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R�#(�
zPrint CLI helpzQUANTCLAW DATA CLIz Available commands: zPairs Trading (Phase 32):z- python cli.py pairs-scan SECTOR [--limit N]z? python cli.py cointegration SYMBOL1 SYMBOL2 [--lookback DAYS]z@ python cli.py spread-monitor SYMBOL1 SYMBOL2 [--period PERIOD]z CDS Spreads (Phase 30):z+ python cli.py sovereign-spreads [COUNTRY]z* python cli.py corporate-spreads [RATING]z python cli.py spread-comparez( python cli.py credit-risk-score TICKERz Sector Rotation (Phase 33):z/ python cli.py sector-rotation [LOOKBACK_DAYS]z/ python cli.py sector-momentum [LOOKBACK_DAYS]z python cli.py economic-cyclez# Monte Carlo Simulation (Phase 34):zX python cli.py monte-carlo SYMBOL [--simulations N] [--days N] [--method gbm|bootstrap]z> python cli.py var SYMBOL [--confidence 0.95 0.99] [--days N]z* python cli.py scenario SYMBOL [--days N]z& Walk-Forward Optimization (Phase 37):z> python cli.py walk-forward SYMBOL [--strategy sma-crossover]z$ python cli.py overfit-check SYMBOLz& python cli.py param-stability SYMBOLz! Kalman Filter Trends (Phase 35):z/ python cli.py kalman SYMBOL [--period PERIOD]z4 python cli.py adaptive-ma SYMBOL [--period PERIOD]zH python cli.py regime-detect SYMBOL [--period PERIOD] [--window WINDOW]z% Multi-Timeframe Analysis (Phase 38):z python cli.py mtf SYMBOLz& python cli.py trend-alignment SYMBOLz( python cli.py signal-confluence SYMBOLz Smart Alerts (Phase 40):z] python cli.py alert-create SYMBOL --condition 'price>200' [--channels console,file,webhook]z% python cli.py alert-list [--active]z1 python cli.py alert-check [--symbols AAPL,TSLA]z% python cli.py alert-delete ALERT_IDz: python cli.py alert-history [--symbol AAPL] [--limit 50]z python cli.py alert-statsz Alert Backtesting (Phase 41):zO python cli.py alert-backtest SYMBOL --condition 'CONDITION' [--period PERIOD]z7 python cli.py signal-quality SYMBOL [--period PERIOD]z8 python cli.py alert-potential SYMBOL [--period PERIOD]z Order Book Depth (Phase 39):z. python cli.py order-book SYMBOL [--levels N]z python cli.py bid-ask SYMBOLz python cli.py liquidity SYMBOLz5 python cli.py imbalance SYMBOL [--period 1d|5d|1mo]z8 python cli.py support-resistance SYMBOL [--period 3mo]z Custom Alert DSL (Phase 42):z, python cli.py dsl-eval SYMBOL "EXPRESSION"zD python cli.py dsl-scan "EXPRESSION" [--universe SP500] [--limit N]z python cli.py dsl-helpz% Commodity Futures Curves (Phase 44):z0 python cli.py futures-curve SYMBOL [--limit N]z python cli.py contangoz3 python cli.py roll-yield SYMBOL [--lookback DAYS]z% python cli.py term-structure SYMBOLz& Satellite Imagery Proxies (Phase 46):z& python cli.py satellite-proxy TICKERz python cli.py shipping-indexz% python cli.py construction-activityz# python cli.py foot-traffic TICKERz python cli.py economic-indexz" Fed Policy Prediction (Phase 45):zJ python cli.py fed-watch # Comprehensive Fed policy analysiszN python cli.py rate-probability # Calculate rate hike/cut probabilitieszI python cli.py fomc-calendar # Show upcoming FOMC meeting dateszD python cli.py dot-plot # Dot plot consensus analysiszF python cli.py yield-curve # Treasury yield curve analysiszN python cli.py current-rate # Current fed funds rate & target rangez) EM Sovereign Spread Monitor (Phase 158):zU python cli.py embi-global # JPMorgan EMBI Global spread (main benchmark)zW python cli.py regional-spreads # Regional breakdown (LatAm, Asia, Europe, MENA)zR python cli.py credit-quality # High yield vs investment grade comparisonzM python cli.py spread-history [DAYS] [SERIES_ID] # Historical spread trendszL python cli.py em-report # Comprehensive EM sovereign analysisz( EM Currency Crisis Monitor (Phase 184):zU python cli.py em-fx-reserves Brazil # Get FX reserves data for EM countryzR python cli.py em-current-account Turkey # Get