# Macro Economic Dashboard > Macro economic inter-market analysis dashboard — DXY, VIX, yield curves, bond spreads, commodity flows, and cross-asset correlations. Use this skill whenever the user asks about "DXY", "dollar index", "VIX", "volatility index", "yield curve", "bond yields", "10-year", "2-10 spread", "yield inversion", "risk on risk off", "inter-market", "commodity flows", "gold vs dollar", "oil vs CAD", "equities vs forex", "macro overview", "big picture", "cross-asset", "safe havens", or any macro-level inter-market relationship analysis. This is the macro context layer that sits above pair-level analysis. - Skill: `mahmoud20138/macro-economic-dashboard` (Agent Skill) - Install (CLI): `npx skillmds@latest add mahmoud20138/macro-economic-dashboard` - Raw SKILL.md: https://api.skillmd.com/api/skills/mahmoud20138/macro-economic-dashboard/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: mahmoud20138 (https://skillmd.com/u/mahmoud20138) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/mahmoud20138/macro-economic-dashboard --- # Macro Economic Dashboard ## Overview Maps the macro landscape across asset classes — currencies, bonds, equities, commodities. Identifies risk-on/risk-off conditions, yield curve signals, and cross-asset divergences that drive currency trends. --- ## 1. Key Macro Instruments ```python MACRO_INSTRUMENTS = { "dollar": { "DXY": {"description": "US Dollar Index", "impact": "USD strength gauge"}, }, "volatility": { "VIX": {"description": "CBOE Volatility Index", "impact": "Fear gauge — high VIX = risk-off"}, }, "bonds": { "US10Y": {"description": "US 10-Year Treasury Yield"}, "US02Y": {"description": "US 2-Year Treasury Yield"}, "US30Y": {"description": "US 30-Year Treasury Yield"}, "DE10Y": {"description": "German 10-Year Bund Yield"}, "JP10Y": {"description": "Japan 10-Year JGB Yield"}, "UK10Y": {"description": "UK 10-Year Gilt Yield"}, }, "commodities": { "XAUUSD": {"description": "Gold", "impact": "Safe haven, inverse USD"}, "XAGUSD": {"description": "Silver", "impact": "Industrial + precious"}, "WTI": {"description": "Crude Oil", "impact": "CAD, NOK, RUB driver"}, "BRENT": {"description": "Brent Crude", "impact": "Global energy benchmark"}, }, "equity_indices": { "SPX": {"description": "S&P 500", "impact": "US risk appetite"}, "NDX": {"description": "Nasdaq 100", "impact": "Tech/growth sentiment"}, "DAX": {"description": "German DAX", "impact": "EU risk appetite"}, "NI225": {"description": "Nikkei 225", "impact": "JPY flows"}, }, } ``` --- ## 2. Inter-Market Relationship Engine ```python import pandas as pd import numpy as np INTER_MARKET_RULES = [ {"condition": "DXY rising", "effect": "EURUSD falls, GBPUSD falls, Gold falls", "reliability": 0.85}, {"condition": "DXY falling", "effect": "EURUSD rises, GBPUSD rises, Gold rises", "reliability": 0.85}, {"condition": "VIX > 25", "effect": "Risk-off: JPY, CHF, Gold rise; AUD, NZD fall", "reliability": 0.80}, {"condition": "VIX < 15", "effect": "Risk-on: AUD, NZD rise; JPY, CHF fall", "reliability": 0.75}, {"condition": "US10Y rising", "effect": "USD tends to strengthen, Gold weakens", "reliability": 0.70}, {"condition": "US10Y falling", "effect": "USD may weaken, Gold strengthens", "reliability": 0.65}, {"condition": "2-10 spread inverting", "effect": "Recession signal — risk-off ahead", "reliability": 0.60}, {"condition": "Oil rising sharply", "effect": "CAD strengthens, inflation fears, JPY weakens", "reliability": 0.70}, {"condition": "Oil falling sharply", "effect": "CAD weakens, deflation signal", "reliability": 0.70}, {"condition": "SPX + Gold both rising", "effect": "Liquidity expansion — everything bid", "reliability": 0.55}, {"condition": "SPX falling + Gold rising", "effect": "Classic risk-off rotation", "reliability": 0.80}, {"condition": "SPX falling + Gold