A sophisticated quantitative trading skill that identifies and exploits market mispricings driven by investor irrationality and emotional extremes.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install behavioral-finance
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install behavioral-finance using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Behavioral Finance Strategy Skill?
The Behavioral Finance Strategy Skill is an advanced toolset designed for AI agents to capitalize on market inefficiencies caused by psychological factors. By quantifying cognitive biases such as overconfidence, anchoring, and herd behavior, this skill allows developers to move beyond traditional fundamental analysis.
Integrating this into your collection of Openclaw Skills enables the detection of irrational exuberance and panic selling. It provides a structured framework to transform qualitative sentiment into quantitative, actionable trading signals, helping agents navigate volatile market regimes with a behavioral edge.
Behavioral Finance Strategy Skill Use Cases
- Detecting buying opportunities after irrational panic selling and market overreactions.
- Identifying contrarian signals during periods of extreme retail or institutional sentiment.
- Exploiting calendar-based behavioral patterns like monthly or weekend effects.
- Leveraging the disposition effect to predict price reversals in winning or losing stocks.
- Managing risk by identifying market bubbles and liquidity traps before they burst.
How Behavioral Finance Strategy Skill Works
- Data Acquisition: The skill ingests real-time price and volume data alongside sentiment inputs from social media, news, and analyst ratings.
- Sentiment Quantification: It calculates a standardized sentiment index by weighting retail and institutional moods against historical volatility.
- Bias Identification: Algorithms analyze price movements relative to fundamentals to score indicators like the Overreaction Score and Herd Strength.
- Signal Generation: Based on the pattern type (e.g., V-shaped reversal or anchoring break), the skill generates contrarian or trend-continuation signals.
- Risk Filtering: Every signal is passed through a risk-adjustment layer that evaluates realized probability and liquidity constraints.
Behavioral Finance Strategy Skill Setup
To deploy this within your Openclaw Skills environment, ensure the necessary Python dependencies are installed:
pip install pandas numpy statistics
You must also configure access to the MDL_data_skill for real-time market data. Initialize the skill within your agent logic by defining the target stock codes and timeframe for pattern detection.
Behavioral Finance Strategy Skill Data Schema & Taxonomy
The skill organizes its behavioral analysis into a structured JSON output for easy agent consumption:
| Component | Description |
|---|---|
detected_patterns |
Array of identified biases (e.g., overreaction) with confidence scores and expected correction ranges. |
sentiment_indicators |
Quantitative metrics for retail, institutional, and social media sentiment levels. |
trading_signal |
Actionable trade data including entry zones, stop-loss, and target prices. |
risk_parameters |
Real-time limits on position sizing and holding periods based on signal strength. |
Behavioral Finance Strategy Skill Advanced Features
- Multi-agent support for cross-referencing behavioral signals with policy analysis and fundamental data.
- Automated backtesting engine specifically for behavioral patterns to validate strategy win rates.
- Real-time liquidity trap warnings and irrational exuberance alerts for bubble protection.
- Dynamic sentiment normalization that adjusts to historical medians and market cycles.
SKILL.md
Loading
Related Openclaw Skills
DePIN
A comprehensive AI agent skill for navigating, evaluating, and tracking Decentralized Physical Infrastructure Networks and their tokenomics.
Short Play Writer
A professional AI-powered scriptwriting assistant designed to create viral short-form dramas and AI manga scripts using industry-standard templates.
A-MEM Memory Organization
A-MEM Memory Organization provides a structured workflow for AI agents to capture, link, and evolve long-term project memory.
Defense Draft
A specialized tool for generating professional civil answer frameworks and defense document structures in response to legal complaints.
CN Holiday Reminder & Love Assistant
An AI-powered automation for tracking Chinese statutory holidays and personal romantic milestones with proactive notifications.
Agent Memory Tiers
A structured, self-updating memory system that provides AI agents with instant context via multi-layered state snapshots.
Featured*