current account balance datazR python cli.py em-reer Argentina # Get real effective exchange ratez[ python cli.py em-crisis-risk India # Calculate comprehensive crisis risk scorezY python cli.py em-regional-overview latam # Regional overview (all/latam/asia/emea)zJ Countries: Brazil, Mexico, Argentina, China, India, Indonesia, Thailand,zG Philippines, Malaysia, Russia, Turkey, South Africa, Polandz& Crypto On-Chain Analytics (Phase 43):zT python cli.py onchain ETH # Get Ethereum on-chain metricszR python cli.py whale-watch BTC [--min 100] # Track Bitcoin whale walletszB python cli.py dex-volume [--protocol uniswap] [--chain ethereum]zP python cli.py gas-fees # Current Ethereum gas feeszS python cli.py token-flows USDT [--hours 24] # Track token transfer volumesz" Peer Network Analysis (Phase 48):zT python cli.py peer-network TICKER # Analyze company relationshipszP python cli.py compare-networks AAPL,MSFT,GOOGL # Compare multiple companieszO python cli.py map-dependencies TICKER # Map revenue dependenciesz# Political Risk Scoring (Phase 49):z] python cli.py geopolitical-events [--country COUNTRY] [--keywords KEYWORDS] [--hours HOURS]zS python cli.py sanctions-search [--entity NAME] [--type country|individual|entity]zV python cli.py regulatory-changes [--sector SECTOR] [--country COUNTRY] [--days DAYS]z[ python cli.py country-risk COUNTRY_CODE # Get World Bank governance indicatorsz% Revenue Quality Analysis (Phase 52):z\ python cli.py revenue-quality TICKER # Comprehensive revenue quality analysisz[ python cli.py dso-trends TICKER # Days Sales Outstanding trend analysiszW python cli.py channel-stuffing TICKER # Detect channel stuffing red flagszR python cli.py cash-flow-divergence TICKER # CFO vs net income divergencez% Earnings Quality Metrics (Phase 59):ze python cli.py earnings-quality TICKER # Accruals ratio, Beneish M-Score, Altman Z-ScorezY python cli.py accruals-trend TICKER # Accruals ratio trend over 4 periodsz\ python cli.py fraud-indicators TICKER # Quick fraud/distress red flags summaryz# Executive Compensation (Phase 51):zo python cli.py exec-comp TICKER # Executive compensation breakdown (CEO, CFO, top officers)z^ python cli.py pay-performance TICKER # Pay-for-performance correlation analysiszk python cli.py comp-peer-compare TICKER # Peer compensation comparison with percentile rankingszi python cli.py shareholder-alignment TICKER # Shareholder alignment metrics and insider ownershipz# Share Buyback Analysis (Phase 56):zt python cli.py buyback-analysis TICKER # Full buyback report: authorization vs execution, dilution, ROIzq python cli.py share-count-trend TICKER # Shares outstanding history and quarter-over-quarter changesze python cli.py buyback-yield TICKER # Buyback yield calculation (buybacks/market cap)zi python cli.py dilution-impact TICKER # Stock-based compensation dilution vs buyback offsetz% Peer Earnings Comparison (Phase 53):zc python cli.py peer-earnings TICKER # Compare earnings patterns across sector peerszY python cli.py beat-miss-history TICKER # Detailed beat/miss pattern analysiszb python cli.py guidance-tracker TICKER # Track management guidance and analyst trendsze python cli.py estimate-dispersion TICKER # Analyze analyst estimate spread and uncertaintyz Tax Loss Harvesting (Phase 55):zY python cli.py tlh-scan AAPL,TSLA,MSFT,AMZN,META # Scan portfolio for TLH opportunitieszZ python cli.py wash-sale-check TSLA 2025-01-15 # Check wash sale rule window (30 days)zV python cli.py tax-savings AAPL --cost-basis 180 --shares 100 # Estimate tax savingszZ python cli.py tlh-replacements TSLA # Suggest sector replacement securitiesz$ Dividend Sustainability (Phase 57):zb python cli.py dividend-health TICKER # Comprehensive dividend sustainability reportzQ python cli.py payout-ratio TICKER # Payout ratio trend analysisz_ python cli.py fcf-coverage TICKER # Free cash flow dividend coverage analysisz_ python cli.py dividend-cut-risk TICKER # Probability of dividend cut score (0-100)z* Crypto Correlation Indicators (Phase 54):zc python cli.py btc-dominance # BTC dominance trend and altcoin season signalzj python cli.py altcoin-season # Altcoin season index (% of top 50 outperforming BTC)zb python cli.py defi-tvl-correlation # DeFi TVL correlation with NASDAQ/tech stockszm python cli.py crypto-equity-corr # Crypto-equity correlation matrix (BTC/ETH/BNB vs FAANG)z$ Institutional Ownership (Phase 58):zv python cli.py 13f-changes TICKER # Track institutional 13F changes (new/increased/decreased/exited)zh python cli.py whale-accumulation TICKER # Detect whale accumulation or distribution patternszm python cli.py top-holders TICKER [--limit 20] # Get top institutional holders and concentration metricszn python cli.py smart-money TICKER # Track famous investor (Buffett, Ackman, Burry) positionsz) Insider Transaction Heatmap (Phase 137):za python cli.py insider-summary [--days 7] # Sector-wide insider buying/selling patternszd python cli.py insider-sector SECTOR [--days 30] # Deep dive: insider clusters in specific sectorz^ python cli.py insider-ticker TICKER [--days 90] # Insider transaction history for a tickerz' Convertible Bond Arbitrage (Phase 64):z] python cli.py convertible-scan # Scan for convertible bond opportunitieszQ python cli.py conversion-premium TSLA # Conversion premium analysiszT python cli.py convertible-arb MSTR # Arbitrage opportunity analysisz[ python cli.py convertible-greeks COIN # Delta/gamma for convertible positionsz( Sustainability-Linked Bonds (Phase 71):zR python cli.py slb-market # Overall SLB market dashboardzI python cli.py slb-issuer ENEL # Issuer SLB analysiszZ python cli.py slb-kpi-tracker # Track upcoming KPI measurement dateszX python cli.py slb-coupon-forecast # Forecast potential coupon step-upsz# Short Squeeze Detector (Phase 65):zl python cli.py squeeze-scan [--tickers GME,AMC] # Scan market for high short interest squeeze candidatesza python cli.py squeeze-score GME # Calculate squeeze probability score (0-100)zV python cli.py short-interest TSLA # Detailed short interest analysiszZ python cli.py days-to-cover AMC # Days to cover & borrow cost estimatez Dark Pool Tracker (Phase 61):zg python cli.py dark-pool-volume TICKER # Estimate dark pool volume percentage (OTC vs lit)zh python cli.py block-trades TICKER # Detect large block trades (institutional activity)zf python cli.py institutional-accumulation TICKER [--period DAYS] # Accumulation/distribution patternzm python cli.py off-exchange-ratio TICKER [--period DAYS] # Off-exchange vs lit exchange ratio trendz$ Market Regime Detection (Phase 66):zo python cli.py market-regime # Current market regime classification (risk-on/off/crisis)zW python cli.py regime-history # Regime timeline over last 60 dayszx python cli.py risk-dashboard # Comprehensive risk-on/off dashboard with volatility & correlationszk python cli.py correlation-regime # Cross-asset correlation state and breakdown detectionz) Correlation Anomaly Detector (Phase 87):zo python cli.py corr-breakdown --ticker1 AAPL --ticker2 MSFT # Detect correlation breakdown between two assetsze python cli.py corr-scan --tickers SPY,TLT,GLD,QQQ # Scan correlation matrix for anomalieszu python cli.py corr-regime --tickers SPY,TLT,GLD,DBC # Detect market regime shifts via correlation structurez� python cli.py corr-arbitrage --tickers XLF,XLK,XLE # Find statistical arbitrage opportunities from correlation breakdownsz& Corporate Action Calendar (Phase 63):zt python cli.py corporate-calendar TICKER # Upcoming corporate actions (dividends, splits, special events)zd python cli.py split-history TICKER # Stock split history with price impact