Form 4 filings and cross-references them with company market cap. It flags unusual patterns, like a CEO selling while the board buys. This data updates within 10 minutes of filing, giving you an edge over delayed aggregators.
Correlation Matrix and Intermarket Analysis
Modern markets are interconnected. The correlation tool calculates rolling 30-day and 90-day coefficients between any two assets (stocks, bonds, currencies, commodities). You can overlay this with a “Divergence Indicator” – for instance, when gold and the dollar diverge from their historical 80% negative correlation, the system flags a potential regime change. This is critical for hedging and asset allocation.
Custom Dashboard and API Access
All tools feed into a single dashboard you can rearrange by widget. Save up to 50 layouts for different workflows: “Pre-market scan,” “Earnings day review,” “Swing trade monitor.” Each widget exports data to CSV or JSON for offline analysis. For developers, the API provides raw access to the scanner and sentiment endpoints with a rate limit of 1,000 requests per minute.
Finally, the “Journal” feature logs every trade you input manually or via API. It calculates expectancy, Sharpe ratio, and win rate per strategy. This turns your daily analysis into a measurable feedback loop for continuous improvement.
FAQ:
How often does the data update?
Real-time data updates every 2 seconds; sentiment data refreshes every 15 minutes; insider filings update within 10 minutes of SEC receipt.
Can I use the backtester without coding?
Yes. The visual strategy builder uses drag-and-drop logic blocks. No Python or JavaScript required.
Is there a mobile version of the tools?
The dashboard is fully responsive and works on any modern browser. Native iOS and Android apps are in beta.
How does the sentiment engine handle fake news?
It cross-references sources by domain authority and checks for duplication. Sources with a history of misinformation are weighted at 10% of normal influence.
What is the maximum historical range for backtesting?
15 years for US equities and ETFs; 5 years for forex and crypto pairs.
Reviews
Marcus T.
I cut my screen time by two hours using the gap scanner. The sentiment alerts caught a pump-and-dump before I saw it on Twitter. Worth every penny.
Linda K.
The correlation matrix saved me from a bad hedge last month. I saw the dollar/gold divergence flag and adjusted my portfolio before the selloff. Solid tool.
Raj P.
Backtesting engine is a beast. I tested a mean-reversion strategy on 10 years of SPY data, and the Monte Carlo showed I was fooling myself. Back to the drawing board, but now I know.
