About LPPL Radar
LPPL Radar is a comprehensive financial analysis platform that uses the Log-Periodic Power Law Singularity (LPPLS) model to detect and analyze potential market bubbles across global stock markets. Our platform provides real-time screening, detailed chart analysis, and personalized tracking tools to help investors identify opportunities and risks.
What We Do
LPPL Radar continuously monitors stocks and financial instruments, applying advanced mathematical models to detect patterns that may indicate bubble formation or market corrections. Our system analyzes price movements to identify:
- Faster-than-Exponential Growth: Unsustainable price acceleration patterns that may signal an approaching correction
- Log-Periodic Oscillations: Oscillatory price behavior with increasing frequency, indicating potential critical transition points
- Confidence Indicators: Positive and negative confidence metrics that help assess the strength of detected patterns
Platform Features
Charts
Access charts with LPPLS model visualizations for the selected assets. Our charts display price movements alongside confidence indicators, helping you understand the underlying dynamics and potential bubble formations.
Screener
Our powerful screener allows you to browse and filter stocks from global markets. Search by ticker or company name, filter by country, and view confidence indicators.
Registered users can click on any row to view detailed interactive charts with LPPLS analysis overlays. Please note that the LPPLS calculation is computationally expensive, so up-to-date results are not available for all assets. In the future, you will be able to request (for a fee) a calculation for any instrument you’re interested in.
Indicators
Explore comprehensive indicator data that provides insights into market conditions.
Watchlist (Registered Users)
Create and manage a personalized watchlist of stocks you want to monitor closely. Track your selected instruments and receive updates on their LPPLS analysis status.
Alerts (Registered Users)
Set up custom alerts to be notified when specific conditions are met for stocks in your watchlist or across the entire market. Stay informed about significant changes in confidence indicators or model updates.
The LPPLS Model
LPPL Radar is powered by the Log-Periodic Power Law Singularity model, a mathematical framework that has been validated through analysis of major historical market events, including the 1929 crash, the 2000 dot-com bubble, and recent cryptocurrency cycles. The model identifies characteristic patterns in price movements that often precede significant market corrections.
The LPPLS model expresses the expected logarithm of an asset's price as:
E[ln p(t)] = A + B|tc - t|m + C|tc - t|m cos[ω ln|tc - t| - φ]
This formulation captures both the accelerating growth component and the log-periodic oscillations that characterize bubble dynamics. Our platform continuously computes these parameters for thousands of instruments, providing you with actionable insights.
Getting Started
You can start using LPPL Radar immediately without registration. Browse the screener, view public indicators, and explore the platform's capabilities. To unlock full features including detailed charts, personalized watchlists, and alerts, simply create a free account by clicking the user icon in the top-right corner.
Important Disclaimer
LPPL Radar provides analytical tools and indicators based on mathematical models. The LPPLS model identifies potential bubbles and critical times, not certainties. Market conditions can change rapidly, and external factors may disrupt predicted patterns. Our platform should be used as part of a comprehensive investment strategy that includes:
- Fundamental analysis of companies and markets
- Consideration of broader economic conditions
- Proper risk management and diversification
Past performance and model predictions do not guarantee future results. Always conduct your own research and make informed investment decisions.
Contact
Have questions or feedback? Reach out to us at [email protected]. We're always looking to improve the platform.