analysisza python cli.py dividend-calendar [TICKERS] # Upcoming dividend ex-dates across watchlistzi python cli.py spinoff-tracker # Recent/upcoming spin-offs and special distributionsz, Stock Split & Corporate Events (Phase 146):zq python cli.py stock-split-history TICKER [--years N] # Complete split history with cumulative factorszg python cli.py stock-split-impact TICKER [--date YYYY-MM-DD] # Pre/post split price impact analysiszl python cli.py stock-corporate-actions TICKER [--years N] # All corporate actions with impact metricszo python cli.py stock-compare-splits TICKER1,TICKER2,... [--days N] # Compare split performance across tickersz" 13D/13G Filing Alerts (Phase 68):z` python cli.py filing-alerts-recent [--hours 24] [--type 'SC 13D'] # Recent activist filingsz_ python cli.py filing-alerts-search TESLA [--type '13D'] # Search company filingszn python cli.py filing-alerts-activists [--min-filings 3] # Active filers with multiple campaignsz` python cli.py filing-alerts-watch [--interval 15] [--iterations 4] # Monitor for new filingsz Proxy Fight Tracker (Phase 69):zi python cli.py proxy-filings TICKER [--years 3] # Fetch proxy-related filings (DEF 14A, DEFA14A, 8-K)z^ python cli.py proxy-contests TICKER # Detect proxy contests (PREC14A, DEFC14A)z] python cli.py proxy-voting TICKER # Fetch voting results from 8-K Item 5.07za python cli.py proxy-advisory TICKER # Information on ISS/Glass Lewis data sourceszh python cli.py proxy-summary TICKER # Comprehensive proxy fight analysis with risk scorez' Activist Success Predictor (Phase 67):zc python cli.py activist-predict TICKER # Predict activist campaign success probabilityzh python cli.py activist-history # Historical activist campaign outcomes and patternszV python cli.py activist-targets [--sector SECTOR] # Scan for likely activist targetsz^ python cli.py governance-score TICKER # Company governance quality score (0-100)z! Climate Risk Scoring (Phase 72):zj python cli.py climate-risk TICKER # Composite climate risk score (physical + transition)zt python cli.py physical-risk TICKER # Physical risk exposure (floods, hurricanes, drought, wildfire)zs python cli.py transition-risk TICKER # Carbon transition risk (pricing, regulation, stranded assets)ui python cli.py carbon-scenario TICKER # Scenario analysis (1.5°C vs 2°C vs 3°C pathways)z Factor Timing Model (Phase 73):zf python cli.py factor-timing # Current factor regime and recommended allocationzu python cli.py factor-rotation # Adaptive factor rotation signals (STRONG_BUY, OVERWEIGHT, etc.)z\ python cli.py factor-performance [PERIOD] # Factor returns comparison (1y, 6m, 3m)zm python cli.py factor-regime-history [--days N] # Historical regime timeline (RISK_ON, RISK_OFF, NEUTRAL)z ML Factor Discovery (Phase 74):zt python cli.py discover-factors TICKERS # Auto-discover predictive factors (price, volume, fundamentals)zf python cli.py factor-ic [--top-n 20] # Information Coefficient rankings for all factorsz^ python cli.py factor-backtest FACTOR_NAME # Walk-forward backtest of specific factorze python cli.py feature-importance [--top-n 20] # ML ensemble feature importance (RF, GBM, Lasso)z& AI Earnings Call Analyzer (Phase 76):zf python cli.py earnings-tone TICKER # Real-time tone detection with LLM-style analysiszl python cli.py confidence-score TICKER # Executive confidence scoring via multi-factor analysiszd python cli.py language-shift TICKER # Quarter-over-quarter language change detectionzg python cli.py hedging-detector TICKER # Advanced hedging language detection with examplesz& Regulatory Event Calendar (Phase 78):zd python cli.py econ-calendar # Upcoming economic events (FOMC, CPI, GDP, NFP)z` python cli.py event-reaction CPI [--years 5] # Historical market reaction to CPI releaseszb python cli.py event-volatility FOMC # Volatility