✨Data Intelligence Lab@HKU✨
Official@hkuds · Hong Kong
Data Intelligence Lab provides command-line interfaces for cross-platform software control and quantitative financial research, signal generation, and portfolio risk assessment.
Agent Skills by ✨Data Intelligence Lab@HKU✨
Showing 231 vetted skills indexed across 5 GitHub repositories.
HKUDSmarket-intel
Reads AI-Trader financial event snapshots and market-intel API endpoints for trading context.
HKUDSmootdx
Fetches A-share OHLCV market data via the TDX binary TCP protocol.
HKUDSshadow-account
Extracts trading rules from user trade journals and backtests them across four markets.
HKUDSthesis-tracker
Builds and quarterly re-checks written investment theses with assumptions, red lines, and valuation anchors.
HKUDSashare-pre-st-filter
Predicts A-share ST and delisting risk from financial reports, dividends, and regulatory penalties.
HKUDSdividend-analysis
Analyzes dividend stocks for yield quality, payout sustainability, and yield-trap risk.
HKUDSalpha-zoo
Browse and benchmark prebuilt cross-sectional alpha factor libraries with IC and IR metrics.
HKUDStrade-journal
Analyzes broker trade journal exports to produce trading profiles and behavioral bias diagnostics.
HKUDSinvestor-lenses
Apply twelve named investor reasoning frameworks to pre-gathered evidence with ordered signals and hard disqualifiers.
HKUDSstrategy-discovery
Query trading strategies with per-regime backtest evidence and freshness verdicts.
HKUDSqveris
Discovers, inspects, and executes paid market data capabilities through the QVeris marketplace API.
HKUDSvnpy-export
Converts Vibe-Trading backtest strategies into runnable vnpy CtaTemplate Python classes.
HKUDSbottleneck-hunter
Decompose super-trend supply chains to identify Layer 2/3 bottleneck stocks with valuation gates.
HKUDSstrategy-dev-manager
Convert academic papers into backtested trading factors and strategies with decay monitoring.
HKUDSeastmoney
Query Eastmoney free APIs for A-share, HK, and US market data.
HKUDSprivate-company-research
Researches pre-IPO companies through six parallel analyst lenses with confidence-labeled data.
HKUDSmanagement-deep-dive
Evaluates company management integrity, ability, capital allocation, and governance into a weighted score.
HKUDScorrelation-regime
Detect correlation regimes and attribute crisis first-movers across multi-asset return series.
HKUDScross-market-strategy
Write signal_engine.py strategies for backtests spanning multiple markets like A-shares and crypto.
HKUDSdeep-company-series
Writes an 8-part deep-dive article series on a single company with strict fact-checking.
HKUDSresearch-goal
Tracks multi-step finance research goals with criteria, evidence, and audit status.
HKUDSresearch-discipline
Applies a five-bias self-check checklist to investment research tasks before searching.
HKUDSsec-edgar
Fetches SEC EDGAR filings, CIK mappings, and XBRL companyfacts financial series for U.S. tickers.
HKUDSmemory
Search conversation history logs and interpret Dream-managed memory files.
Frequently Asked Questions About ✨Data Intelligence Lab@HKU✨
FAQPage SchemaWhat specific financial tasks can these skills perform?▼
These skills enable quantitative research including backtesting, signal generation from OHLCV data, portfolio risk assessment using Monte Carlo simulations, and analysis of SEC filings or on-chain metrics for trading strategy development.
Who is the target persona for these technical capabilities?▼
The primary target personas are quantitative researchers, financial engineers, and system administrators who require programmatic control over desktop applications and high-frequency financial data processing environments.
What are the prerequisites for running these command-line interfaces?▼
Most interfaces require a standard terminal environment with Python 3.10+ installed, alongside specific dependencies like ffmpeg for media processing or relevant financial data provider tokens for market data retrieval.