market-correlation-trading

name	market-correlation-trading
description	Measure time-varying cross-asset correlation, beta, lead-lag, and spread stationarity. Use when evaluating hedges, common factors, regime breaks, divergences, or convergence hypotheses.
license	Apache-2.0
metadata	{"author":"ske-labs","version":"4.0"}

Market Correlation Trading

Measure time-varying co-movement and test whether a hedge, factor exposure, or stationary spread exists. Divergence can reflect a regime change; correlation alone does not imply convergence, causation, or lead-lag.

Measurement

• Align exchange calendars, timestamps, currencies, and return intervals; do not correlate price levels.
• Compute rolling Pearson and rank correlation over predeclared short and long windows, with confidence intervals and enough observations.
• Estimate rolling beta or a multi-factor model when the objective is hedging.
• Require an economically linked, stationary spread and out-of-sample half-life before proposing convergence.
• Test lead-lag with lagged returns while controlling common factors and multiple comparisons.

Divergence Signals

Scenario	Signal
BTC rallies but Nasdaq flat/down	BTC overextended, watch for pullback
Gold falls but real yields also fall	Gold undervalued, potential buy
Oil rises but energy stocks lag	Energy stocks may catch up
VIX rises but S&P holds	Hedging without selling, watch for resolution

Use 20/60 bars only as example windows. Calibrate the windows and breakdown threshold in training data, then report estimates, uncertainty, and observation count.

Lead-Lag Hypotheses

For every proposed leader/follower pair, state the economic mechanism, data clock, lags tried, common-factor controls, and held-out result. Never copy a fixed lag table into a trade.

Regime-Dependent Correlations

Regime	Correlation Behavior
Risk-on (normal)	Traditional correlations hold
Risk-off (crisis)	Everything correlates -- stocks, crypto, commodities drop; only USD/treasuries/gold rise
Inflation	Stocks and bonds fall together (atypical positive correlation)
Deflation	Stocks fall, bonds rise (traditional inverse)

Workflow

1. Check Related Assets

get_candles(symbol="SPY", exchange=<exchange>, interval="1D", count=250)
get_candles(symbol="QQQ", exchange=<exchange>, interval="1D", count=250)
get_candles(symbol="TLT", exchange=<exchange>, interval="1D", count=250)
get_candles(symbol="GLD", exchange=<exchange>, interval="1D", count=250)

Compare recent performance (1W, 1M, 3M) across correlated pairs.

2. Research Macro Context

get_financial_news(topic="correlation stocks bonds regime shift <current year>", max_results=10)
get_economics_calendar(from_date=<start>, to_date=<end>, impact="high")

Determine whether current correlations are driven by Fed policy, inflation, or event-specific factors. High-impact macro events can trigger regime shifts.

3. Identify and Report Divergences

Report return definition, windows, estimates/uncertainty, beta/factor exposures, divergence z-score, stationarity result, costs, and hedge, watch, or no trade. Do not call an asset mispriced from correlation alone.

Evidence and Validation

• Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
• Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
• Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
• Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
• Research basis: Ang & Bekaert finds correlations and volatilities vary by regime and often rise in bad times; a static correlation table is not a trading signal.

Key Rules

• Never assume correlations are permanent; show rolling estimates and adverse stresses toward +1 or -1.
• Include macro/factor regime and stress correlations; diversification can weaken without every asset moving together.
• Aggregate positions with shared beta/factor/scenario risk rather than relying on one pair correlation.
• Correlation is not causation or convergence; control for common drivers where possible.
• When a historical relationship changes, test for a regime break before proposing convergence.

Related Skills

• sector-rotation -- Sector correlations reveal rotation opportunities
• economic-calendar-trading -- Macro events drive correlation regime shifts