forecast around next FOMC meetingz^ python cli.py event-backtest NFP --years 5 # Backtest NFP employment report reactionsz( Alert Backtesting Dashboard (Phase 80):zg python cli.py dashboard-backtest rsi --ticker AAPL [--years 3] [--hold-days 5] # Backtest RSI alertszq python cli.py dashboard-backtest volume --ticker TSLA [--years 3] # Backtest volume spike alertszs python cli.py dashboard-backtest breakout --ticker NVDA [--years 3] # Backtest price breakout alertsz` python cli.py dashboard-performance [--years 3] # Compare all alert types across tickerszn python cli.py dashboard-optimize TICKER [--alert-type rsi] [--years 3] # Optimize alert parameterszd python cli.py dashboard-report [--output report.json] # Generate comprehensive performance reportz PDF Report Exporter (Phase 79):zV python cli.py export-pdf AAPL --modules all # Full PDF reportzX python cli.py export-pdf TSLA --modules earnings,technicals # Selective moduleszT python cli.py batch-report AAPL,MSFT,GOOGL # Batch reportszZ python cli.py report-template list # Available templatesz# Smart Data Prefetching (Phase 83):zY python cli.py prefetch-stats # Show usage patterns and predictionszT python cli.py prefetch-warmup # Warm cache with predicted datazY python cli.py cache-status # Show cache hit rates and statisticszR python cli.py prefetch-config --top 20 # Configure prefetch pool sizezV python cli.py prefetch-config --confidence 0.6 # Set minimum confidence thresholdzP python cli.py prefetch-config --enable true # Enable/disable prefetchingz- Multi-Source Data Reconciliation (Phase 84):z_ python cli.py reconcile-price SYMBOL # Compare price across Yahoo/CoinGecko/FREDzd python cli.py data-quality-report # Overall data quality metrics and discrepancieszh python cli.py source-reliability # Source reliability rankings with confidence scoresz^ python cli.py discrepancy-log [--hours 24] # Recent data discrepancies across sourceszT python cli.py discrepancy-log --symbol AAPL # Filter discrepancies by symbolz( Live Earnings Transcription (Phase 82):zX python cli.py earnings-schedule [DAYS] # Upcoming earnings this week/periodzd python cli.py transcript-signals TICKER # Extract trading signals from latest transcriptzU python cli.py earnings-countdown TICKER # Days until next earnings reportz` python cli.py transcript-compare TICKER # Compare latest vs prior quarter transcriptz% Cross-Exchange Arbitrage (Phase 77):zc python cli.py arb-scan [SYMBOLS] # Scan for price discrepancies across exchangesz] python cli.py arb-spread SYMBOL # Detailed cross-exchange spread analysiszX python cli.py arb-history SYMBOL [--days N] # Historical arbitrage profitabilityzY python cli.py exchange-latency # Exchange execution speed comparisonz$ Neural Price Prediction (Phase 85):zT python cli.py predict-price AAPL --horizon 5d # LSTM price forecast (1d/5d/20d)zX python cli.py prediction-confidence TSLA # Uncertainty quantification with CIzX python cli.py model-comparison NVDA # Compare LSTM vs statistical modelszT python cli.py prediction-backtest MSFT --years 1 # Historical prediction accuracyz$ SPAC Lifecycle Tracker (Phase 148):zX python cli.py spac-list [--status searching|announced|completed] # List tracked SPACsze python cli.py spac-trust TICKER # Calculate trust value per sharezX python cli.py spac-timeline TICKER # Show deal timelinez^ python cli.py spac-redemptions TICKER # Estimate redemption riskzb python cli.py spac-arbitrage # Find arbitrage opportunitieszV python cli.py spac-search [KEYWORD] # Search for SPACsz Examples:z$ python cli.py cointegration KO PEPz- python cli.py pairs-scan beverage --limit 5z5 python cli.py spread-monitor AAPL MSFT --period 60dz" python cli.py sector-rotation 90z python cli.py kalman AAPLz, python cli.py adaptive-ma TSLA --period 1yz- python cli.py regime-detect