falling", "effect": "Liquidity crisis — cash is king", "reliability": 0.75}] class MacroDashboard: """Analyze macro conditions and their FX implications.""" @staticmethod def risk_regime(vix: float, spx_change: float, gold_change: float, dxy_change: float) -> dict: """Classify current risk environment.""" if vix > 30 and spx_change < -0.5: regime = "RISK-OFF EXTREME" fx_impact = "JPY, CHF surge. AUD, NZD, EM currencies under pressure." elif vix > 20 and spx_change < 0: regime = "RISK-OFF" fx_impact = "JPY, CHF firm. AUD, NZD soft. USD mixed (safe haven but rates)." elif vix < 15 and spx_change > 0: regime = "RISK-ON" fx_impact = "AUD, NZD, EM strong. JPY, CHF weak. Carry trades favored." elif vix < 12: regime = "COMPLACENT" fx_impact = "Low vol environment. Carry works. Watch for vol spike reversal." else: regime = "NEUTRAL" fx_impact = "Mixed signals. Trade on pair-specific fundamentals." return { "regime": regime, "vix": vix, "fx_impact": fx_impact, "safe_haven_flow": vix > 20, "carry_environment": vix < 18 and spx_change > 0, } @staticmethod def yield_curve_analysis(us2y: float, us10y: float, us30y: float) -> dict: """Analyze US yield curve for economic signals.""" spread_2_10 = us10y - us2y spread_10_30 = us30y - us10y if spread_2_10 < 0: curve_state = "INVERTED" signal = "Recession warning — historically leads recession by 6-18 months" elif spread_2_10 < 0.25: curve_state = "FLAT" signal = "Slowdown signal — economy losing momentum" elif spread_2_10 > 1.5: curve_state = "STEEP" signal = "Growth signal — economy expanding, rates expected to rise" else: curve_state = "NORMAL" signal = "Healthy curve — no extreme signal" return { "curve_state": curve_state, "spread_2_10": round(spread_2_10, 3), "spread_10_30": round(spread_10_30, 3), "signal": signal, "us2y": us2y, "us10y": us10y, "us30y": us30y, "fx_implications": { "INVERTED": "USD may weaken medium-term. Safe havens favored.", "STEEP": "USD may strengthen on growth. Risk-on currencies favored.", "FLAT": "Uncertainty. Range-bound FX likely.", "NORMAL": "Fundamentals-driven. Follow rate differentials.", }.get(curve_state, ""), } @staticmethod def dollar_regime(dxy_current: float, dxy_sma50: float, dxy_sma200: float) -> dict: """Classify USD regime from DXY.""" if dxy_current > dxy_sma50 > dxy_sma200: return {"regime": "STRONG DOLLAR", "bias": "USD bullish — sell EURUSD, GBPUSD. Buy USDJPY.", "trend": "uptrend", "dxy": dxy_current} elif dxy_current < dxy_sma50 < dxy_sma200: return {"regime": "WEAK DOLLAR", "bias": "USD bearish — buy EURUSD, GBPUSD. Sell USDJPY.", "trend": "downtrend", "dxy": dxy_current} return {"regime": "MIXED DOLLAR", "bias": "No clear USD trend. Trade cross-pairs.", "trend": "sideways", "dxy": dxy_current} @staticmethod def commodity_fx_links(oil_change: float, gold_change: float) -> dict: """Map commodity moves to currency implications.""" links = [] if abs(oil_change) > 1: direction = "rising" if oil_change > 0 else "falling" links.append({ "commodity": "Oil", "move": f"{direction} ({oil_change:+.1f}%)", "fx_impact": f"CAD {'strengthens' if oil_change > 0 else 'weakens'} — " f"{'buy' if oil_change > 0 else 'sell'} USDCAD", }) if abs(gold_change) > 0.5: direction = "rising" if gold_change > 0 else "falling" links.append({ "commodity": "Gold", "move": f"{direction} ({gold_change:+.1f}%)", "fx_impact": f"Safe haven {'bid' if gold_change > 0 else 'offered'} — " f"AUD {'supported' if gold_change > 0 else 'pressured'} (gold exporter)", }) return {"links": links, "rules_checked": len(INTER_MARKET_RULES)} ``` --- ## Web Search Queries for Real-Time Data ``` web_search("DXY dollar index today") web_search("VIX index current level") web_search("US 10 year treasury yield today") web_search("US 2-10 yield curve spread") web_search("oil price WTI today") web_search("S&P 500 today risk sentiment") ```