Market Correlation Trading

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

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

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