SPY --window 30zV python cli.py black-litterman --tickers AAPL,MSFT,GOOGL --views AAPL:0.20,GOOGL:0.12z9 python cli.py equilibrium-returns --tickers SPY,QQQ,IWMzQ python cli.py portfolio-optimize --tickers AAPL,MSFT,GOOGL --target-return 0.15z? python cli.py monte-carlo AAPL --simulations 10000 --days 252z/ python cli.py var TSLA --confidence 0.95 0.99z( python cli.py scenario NVDA --days 180z9 python cli.py walk-forward SPY --strategy sma-crossoverz" python cli.py overfit-check AAPLz$ python cli.py param-stability TSLAz python cli.py mtf AAPLz$ python cli.py trend-alignment TSLAz& python cli.py signal-confluence NVDAz8 python cli.py dsl-eval AAPL "price > 200 AND rsi < 30"z? python cli.py dsl-scan "rsi < 25" --universe SP500 --limit 10z= python cli.py dsl-eval TSLA "sma(20) crosses_above sma(50)"z* python cli.py futures-curve CL --limit 6z+ python cli.py roll-yield GC --lookback 90z! python cli.py term-structure NGz# python cli.py satellite-proxy WMTz! python cli.py foot-traffic AAPLz python cli.py country-risk USAz? python cli.py geopolitical-events --country Russia --hours 24z. python cli.py sanctions-search --entity Iranz= python cli.py regulatory-changes --sector finance --days 30z% python cli.py buyback-analysis AAPLz& python cli.py share-count-trend MSFTz# python cli.py buyback-yield GOOGLz$ python cli.py dilution-impact METAz python cli.py 13f-changes AAPLz' python cli.py whale-accumulation TSLAz+ python cli.py top-holders NVDA --limit 20z! python cli.py smart-money GOOGLz6 python cli.py squeeze-scan --min-score 50 --limit 10z! python cli.py squeeze-score GMEz# python cli.py short-interest TSLAz! python cli.py days-to-cover AMCz' python cli.py corporate-calendar AAPLz" python cli.py split-history TSLAz2 python cli.py dividend-calendar AAPL,MSFT,JNJ,KOz python cli.py spinoff-trackerz% python cli.py dark-pool-volume AAPLz! python cli.py block-trades TSLAz; python cli.py institutional-accumulation NVDA --period 30z2 python cli.py off-exchange-ratio SPY --period 20z python cli.py market-regimez python cli.py regime-historyz python cli.py risk-dashboardz" python cli.py correlation-regimez< python cli.py corr-breakdown --ticker1 AAPL --ticker2 MSFTz3 python cli.py corr-scan --tickers SPY,TLT,GLD,QQQz5 python cli.py corr-regime --tickers SPY,TLT,GLD,DBCz4 python cli.py corr-arbitrage --tickers XLF,XLK,XLEz/ python cli.py filing-alerts-recent --hours 48z* python cli.py filing-alerts-search TESLAz7 python cli.py filing-alerts-activists --min-filings 3z% python cli.py activist-predict AAPLz python cli.py activist-historyz4 python cli.py activist-targets --sector Technologyz% python cli.py governance-score MSFTz! python cli.py climate-risk AAPLz! python cli.py physical-risk XOMz" python cli.py transition-risk BPz$ python cli.py carbon-scenario TSLAz python cli.py factor-timingz python cli.py factor-rotationz% python cli.py factor-performance 6mz/ python cli.py factor-regime-history --days 90z: python cli.py discover-factors AAPL,MSFT,GOOGL,AMZN,METAz$ python cli.py factor-ic --top-n 30z+ python cli.py factor-backtest momentum_3mz/ python cli.py feature-importance --horizon 5dz" python cli.py earnings-tone AAPLz% python cli.py confidence-score TSLAz# python cli.py language-shift MSFTz% python cli.py hedging-detector NVDAz python cli.py econ-calendarz, python cli.py event-reaction CPI --years 3z% python cli.py event-volatility FOMCz, python cli.py event-backtest NFP --years 5z' python cli.py arb-scan AAPL TSLA NVDAz python cli.py arb-spread AAPLz* python cli.py arb-history TSLA --days 60z python cli.py exchange-latencyz> python cli.py dashboard-backtest rsi --ticker AAPL --years 3zE python cli.py dashboard-backtest volume --ticker TSLA --hold-days 7z% python cli.py dashboard-performancez= python cli.py dashboard-optimize NVDA --alert-type breakoutz@ python cli.py dashboard-report --output alert_performance.jsonz- python cli.py export-pdf AAPL --modules allz= python cli.py export-pdf TSLA --modules earnings,technicalsz, python cli.py batch-report AAPL,MSFT,GOOGLz$ python cli.py report-template listz python cli.py prefetch-statsz python cli.py prefetch-warmupz python cli.py cache-statusz9 python cli.py prefetch-config --top 20 --confidence 0.6z$ python cli.py reconcile-price AAPLz1 python cli.py reconcile-price BTC --type cryptoz# python cli.py data-quality-reportz" python cli.py source-reliabilityz8 python cli.py discrepancy-log --hours 48 --symbol TSLAz/ python cli.py predict-price AAPL --horizon 5dz* python cli.py prediction-confidence TSLAz% python cli.py model-comparison NVDAz2 python cli.py prediction-backtest MSFT --years 1z# python cli.py country-profile USAzB python cli.py country-profile CHN --indicators GDP,INFLATION,FDIz& python cli.py countries --region EASz! python cli.py indicator USA GDPz; python cli.py compare USA,CHN,JPN,DEU,GBR --indicator GDPz python cli.py search Unitedz3 python cli.py regional EAS --indicator GDP_GROWTHz python cli.py indicatorsz, python cli.py spac-list --status announcedz python cli.py spac-trust DWACz" python cli.py spac-timeline LCIDz% python cli.py spac-redemptions DWACz python cli.py spac-arbitragez! python cli.py spac-search lucidz# Global PMI Aggregator (Phase 106):zU python cli.py pmi-country USA # US Manufacturing & Services PMIzN python cli.py pmi-country CHN --type both # China PMI (both sectors)zY python cli.py pmi-global manufacturing # Global PMI snapshot (30+ countries)zW python cli.py pmi-compare USA,CHN,DEU,JPN # Compare PMI across major economieszK python cli.py pmi-regional Europe --type services # European services PMIzP python cli.py pmi-divergence --months 12 # Mfg vs Services divergencezL python cli.py pmi-list # List all 30+ countriesz) Central Bank Balance Sheets (Phase 109):zb python cli.py cb-fed # Federal Reserve H.4.1 balance sheet (weekly)zb python cli.py cb-ecb # European Central Bank balance sheet (weekly)z[ python cli.py cb-boj # Bank of Japan balance sheet (monthly)zd python cli.py cb-pboc # People's Bank of China balance sheet (monthly)zd python cli.py cb-global # Compare all major central banks (QE/QT status)zf python cli.py cb-reserves # Fed reserve balances detail (liquidity analysis)zX python cli.py cb-fed --api-key YOUR_KEY # Use FRED API key for real-time dataz python cli.py pmiz python cli.py gdpz python cli.py tradez python cli.py fx-reservesz python cli.py yuanz python cli.py industrialz python cli.py inflationz python cli.py dashboardz, python cli.py cia-factbook 'United States'zA python cli.py cia-factbook-compare China 'United States' Russiaz/ python cli.py cia-factbook-demographics Indiaz, python cli.py cia-factbook-military Israelz* python cli.py cia-factbook-trade Germanyz- python cli.py cia-factbook-resources Brazilz< python cli.py cia-factbook-scan --output factbook_all.jsonz) US Treasury Auctions & Debt (Phase 118):z_ python cli.py treasury-recent [days] [type] # Recent auction results (default: 30 days)zO python cli.py treasury-upcoming [days] # Upcoming auction schedulezW python cli.py treasury-tic [country] # Foreign holdings of US TreasurieszQ python cli.py treasury-debt # Current US debt outstandingzR python cli.py treasury-performance [days] # Auction performance analysiszM python cli.py treasury-dashboard # Comprehensive dashboardz$ Types: Bill, Note, Bond, TIPS, FRNz" Treasury Yield Curve (Phase 154):zU python cli.py yield-curve # Current yield curve (1M to 30Y)zZ python cli.py yield-history [days] # Historical curves (default: 90 days)zW python cli.py yield-analyze # Curve shape analysis & inversionszW python cli.py yield-compare [days] # Compare curves (default: 30 days)zS python cli.py yield-maturity 10Y [days] # Specific maturity time seriesz& Sovereign Rating Tracker (Phase 164):za python cli.py sovereign-ratings [days] # All rating changes across S&P/Moody's/FitchzT python cli.py sovereign-country <name> # Ratings for a specific countryzQ python cli.py sovereign-downgrades [days] # Recent sovereign downgradeszO python cli.py sovereign-upgrades [days] # Recent sovereign upgradeszY python cli.py sovereign-watch # Countries on negative watch/outlookzo python cli.py sovereign-ig-changes [days] # Investment grade transitions (fallen angels/rising stars)zT python cli.py sovereign-dashboard # Comprehensive rating dashboardz' Relative Valuation Matrix (Phase 143):ze python cli.py valuation-heatmap [--format text|json] # Cross-sector valuation comparison heatmapzl python cli.py valuation-sector Technology # Get valuation metrics for all stocks in a sectorzl python cli.py valuation-stock AAPL # Comprehensive valuation metrics for single stockzX python cli.py valuation-peers AAPL MSFT GOOGL # Compare peer group valuationz_ python cli.py valuation-screen pe_trailing 15 # Screen for stocks with P/E below 15z^ python cli.py valuation-screen peg_ratio 1.5 --comparison above # Find stocks with high PEGzV python cli.py valuation-sectors # List all available sectorsz' ADR/GDR Arbitrage Monitor (Phase 147):z{ python cli.py adr-spread BP # Calculate arbitrage spread for BP ADR vs London ordinary shareszJ python cli.py adr-scan [--min-spread 50] [--sort-by spread|volume|alpha]ze # Scan all ADRs for arbitrage opportunitieszd python cli.py adr-compare BABA JD BIDU # Compare Chinese ADR spreads side-by-sidezw python cli.py adr-list [--currency JPY] # List all known ADR/GDR pairs, optionally filter by currencyz+ BIS Global Banking Statistics (Phase 117):zK python cli.py dataflows # List all BIS datasetsz= python cli.py cross-border --reporting US --counterparty CNzT # Cross-border banking positionszP python cli.py derivatives # OTC derivatives statisticszT python cli.py derivatives-by-type # Derivatives by instrument typezT python cli.py fx-turnover --year 2022 # FX market turnover (Triennial)zO python cli.py fx-centers --countries GB,US,SG # Compare FX market centerszQ python cli.py global-liquidity # Global liquidity indicatorszA python cli.py debt-securities --sector financial --currency USDzS # International debt securitiesz5 python cli.py property-prices US --type residentialzL # Property price indiceszO python cli.py country-profile GB # Comprehensive BIS profilezR python cli.py countries # List BIS reporting countriesz( Carbon Credits & Emissions (Phase 177):za python cli.py eu-ets-price [days] # EU ETS carbon allowance (EUA) price historyzl python cli.py global-prices # Current carbon prices across global compliance marketszg python cli.py market-stats # Comprehensive carbon market statistics and trendsza python cli.py emissions-by-sector [jurisdiction] # Emissions breakdown by sector (EU, UK, USA)zl python cli.py compare-markets [market1,market2] # Compare carbon pricing mechanisms across jurisdictionsz| python cli.py offset-projects [type] # Carbon offset project types and registries (forestry, renewable, etc.)z' Container Port Throughput (Phase 193):zr python cli.py port-all # All major ports (Shanghai, Rotterdam, LA/Long Beach) summaryza python cli.py port-shanghai # Shanghai port TEU volumes (world's largest)zc python cli.py port-rotterdam # Rotterdam port TEU volumes (Europe's largest)ze python cli.py port-la-long-beach # LA/Long Beach combined TEU volumes (US gateway)za python cli.py port-compare # Compare throughput across all tracked portsz\ python cli.py port-list # List all available ports with metadataz[ python cli.py port-rankings # Global top 20 container port rankingsN)
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